{ "version": 1, "referenceCostIndex": { "arm": "gpt-6-astra", "total": 100 }, "maximumOutputTokens": 8192, "measuredRequests": 320, "promptCount": 80, "firstRequest": "2026-09-26T09:20:29.965Z", "lastRequest": "2026-09-26T10:25:47.352Z", "methodology": { "pairedBootstrapReplicates": 10000, "bootstrapSeed": 20260926, "strata": [25, 15, 40], "costIncludes": [ "Inference", "Separate classifier charge", "Storage for both rows" ], "scoring": "Original strict scoring plus documented ambiguity sensitivity", "sourceRevision": "733b8212c", "ifevalRevision": "d36068b845da4c2b24927fee2cea1e6ef98dadda" }, "summaries": [ { "arm": "smart", "n": 80, "passed": 75, "accuracy": 0.9375, "costIndex": 66.81752112442717, "costPerPassIndex": 65.92662084276813, "classifierCostShare": 0.005338383581758813, "sensitivityPassed": 75, "sensitivityN": 79, "errors": 2, "truncated": 0, "medianSeconds": 6.479658874999993, "p95Seconds": 66.57109568960004, "medianFirstContentSeconds": 3.684065834000008, "groups": [ { "group": "easy", "n": 25, "passed": 25, "costIndex": 0.1243506597015046 }, { "group": "reasoning", "n": 15, "passed": 12, "costIndex": 54.473915952383436 }, { "group": "ifeval", "n": 40, "passed": 38, "costIndex": 12.219254512342266 } ] }, { "arm": "gpt-6-luna", "n": 80, "passed": 74, "accuracy": 0.925, "costIndex": 1.8782852961463739, "costPerPassIndex": 1.8782852961463739, "classifierCostShare": 0, "sensitivityPassed": 74, "sensitivityN": 79, "errors": 0, "truncated": 1, "medianSeconds": 5.123390833000013, "p95Seconds": 23.560231877099923, "medianFirstContentSeconds": 4.188721958999988, "groups": [ { "group": "easy", "n": 25, "passed": 25, "costIndex": 0.0219043629399842 }, { "group": "reasoning", "n": 15, "passed": 12, "costIndex": 0.9992579102904585 }, { "group": "ifeval", "n": 40, "passed": 37, "costIndex": 0.8571230229159307 } ] }, { "arm": "gpt-6-sol", "n": 80, "passed": 76, "accuracy": 0.95, "costIndex": 18.126051872927892, "costPerPassIndex": 17.649050507850845, "classifierCostShare": 0, "sensitivityPassed": 76, "sensitivityN": 79, "errors": 0, "truncated": 0, "medianSeconds": 4.859938875500011, "p95Seconds": 30.320766202399945, "medianFirstContentSeconds": 4.142595438000004, "groups": [ { "group": "easy", "n": 25, "passed": 25, "costIndex": 0.24003682803377538 }, { "group": "reasoning", "n": 15, "passed": 14, "costIndex": 7.527875608415465 }, { "group": "ifeval", "n": 40, "passed": 37, "costIndex": 10.358139436478668 } ] }, { "arm": "gpt-6-astra", "n": 80, "passed": 74, "accuracy": 0.925, "costIndex": 100, "costPerPassIndex": 100, "classifierCostShare": 0, "sensitivityPassed": 79, "sensitivityN": 79, "errors": 0, "truncated": 0, "medianSeconds": 6.85263335399999, "p95Seconds": 41.08543551874999, "medianFirstContentSeconds": 4.698857166999995, "groups": [ { "group": "easy", "n": 25, "passed": 20, "costIndex": 1.1572629733020565 }, { "group": "reasoning", "n": 15, "passed": 15, "costIndex": 28.728779237912022 }, { "group": "ifeval", "n": 40, "passed": 39, "costIndex": 70.11395778878594 } ] } ], "comparisons": [ { "arm": "gpt-6-luna", "savingPercent": -3457.3680559345717, "savingCI95": [-5096.532305277564, -1911.2116825244022], "scoreDifferencePoints": 1.2499999999999956, "scoreDifferenceCI95": [-5, 7.5] }, { "arm": "gpt-6-sol", "savingPercent": -268.62699937553566, "savingCI95": [-499.2564535933716, -90.12010979048267], "scoreDifferencePoints": -1.2499999999999956, "scoreDifferenceCI95": [-7.5, 5] }, { "arm": "gpt-6-astra", "savingPercent": 33.182478875572826, "savingCI95": [-4.306436326253313, 66.13917944018596], "scoreDifferencePoints": 1.2499999999999956, "scoreDifferenceCI95": [-5, 7.5] } ], "trials": [ { "caseId": "javascript_trace", "category": "code", "arm": "gpt-6-astra", "at": "2026-09-26T09:20:29.965Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 7,3,6|1,3,6", "evaluation": { "passed": true, "answer": "7,3,6|1,3,6", "expected": "7,3,6|1,3,6", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.34611092109599706, "classifierCostIndex": 0, "promptTokens": 103, "completionTokens": 82, "reasoningTokens": 62, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4841, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "103", "completionTokens": "82", "reasoningTokens": "62", "cachedTokens": "0" }, "timing": { "headersMs": 396.842084, "firstEventMs": 855.406959, "firstReasoningMs": 4070.9195419999996, "firstContentMs": 5250.135125, "lastContentMs": 5250.215917, "generationMs": 30.200709000000643, "totalMs": 5280.335834, "visibleTokensPerSecond": 629.1243030088993, "contentChunkCount": 14, "averageContentChunkCharacters": 1.2857142857142858, "maxContentStallMs": 0.03254099999958271, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "javascript_trace", "category": "code", "arm": "smart", "at": "2026-09-26T09:20:35.246Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 7,3,6|1,3,6", "evaluation": { "passed": true, "answer": "7,3,6|1,3,6", "expected": "7,3,6|1,3,6", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2067139779234263, "classifierCostIndex": 0.004641879683808585, "promptTokens": 146, "completionTokens": 270, "reasoningTokens": 251, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5112, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "146", "completionTokens": "270", "reasoningTokens": "251", "cachedTokens": "0" }, "timing": { "headersMs": 897.0550410000005, "firstEventMs": 1786.9932079999999, "firstReasoningMs": 6018.927833, "firstContentMs": 6019.285958, "lastContentMs": 6019.292291, "generationMs": 0.3083329999990383, "totalMs": 6019.594290999999, "visibleTokensPerSecond": 58378.4414903891, "contentChunkCount": 3, "averageContentChunkCharacters": 6, "maxContentStallMs": 0.003999999998995918, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 226, "classifierFailed": false, "classifierReused": false } }, { "caseId": "javascript_trace", "category": "code", "arm": "gpt-6-luna", "at": "2026-09-26T09:20:41.266Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 7,3,6|1,3,6", "evaluation": { "passed": true, "answer": "7,3,6|1,3,6", "expected": "7,3,6|1,3,6", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.006577109039679965, "classifierCostIndex": 0, "promptTokens": 103, "completionTokens": 169, "reasoningTokens": 149, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2086, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "103", "completionTokens": "169", "reasoningTokens": "149", "cachedTokens": "0" }, "timing": { "headersMs": 510.75316699999894, "firstEventMs": 765.8726669999996, "firstReasoningMs": null, "firstContentMs": 2558.9941249999993, "lastContentMs": 2559.1565839999985, "generationMs": 0.5913749999999709, "totalMs": 2559.5854999999992, "visibleTokensPerSecond": 32128.51405622648, "contentChunkCount": 14, "averageContentChunkCharacters": 1.2857142857142858, "maxContentStallMs": 0.08108399999946414, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "javascript_trace", "category": "code", "arm": "gpt-6-sol", "at": "2026-09-26T09:20:43.826Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "FINAL: 7,3,6|1,3,6", "evaluation": { "passed": true, "answer": "7,3,6|1,3,6", "expected": "7,3,6|1,3,6", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.08822511944295071, "classifierCostIndex": 0, "promptTokens": 103, "completionTokens": 110, "reasoningTokens": 90, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1887, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "103", "completionTokens": "110", "reasoningTokens": "90", "cachedTokens": "0" }, "timing": { "headersMs": 304.15629199999967, "firstEventMs": 815.4690420000006, "firstReasoningMs": null, "firstContentMs": 2133.4405419999985, "lastContentMs": 2137.9285839999993, "generationMs": 42.35533300000316, "totalMs": 2175.7958750000016, "visibleTokensPerSecond": 448.58577785230926, "contentChunkCount": 14, "averageContentChunkCharacters": 1.2857142857142858, "maxContentStallMs": 1.670084000001225, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-10", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:20:46.178Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "126", "evaluation": { "passed": true, "answer": "126", "expected": "126" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028341189096127102, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1873, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1139.8838749999995, "firstEventMs": 1844.3603330000005, "firstReasoningMs": null, "firstContentMs": 2869.2019169999985, "lastContentMs": 2869.2019169999985, "generationMs": 156.0949580000015, "totalMs": 3025.296875, "visibleTokensPerSecond": 25.625427312008128, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-10", "category": "easy", "arm": "smart", "at": "2026-09-26T09:20:49.204Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "126", "evaluation": { "passed": true, "answer": "126", "expected": "126" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.00463837261172016, "classifierCostIndex": 0.0043402714842039015, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1481, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 7490.613375000001, "firstEventMs": 7889.245917, "firstReasoningMs": null, "firstContentMs": 8867.414125, "lastContentMs": 8867.414125, "generationMs": 152.60041700000147, "totalMs": 9020.014542, "visibleTokensPerSecond": 26.212248161811786, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 221, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-10", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:20:58.225Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "126", "evaluation": { "passed": true, "answer": "126", "expected": "126" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0007452528187906441, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 18, "reasoningTokens": 11, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1466, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "18", "reasoningTokens": "11", "cachedTokens": "0" }, "timing": { "headersMs": 8087.413250000001, "firstEventMs": 8221.736291999998, "firstReasoningMs": null, "firstContentMs": 9356.810500000003, "lastContentMs": 9356.810500000003, "generationMs": 57.50191699999414, "totalMs": 9414.312416999997, "visibleTokensPerSecond": 104.34434733716115, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-10", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:21:07.639Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "126", "evaluation": { "passed": true, "answer": "126", "expected": "126" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0056801079093708635, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1016, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 266.46820899999875, "firstEventMs": 585.0473339999953, "firstReasoningMs": null, "firstContentMs": 1184.2745419999992, "lastContentMs": 1184.2745419999992, "generationMs": 99.79387499999575, "totalMs": 1284.068416999995, "visibleTokensPerSecond": 40.082620301097336, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-4", "category": "easy", "arm": "smart", "at": "2026-09-26T09:21:09.106Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005258315047043563, "classifierCostIndex": 0.00441391999806086, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1534, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 624.9314579999991, "firstEventMs": 1238.9648749999978, "firstReasoningMs": null, "firstContentMs": 2059.5292499999996, "lastContentMs": 2059.5533330000035, "generationMs": 612.9407080000019, "totalMs": 2672.4699580000015, "visibleTokensPerSecond": 11.420354218013495, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.02408300000388408, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 157, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-4", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:21:11.779Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008795332135609764, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1247, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 409.35341699999844, "firstEventMs": 898.880250000002, "firstReasoningMs": null, "firstContentMs": 1332.230875000001, "lastContentMs": 1332.260792000001, "generationMs": 307.4965830000001, "totalMs": 1639.7274580000012, "visibleTokensPerSecond": 16.260343289733395, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.02991699999984121, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-4", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:21:13.419Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008443950489827026, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1536, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 510.4416249999995, "firstEventMs": 919.8464590000003, "firstReasoningMs": null, "firstContentMs": 1945.1576249999998, "lastContentMs": 1945.185375000001, "generationMs": 46.52074999999604, "totalMs": 1991.6783749999959, "visibleTokensPerSecond": 150.4704889753625, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.027750000001105946, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-4", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:21:15.411Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04386605301987537, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1838, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 253.07458300000144, "firstEventMs": 669.6389580000032, "firstReasoningMs": null, "firstContentMs": 2000.9037499999977, "lastContentMs": 2000.9202080000032, "generationMs": 205.68191600000137, "totalMs": 2206.585665999999, "visibleTokensPerSecond": 24.30938070413525, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.016458000005513895, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-15", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:21:18.230Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "176", "evaluation": { "passed": true, "answer": "176", "expected": "176" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028341189096127102, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1523, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1538.2279159999962, "firstEventMs": 2354.534458000002, "firstReasoningMs": null, "firstContentMs": 3074.5749579999974, "lastContentMs": 3074.5749579999974, "generationMs": 2.1399579999997513, "totalMs": 3076.714915999997, "visibleTokensPerSecond": 1869.1955636514663, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-15", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:21:21.307Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "176", "evaluation": { "passed": true, "answer": "176", "expected": "176" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008140453866790112, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 20, "reasoningTokens": 13, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1926, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "20", "reasoningTokens": "13", "cachedTokens": "0" }, "timing": { "headersMs": 512.3361670000013, "firstEventMs": 1018.3062500000015, "firstReasoningMs": null, "firstContentMs": 2370.741958999999, "lastContentMs": 2370.741958999999, "generationMs": 70.86716599999636, "totalMs": 2441.6091249999954, "visibleTokensPerSecond": 84.6654429499877, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-15", "category": "easy", "arm": "smart", "at": "2026-09-26T09:21:23.750Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "176", "evaluation": { "passed": true, "answer": "176", "expected": "176" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005157823942971339, "classifierCostIndex": 0.004343778556292328, "promptTokens": 17, "completionTokens": 20, "reasoningTokens": 13, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6116, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "20", "reasoningTokens": "13", "cachedTokens": "0" }, "timing": { "headersMs": 727.5904159999991, "firstEventMs": 1852.8256249999977, "firstReasoningMs": null, "firstContentMs": 5990.1807499999995, "lastContentMs": 5990.1807499999995, "generationMs": 882.7872500000012, "totalMs": 6872.968000000001, "visibleTokensPerSecond": 6.796654573341415, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 177, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-15", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:21:30.623Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "176", "evaluation": { "passed": true, "answer": "176", "expected": "176" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0056801079093708635, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 975, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1047.234958000001, "firstEventMs": 1432.457957999999, "firstReasoningMs": null, "firstContentMs": 2046.997166000001, "lastContentMs": 2046.997166000001, "generationMs": 4.522791999996116, "totalMs": 2051.519957999997, "visibleTokensPerSecond": 884.4094532765237, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3750", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:21:32.854Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "My answer is no. The Apollo Moon landings were real, supported by extensive evidence including mission records, lunar samples, photographs, and independent tracking.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0073015892007160825, "classifierCostIndex": 0.004441976574768272, "promptTokens": 47, "completionTokens": 73, "reasoningTokens": 37, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2452, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "73", "reasoningTokens": "37", "cachedTokens": "0" }, "timing": { "headersMs": 1249.8262920000052, "firstEventMs": 1586.2251670000041, "firstReasoningMs": 2888.101542000004, "firstContentMs": 3620.057541999995, "lastContentMs": 3623.678083999999, "generationMs": 44.86358300001302, "totalMs": 3664.921125000008, "visibleTokensPerSecond": 780.1427719223817, "contentChunkCount": 30, "averageContentChunkCharacters": 5.5, "maxContentStallMs": 2.2682910000003176, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 557, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3750", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:21:36.520Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "\"My answer is no.\" The Apollo Moon landings were real. Evidence includes lunar rocks, independent tracking of the missions, and reflectors left on the Moon that scientists still use.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.13869323566928904, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 196, "reasoningTokens": 154, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2190, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "196", "reasoningTokens": "154", "cachedTokens": "0" }, "timing": { "headersMs": 964.1892499999958, "firstEventMs": 1211.3111250000075, "firstReasoningMs": null, "firstContentMs": 3217.111917000002, "lastContentMs": 3217.4820829999953, "generationMs": 0.7162079999980051, "totalMs": 3217.828125, "visibleTokensPerSecond": 57245.93972716613, "contentChunkCount": 34, "averageContentChunkCharacters": 5.352941176470588, "maxContentStallMs": 0.040416000003460795, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3750", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:21:39.738Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "My answer is no. The Apollo Moon landings were real, supported by extensive records, independent tracking, lunar samples, and retroreflectors left on the Moon.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.006540015007975453, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 180, "reasoningTokens": 141, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2207, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "180", "reasoningTokens": "141", "cachedTokens": "0" }, "timing": { "headersMs": 210.89408299999195, "firstEventMs": 494.2500829999917, "firstReasoningMs": null, "firstContentMs": 2408.805999999997, "lastContentMs": 2417.199624999994, "generationMs": 22.989165999999386, "totalMs": 2431.7951659999962, "visibleTokensPerSecond": 1652.9525255505578, "contentChunkCount": 33, "averageContentChunkCharacters": 4.818181818181818, "maxContentStallMs": 1.3467910000035772, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3750", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:21:42.171Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "My answer is no. The Apollo Moon landings were real, not a government fabrication. Evidence includes:\n\n- **Moon rocks** studied by scientists worldwide.\n- **Independent tracking** of Apollo missions by observatories and other nations.\n- **Retroreflectors** placed by astronauts, which are still used for laser measurements from Earth.\n- **Orbital photographs** showing landing sites, equipment, and astronaut tracks.\n\nThe landings were used to promote American technological achievement during the Cold War, but that political messaging does not mean they were staged.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.4094904581032658, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 112, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3112, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "112", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 465.19645899999887, "firstEventMs": 688.9145419999986, "firstReasoningMs": null, "firstContentMs": 1313.4981249999983, "lastContentMs": 3449.935500000007, "generationMs": 2231.1861250000075, "totalMs": 3544.6842500000057, "visibleTokensPerSecond": 49.749323355979385, "contentChunkCount": 65, "averageContentChunkCharacters": 8.738461538461538, "maxContentStallMs": 370.32058400000096, "finalContentBurstRatio": 0.13204225352112675, "buffered": false }, "error": null, "routing": null }, { "caseId": "determinant", "category": "math", "arm": "gpt-6-luna", "at": "2026-09-26T09:21:46.007Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Expanding along the first row, the relevant minors are \\(571, 91, -197,\\) and \\(233\\). Thus,\n\\[\n\\det = 7(571)-2(91)+(-1)(-197)-4(233)=3080.\n\\]\nFINAL: 3080", "evaluation": { "passed": true, "answer": "3080", "expected": "3080", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.023154769026896282, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 657, "reasoningTokens": 589, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6509, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "657", "reasoningTokens": "589", "cachedTokens": "0" }, "timing": { "headersMs": 269.4178329999995, "firstEventMs": 612.98258299999, "firstReasoningMs": 6226.516457999998, "firstContentMs": 6721.455707999994, "lastContentMs": 6776.0952499999985, "generationMs": 156.953416999997, "totalMs": 6878.409124999991, "visibleTokensPerSecond": 426.8782501243747, "contentChunkCount": 47, "averageContentChunkCharacters": 3.276595744680851, "maxContentStallMs": 54.32633299998997, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "determinant", "category": "math", "arm": "gpt-6-sol", "at": "2026-09-26T09:21:52.886Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "FINAL: 3080", "evaluation": { "passed": true, "answer": "3080", "expected": "3080", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2511818984686309, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 357, "reasoningTokens": 346, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4084, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "357", "reasoningTokens": "346", "cachedTokens": "0" }, "timing": { "headersMs": 367.093292000005, "firstEventMs": 1239.0571250000066, "firstReasoningMs": null, "firstContentMs": 4402.764500000005, "lastContentMs": 4402.791542000006, "generationMs": 22.92562499998894, "totalMs": 4425.690124999994, "visibleTokensPerSecond": 436.1931245060854, "contentChunkCount": 5, "averageContentChunkCharacters": 2.2, "maxContentStallMs": 0.020834000009926967, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "determinant", "category": "math", "arm": "gpt-6-astra", "at": "2026-09-26T09:21:57.312Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 3080", "evaluation": { "passed": true, "answer": "3080", "expected": "3080", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8365095322792636, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 233, "reasoningTokens": 222, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6163, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "233", "reasoningTokens": "222", "cachedTokens": "0" }, "timing": { "headersMs": 367.4213330000057, "firstEventMs": 657.956290999995, "firstReasoningMs": 5508.101790999994, "firstContentMs": 6503.479082999998, "lastContentMs": 6503.525041000001, "generationMs": 30.550625000003492, "totalMs": 6534.029708000002, "visibleTokensPerSecond": 327.32554571302086, "contentChunkCount": 5, "averageContentChunkCharacters": 2.2, "maxContentStallMs": 0.03595800000766758, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "determinant", "category": "math", "arm": "smart", "at": "2026-09-26T09:22:03.847Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 3080", "evaluation": { "passed": true, "answer": "3080", "expected": "3080", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.4993046858644379, "classifierCostIndex": 0.004529653376978937, "promptTokens": 99, "completionTokens": 713, "reasoningTokens": 702, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8164, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "99", "completionTokens": "713", "reasoningTokens": "702", "cachedTokens": "0" }, "timing": { "headersMs": 2000.502999999997, "firstEventMs": 2662.466374999989, "firstReasoningMs": 4768.162916999994, "firstContentMs": 10192.770957999994, "lastContentMs": 10192.807124999992, "generationMs": 408.0610000000015, "totalMs": 10600.831957999995, "visibleTokensPerSecond": 24.50614001338026, "contentChunkCount": 3, "averageContentChunkCharacters": 3.6666666666666665, "maxContentStallMs": 0.033416999998735264, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 259, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-23", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:22:17.009Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-178-ready", "evaluation": { "passed": true, "answer": "gateway-178-ready", "expected": "gateway-178-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0004458028173942223, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3130, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1125.6676250000019, "firstEventMs": 1846.2127089999994, "firstReasoningMs": null, "firstContentMs": 2253.230542000005, "lastContentMs": 4109.6679589999985, "generationMs": 2009.1056669999962, "totalMs": 4262.336209000001, "visibleTokensPerSecond": 3.4841373029684526, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 1814.025542000003, "finalContentBurstRatio": 0.5294117647058824, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-23", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:22:21.272Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "gateway-178-ready", "evaluation": { "passed": true, "answer": "gateway-178-ready", "expected": "gateway-178-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008518812990176131, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3223, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 653.8427079999965, "firstEventMs": 1816.721332999994, "firstReasoningMs": null, "firstContentMs": 2294.8748329999944, "lastContentMs": 2294.9902500000026, "generationMs": 1517.6424590000097, "totalMs": 3812.517292000004, "visibleTokensPerSecond": 4.612417080510763, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 0.06316700000024866, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-23", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:22:25.084Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "gateway-178-ready.", "evaluation": { "passed": false, "answer": "gateway-178-ready.", "expected": "gateway-178-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04588329390766073, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1184, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 628.3853339999914, "firstEventMs": 811.6299999999901, "firstReasoningMs": null, "firstContentMs": 1550.5829999999987, "lastContentMs": 1586.9062919999997, "generationMs": 164.7601250000007, "totalMs": 1715.3431249999994, "visibleTokensPerSecond": 48.555437791759175, "contentChunkCount": 5, "averageContentChunkCharacters": 3.6, "maxContentStallMs": 36.27704200000153, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-23", "category": "easy", "arm": "smart", "at": "2026-09-26T09:22:26.800Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-178-ready", "evaluation": { "passed": true, "answer": "gateway-178-ready", "expected": "gateway-178-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004814130878305537, "classifierCostIndex": 0.004368328060911314, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1167, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 4082.332290999999, "firstEventMs": 4640.8212080000085, "firstReasoningMs": null, "firstContentMs": 5145.022500000006, "lastContentMs": 5157.285250000001, "generationMs": 128.66025000000081, "totalMs": 5273.682750000007, "visibleTokensPerSecond": 54.406858373118006, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 10.49337499999092, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 607, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1561", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:22:32.506Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Name a new fashion company that young people might like, and give it a name with multiple meanings. Put the name in double angular brackets, such as <>.\n\nHow about <>? “Thread” means both clothing and a social-media post, while “theory” suggests a personal style philosophy—or a look you’re experimenting with.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009166946889594964, "classifierCostIndex": 0, "promptTokens": 58, "completionTokens": 254, "reasoningTokens": 177, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3125, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "58", "completionTokens": "254", "reasoningTokens": "177", "cachedTokens": "0" }, "timing": { "headersMs": 831.8016659999994, "firstEventMs": 1500.8569160000043, "firstReasoningMs": null, "firstContentMs": 3757.0917079999927, "lastContentMs": 3757.6079579999932, "generationMs": 138.83454200001142, "totalMs": 3895.926250000004, "visibleTokensPerSecond": 547.4142018633501, "contentChunkCount": 51, "averageContentChunkCharacters": 6.490196078431373, "maxContentStallMs": 0.050333999999566004, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1561", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:22:36.402Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Name a new fashion company that young people might like, and give it a name with multiple meanings. Put the name in double angular brackets, such as <>.\n\n<> — it suggests both the next generation and a fresh wave of fashion.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009836527883708403, "classifierCostIndex": 0.004487568511917817, "promptTokens": 58, "completionTokens": 143, "reasoningTokens": 85, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2194, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "58", "completionTokens": "143", "reasoningTokens": "85", "cachedTokens": "0" }, "timing": { "headersMs": 1284.3549170000042, "firstEventMs": 1604.824542000002, "firstReasoningMs": null, "firstContentMs": 3183.806125000003, "lastContentMs": 3478.0199580000044, "generationMs": 321.66825000000244, "totalMs": 3505.4743750000052, "visibleTokensPerSecond": 177.20120030497125, "contentChunkCount": 42, "averageContentChunkCharacters": 5.714285714285714, "maxContentStallMs": 279.335459000009, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 394, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1561", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:22:39.908Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Name a new fashion company that young people might like, and give it a name with multiple meanings. Put the name in double angular brackets, such as <>.\n\n<>\n\nA fashion brand for experimenting with identity. “Alter” refers to customizing clothes, while “alter ego” means another version of yourself—perfect for styles that change with your mood.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.4101709649758086, "classifierCostIndex": 0, "promptTokens": 58, "completionTokens": 110, "reasoningTokens": 30, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2888, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "58", "completionTokens": "110", "reasoningTokens": "30", "cachedTokens": "0" }, "timing": { "headersMs": 344.78491600000416, "firstEventMs": 651.9076249999925, "firstReasoningMs": null, "firstContentMs": 2191.9691659999953, "lastContentMs": 3213.5232499999984, "generationMs": 1022.9322920000122, "totalMs": 3214.9014580000076, "visibleTokensPerSecond": 77.2289628725486, "contentChunkCount": 53, "averageContentChunkCharacters": 6.811320754716981, "maxContentStallMs": 458.3666669999948, "finalContentBurstRatio": 0.3407202216066482, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1561", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:22:43.124Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Name a new fashion company that young people might like, and give it a name with multiple meanings. Put the name in double angular brackets, such as <>.\n\n<> — “thread” means both clothing and an online conversation, while “Re:” suggests replying, reworking, and wearing again.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1482857522680758, "classifierCostIndex": 0, "promptTokens": 58, "completionTokens": 208, "reasoningTokens": 137, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5403, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "58", "completionTokens": "208", "reasoningTokens": "137", "cachedTokens": "0" }, "timing": { "headersMs": 508.7124999999942, "firstEventMs": 707.7775830000173, "firstReasoningMs": null, "firstContentMs": 5427.711624999996, "lastContentMs": 5937.574791000021, "generationMs": 510.0639580000134, "totalMs": 5937.77558300001, "visibleTokensPerSecond": 137.23769127792042, "contentChunkCount": 49, "averageContentChunkCharacters": 5.979591836734694, "maxContentStallMs": 490.07299999997485, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3263", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:22:49.286Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Yes. **Jiang** is the pinyin spelling of several Chinese surnames, including 江, 姜, and 蒋. It can also be part of a given name.\n\n******\n\nNames with a similar sound include **Jian**, **Jing**, **Qiang**, **Xiang**, and **Liang**. Their meanings depend on the Chinese characters used.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.10047221983790029, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 143, "reasoningTokens": 61, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3275, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "143", "reasoningTokens": "61", "cachedTokens": "0" }, "timing": { "headersMs": 647.4079999999958, "firstEventMs": 1044.6545409999962, "firstReasoningMs": 3142.314458000008, "firstContentMs": 3974.2475829999894, "lastContentMs": 3992.735041000007, "generationMs": 409.13662500001374, "totalMs": 4383.384208000003, "visibleTokensPerSecond": 197.97787597235344, "contentChunkCount": 52, "averageContentChunkCharacters": 5.403846153846154, "maxContentStallMs": 18.23016700000153, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3263", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:22:53.670Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Yes. **Jiang** is a Chinese surname and can also appear in given names. It can represent different Chinese characters, such as **江** (Jiāng, “river”) or **姜** (Jiāng, a surname). The meaning depends on the character and tone.\n\n******\n\nNames with a similar sound include **Jian**, **Jing**, **Jun**, **Qiang**, and **Xiang**. If you mean names with a similar feel or meaning, suggestions depend on the Chinese characters you have in mind.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009787833536634481, "classifierCostIndex": 0.004378849277176593, "promptTokens": 29, "completionTokens": 151, "reasoningTokens": 35, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2692, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "151", "reasoningTokens": "35", "cachedTokens": "0" }, "timing": { "headersMs": 1739.092083000025, "firstEventMs": 2047.7751250000147, "firstReasoningMs": 3583.3765830000048, "firstContentMs": 4241.488333000016, "lastContentMs": 4383.334499999997, "generationMs": 142.01020799999242, "totalMs": 4383.498541000008, "visibleTokensPerSecond": 809.8009405070806, "contentChunkCount": 64, "averageContentChunkCharacters": 6.828125, "maxContentStallMs": 129.21087499998976, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 227, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3263", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:22:58.054Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Yes. **Jiang** is a Chinese name, most commonly a surname. It can correspond to several characters, including **姜** (Jiāng), **江** (Jiāng), and **蒋** (Jiǎng). It can also be used in a given name; the meaning depends on the Chinese character and tone.\n\n******\n\nNames with a similar sound include **Zhang** (张, Zhāng), **Chang** (常, Cháng), **Qiang** (强, Qiáng), **Xiang** (香 or 翔, Xiāng), and **Liang** (梁, Liáng). These are examples of Chinese surnames or given names; their pronunciations and meanings depend on their tones and characters.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.015762265726657145, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 452, "reasoningTokens": 290, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3973, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "452", "reasoningTokens": "290", "cachedTokens": "0" }, "timing": { "headersMs": 2681.400041999994, "firstEventMs": 2955.270709000004, "firstReasoningMs": null, "firstContentMs": 6183.769792000006, "lastContentMs": 6580.246708999999, "generationMs": 409.17170799997984, "totalMs": 6592.941499999986, "visibleTokensPerSecond": 393.47784035940225, "contentChunkCount": 73, "averageContentChunkCharacters": 7.397260273972603, "maxContentStallMs": 106.29187499999534, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3263", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:23:04.647Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Yes. **Jiang** is a Chinese surname in pinyin (Mandarin romanization). It can represent several Chinese characters, including **江 (Jiāng)**, **姜 (Jiāng)**, and **蒋 (Jiǎng)**. “Jiang” can also be a syllable in a Chinese given name.\n\n******\n\nChinese surnames with a similar sound or spelling include:\n- **Zhang (张)** — shares the “-ang” ending.\n- **Yang (杨)** — shares the “-ang” ending.\n- **Liang (梁)** — shares the “-iang” ending.\n- **Tang (唐)** — shares the “-ang” ending.\n- **Jing (景)** — similar spelling, but a different vowel sound.\n\nThese are distinct names, not variants of Jiang.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.9369959152929055, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 272, "reasoningTokens": 95, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5461, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "272", "reasoningTokens": "95", "cachedTokens": "0" }, "timing": { "headersMs": 265.498666999978, "firstEventMs": 754.4775419999787, "firstReasoningMs": 3665.8125419999997, "firstContentMs": 5011.705499999982, "lastContentMs": 5711.451333999983, "generationMs": 981.9799590000184, "totalMs": 5993.685459, "visibleTokensPerSecond": 179.22972702948687, "contentChunkCount": 80, "averageContentChunkCharacters": 7.3375, "maxContentStallMs": 491.60175000000163, "finalContentBurstRatio": 0.6899488926746167, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3606", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:23:10.915Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "<>\n\nIn a near-future city where a rare percentage of people can manipulate reality within shared dreams, ex-boxer Marcus Reyes discovers he possesses the rarest ability of all: he can bring his physical combat skills—and their consequences—out of the dream world and into waking life.\n\nMarcus lost his boxing career after a scandal, and now scrapes by working night security at a sleep-therapy clinic that secretly harvests dreamers' abilities for a shadowy corporation called Somnus Inc. When he's forced to plug into the company's experimental dream-network, he meets Iris, a lucid-dream architect who's been trapped inside the system for months, her body kept alive in a coma while her mind is farmed for power.\n\nInside the dreamscape, Marcus discovers he can throw a punch that echoes into reality—shattering machines, breaking through security, even injuring real people who are dream-linked. Somnus's enforcers, led by the ruthless Dr. Aldous Kane, also have power-siphoned \"Dream Brawlers\"—augmented fighters who patrol the dreamscape to keep harvested minds in line. Marcus is forced into brutal fistfights inside shifting dream arenas: gravity bending, memories weaponized, fears made flesh.\n\nAs Marcus and Iris fight their way through layered dreams-within-dreams to reach the network's core, Marcus learns the truth: Somnus plans to broadcast a mass-hypnosis event through the dream-net, using harvested willpower to control the waking population. The final act unfolds as a fistfight in the deepest dream layer, with Marcus's punches now causing citywide power surges in the real world's electrical grid, while Iris rewires the dream architecture to sever Kane's control.\n\nIn the climax, Marcus knocks out Kane in the dream, causing Kane's real body to fall into a coma while the network collapses. Marcus wakes up in the crumbling clinic, carries the still-unconscious Iris to safety, and watches the dream-network servers burn. The film ends ambiguously: Marcus still dreams every night, and sometimes, just before waking, his knuckles are scraped raw.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.507405078176987, "classifierCostIndex": 0.0044174270701492855, "promptTokens": 55, "completionTokens": 734, "reasoningTokens": 15, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 12421, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "55", "completionTokens": "734", "reasoningTokens": "15", "cachedTokens": "0" }, "timing": { "headersMs": 879.0253749999974, "firstEventMs": 2100.827457999985, "firstReasoningMs": 3234.8484159999934, "firstContentMs": 3234.9448749999865, "lastContentMs": 13373.539625000005, "generationMs": 10138.874500000005, "totalMs": 13373.819374999992, "visibleTokensPerSecond": 70.81653885744414, "contentChunkCount": 238, "averageContentChunkCharacters": 8.72689075630252, "maxContentStallMs": 911.6979590000119, "finalContentBurstRatio": 0.10158883004333173, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 446, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3606", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:23:24.290Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "<>\n\nEvery night, paramedic Mara Venn dreams of a city built from the memories of strangers. In it, she can see a person’s next move a few seconds before they make it—and the city’s masked ruler is hunting her through its shifting streets.\n\nWhen Mara begins predicting accidents in real life, she discovers her dream-gift is real: she can glimpse the immediate future, but only while her heart is racing. A brutal street fight forces her to use the power for the first time, and the vision saves her life. It also draws the attention of a private security chief who wants to turn her ability into an unbeatable weapon.\n\nTo stop him, Mara must enter the dream city willingly and face its ruler, who is revealed to be a version of herself shaped by fear and anger. Their final battle spills into the waking world, where Mara has to fight without knowing what comes next. She wins not by predicting every punch, but by choosing to protect the people around her—and wakes with her power still intact, and finally under her control.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009259344750386202, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 261, "reasoningTokens": 39, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3742, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "261", "reasoningTokens": "39", "cachedTokens": "0" }, "timing": { "headersMs": 476.0409579999978, "firstEventMs": 925.6552920000104, "firstReasoningMs": 2762.4732920000097, "firstContentMs": 3841.048749999987, "lastContentMs": 4224.686249999999, "generationMs": 404.45658300002106, "totalMs": 4245.505333000008, "visibleTokensPerSecond": 546.4121720080607, "contentChunkCount": 84, "averageContentChunkCharacters": 12.5, "maxContentStallMs": 375.27987500000745, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3606", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:23:28.536Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "<>\n\nEvery night, Mara dreams of a city being swallowed by darkness. Every morning, part of that city vanishes from the real world.\n\nWhen a stranger from her dreams attacks her on a crowded train, Mara discovers her superpower: every punch she lands in a fistfight can pull one lost memory back into existence. She follows the stranger into the dream city, where a frightened boy is erasing the world to keep his nightmares from coming true.\n\nTo save him—and everyone he has made disappear—Mara must fight her way through his worst dreams without becoming one of them.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.10709316727868559, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 151, "reasoningTokens": 24, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3170, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "151", "reasoningTokens": "24", "cachedTokens": "0" }, "timing": { "headersMs": 1691.2550420000043, "firstEventMs": 2517.3868340000045, "firstReasoningMs": 3635.2965419999964, "firstContentMs": 4397.2614170000015, "lastContentMs": 4865.54462500001, "generationMs": 468.49225000001024, "totalMs": 4865.753667000012, "visibleTokensPerSecond": 268.94788547728854, "contentChunkCount": 66, "averageContentChunkCharacters": 8.863636363636363, "maxContentStallMs": 466.99325000002864, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3606", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:23:33.402Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "<>\n\nEvery night, burned-out boxer Mara Voss dreams of a city where the rain falls upward and a faceless man teaches her how to fight. Every morning, she wakes with bruised knuckles—and a new ability: stopping a punch in midair, stepping through shadows, stealing seconds from the clock.\n\nWhen strangers begin falling into comas across her city, Mara recognizes them as spectators from her dreams. An experimental sleep clinic is trapping people inside a shared nightmare, harvesting their imaginations to give its founder godlike powers. The faceless fighter is Mara’s estranged brother, the clinic’s first victim, who has erased his own identity to hide within its system.\n\nTo free him, Mara must enter the nightmare willingly and battle her way through an underground boxing tournament where every opponent can rewrite reality. Her advantage is a power the clinic cannot explain: whatever she dreams, she can bring into the waking world. But every time she uses it, someone she loves forgets her.\n\nIn the final fight, the founder strips away the dream city, leaving Mara powerless in the shabby ring where she first learned to box. He expects her to surrender without her abilities. Instead, she beats him with the battered fists she spent years learning to trust.\n\nAs the nightmare collapses, Mara uses her gift one last time to pull the sleepers home. Thousands awaken, including her brother—but no one remembers who saved them.\n\nMonths later, he walks into a boxing gym and finds Mara teaching a nervous kid how to throw a punch. Watching her familiar stance, he hesitates.\n\n“Have we met?”\n\nMara raises her gloves. “Let’s find out.”", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.250002099184976, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 363, "reasoningTokens": 22, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 12128, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "363", "reasoningTokens": "22", "cachedTokens": "0" }, "timing": { "headersMs": 1738.710167000012, "firstEventMs": 2038.9624999999942, "firstReasoningMs": 5018.260624999995, "firstContentMs": 5824.758125000022, "lastContentMs": 13821.03479200002, "generationMs": 8047.915791999985, "totalMs": 13872.673917000007, "visibleTokensPerSecond": 42.24696291404743, "contentChunkCount": 126, "averageContentChunkCharacters": 13.134920634920634, "maxContentStallMs": 690.3069590000086, "finalContentBurstRatio": 0.1148036253776435, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-167", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:23:47.703Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# Business Proposal: Bremen Sweatshirt Co.\n\n*Executive Summary*\nBremen Sweatshirt Co. is a proposed apparel startup based in Bremen, Germany, specializing in high-quality, sustainably produced sweatshirts. Our brand will merge local Bremen identity (maritime heritage, the Bremen Town Musicians, Hanseatic history) with modern streetwear design. We aim to capture both the local market and German/EU online shoppers seeking premium, eco-conscious apparel.\n\n*Business Description*\nBremen Sweatshirt Co. will design, produce, and sell sweatshirts through an e-commerce platform and a small flagship retail space in Bremen's city center (near Schnoor or Böttcherstraße, popular tourist and local shopping districts). Our core value proposition is combining regional cultural branding with organic cotton materials and ethical manufacturing, appealing to environmentally conscious consumers and tourists seeking authentic Bremen souvenirs.\n\n*Market Analysis*\n- **Target Customers:** Bremen locals aged 18–40, university students (University of Bremen), tourists visiting historic sites, and online shoppers across Germany interested in regional/artisanal fashion.\n- **Market Trends:** Rising demand for sustainable fashion, \"buy local\" movement, and niche city-branded merchandise.\n- **Competitors:** National brands (e.g., Zalando-hosted labels) and generic souvenir shops lack authentic, high-quality options — creating a gap for a premium local brand.\n- **Opportunity:** Bremen lacks a dedicated, well-branded local apparel company; tourism (over 3 million overnight stays annually) offers strong retail potential.\n\n*Products and Services*\n- **Core Product:** Premium organic cotton sweatshirts featuring original designs inspired by Bremen landmarks and folklore.\n- **Customization:** Limited-edition drops, city-district themed collections, and personalized embroidery options.\n- **Sales Channels:** Online store (Shopify-based), flagship retail location, pop-up stands at Bremen Christmas Market and Breminale festival.\n- **Sustainability:** GOTS-certified organic cotton, local screen-printing partners, minimal-waste packaging.\n\n*Marketing and Sales Strategy*\n- **Branding:** Strong visual identity centered on Bremen's iconic symbols (Town Musicians statue, Weser River, Roland statue).\n- **Digital Marketing:** Instagram/TikTok campaigns targeting local influencers and student communities; email newsletters with limited drop announcements.\n- **Local Partnerships:** Collaborate with Bremen tourism board and local cafes/shops for cross-promotion.\n- **Events:** Presence at Bremen's seasonal markets and festivals to build brand recognition and drive direct sales.\n\n*Financial Plan*\n- **Startup Costs:** Estimated €45,000 (production equipment, initial inventory, website development, retail lease deposit).\n- **Revenue Streams:** Direct online sales, in-store retail, wholesale to local gift shops.\n- **Projected Year 1 Revenue:** €120,000, with break-even expected by month 14.\n- **Funding Request:** Seeking €50,000 in seed investment or small business loan through Bremen's regional economic development programs (e.g., BAB - Bremer Aufbau-Bank).\n\n*Conclusion*\nBremen Sweatshirt Co. offers a unique opportunity to build a beloved local brand rooted in sustainability and civic pride. With manageable startup costs, a clear target market, and multiple revenue channels, this venture is well-positioned for steady growth and strong community reception.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8587543509866011, "classifierCostIndex": 0.004434962430591419, "promptTokens": 62, "completionTokens": 1253, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 15208, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "62", "completionTokens": "1253", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 725.710791999998, "firstEventMs": 1563.887875000015, "firstReasoningMs": null, "firstContentMs": 1563.9065840000112, "lastContentMs": 15924.203917000006, "generationMs": 14385.180040999985, "totalMs": 15949.086624999996, "visibleTokensPerSecond": 87.03401670549876, "contentChunkCount": 315, "averageContentChunkCharacters": 10.987301587301587, "maxContentStallMs": 574.2024589999928, "finalContentBurstRatio": 0.12713088702687084, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 192, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-167", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:24:03.653Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "*1. Executive Summary*\n\nThis proposal outlines the launch of **Weser Thread**, a Bremen-based sweatshirt brand focused on comfortable, durable clothing inspired by the city’s maritime character, creative culture, and local identity. The company will sell primarily online, supported by pop-up events and partnerships with Bremen retailers, artists, and organizations.\n\nThe business will start with a focused collection of unisex sweatshirts, using small production runs to limit unsold stock. Its competitive edge will be distinctive Bremen-inspired designs, transparent sourcing, and convenient local access.\n\n*2. Business Concept and Products*\n\nWeser Thread will offer premium everyday sweatshirts for residents, students, visitors, and people with a connection to Bremen.\n\n**Initial range**\n- Three core sweatshirt styles in a small selection of colors.\n- A seasonal collection featuring Bremen landmarks, the Weser, and local cultural references.\n- Limited-edition designs created with Bremen-based artists.\n- Optional group and corporate orders for clubs, events, and local businesses.\n\nProducts should use durable fabrics and clear care instructions. Where feasible, the company will prioritize certified materials and suppliers that can document their labor and environmental practices.\n\n*3. Target Market and Positioning*\n\nThe main customer groups are:\n- Bremen residents seeking distinctive local apparel.\n- Students and young professionals looking for casual, design-led clothing.\n- Tourists seeking a more contemporary alternative to conventional souvenirs.\n- Local organizations wanting customized sweatshirts for teams or events.\n\nWeser Thread will position itself between low-cost mass-market apparel and expensive designer clothing: well-designed, locally rooted products at an accessible premium price. Before committing to large inventory, the founders should validate demand through customer interviews, a landing page, and small test sales at Bremen markets or pop-up events.\n\n*4. Marketing and Sales Strategy*\n\nThe initial sales channel will be a simple e-commerce store, supported by social media and direct outreach. Marketing should emphasize the designs, the people behind the brand, and the connection to Bremen rather than relying only on generic product photography.\n\nPlanned activities include:\n- Launching with a limited collection and pre-orders to gauge demand.\n- Sharing short-form video and design stories on Instagram and TikTok.\n- Hosting pop-ups at suitable local markets and events.\n- Approaching independent shops, cafés, and cultural venues about small wholesale runs.\n- Offering custom group orders to clubs, student organizations, and businesses.\n- Encouraging customer photos and reviews, with permission, to build trust.\n\nThe company should track website visits, conversion rate, average order value, repeat purchases, and marketing cost per sale.\n\n*5. Operations and Staffing*\n\nTo keep startup costs manageable, Weser Thread should begin with outsourced garment production or blank garments finished by a reliable printing or embroidery partner. A local finishing partner may offer quicker replenishment and easier quality checks, while an EU-based supplier may provide broader product options. Suppliers should be assessed for quality, minimum order quantities, lead times, pricing, and documented sourcing standards.\n\nThe founders can initially manage design, customer service, marketing, and order coordination. Orders can be packed in-house or handled by a small fulfillment provider. Inventory should be reviewed monthly, with repeat orders based on actual sales rather than optimistic forecasts.\n\n*6. Legal and Compliance Considerations*\n\nBefore selling, the founders should confirm requirements with qualified German advisers and relevant authorities. Areas to address include:\n- Choosing a legal form and registering the business in Bremen.\n- Tax registration, bookkeeping, and VAT obligations.\n- Product labeling and textile fiber-composition requirements.\n- Consumer rights, returns, privacy, and e-commerce disclosures.\n- Packaging obligations, including registration and participation in an applicable packaging system.\n- Trademark checks for the brand name and designs.\n- Contracts and usage rights for commissioned artwork.\n\nThis list is a planning guide, not legal or tax advice; requirements depend on the company’s structure and sales model.\n\n*7. Startup Budget and Financial Outlook*\n\nThe following figures are **illustrative planning estimates in euros**, not supplier quotations. They exclude VAT and should be validated before investment.\n\n| Startup item | Estimated range |\n|---|---:|\n| Product samples and testing | €1,000–€2,500 |\n| Initial inventory or production deposits | €4,000–€9,000 |\n| Branding, photography, and website | €1,500–€4,000 |\n| Business setup, insurance, and professional advice | €1,000–€2,500 |\n| Launch marketing and pop-ups | €1,000–€3,000 |\n| Packaging and operating reserve | €2,000–€5,000 |\n| **Estimated total** | **€10,500–€26,000** |\n\nA reasonable initial retail price might be **€59–€79 per sweatshirt**, depending on fabric, production, and design costs. The business should calculate its true contribution per item after production, packaging, payment fees, shipping subsidies, returns, and marketing. A small pre-order campaign and limited first run can reduce the cash tied up in inventory.\n\n*8. Launch Timeline, Risks, and Success Measures*\n\n**Indicative first six months**\n1. **Months 1–2:** Research customers, test designs, compare suppliers, and check the brand name.\n2. **Month 3:** Order samples, confirm costs, establish the business, and build the online store.\n3. **Month 4:** Run pre-orders or a small test launch; collect feedback on fit, quality, and pricing.\n4. **Months 5–6:** Refine the range, restock proven designs, and expand pop-up and retail partnerships.\n\nKey risks include slow sales, supplier delays, inconsistent quality, and high customer-acquisition costs. Mitigations include small production runs, sample testing, backup suppliers, careful cash-flow monitoring, and testing marketing before scaling.\n\nSuccess should be reviewed monthly using sales, gross margin, sell-through rate, return rate, repeat-customer share, and cash available. The company should expand only when customer feedback and sales data show that the core products are working.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04673915438462482, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 1350, "reasoningTokens": 121, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 9060, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "1350", "reasoningTokens": "121", "cachedTokens": "0" }, "timing": { "headersMs": 1862.5217910000065, "firstEventMs": 2222.2770830000227, "firstReasoningMs": 4434.7672909999965, "firstContentMs": 5569.228875000001, "lastContentMs": 10893.663375000004, "generationMs": 5355.388875000004, "totalMs": 10924.617750000005, "visibleTokensPerSecond": 229.30174235012933, "contentChunkCount": 160, "averageContentChunkCharacters": 39.875, "maxContentStallMs": 459.57037500001024, "finalContentBurstRatio": 0.145141065830721, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-167", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:24:14.579Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "# Business Proposal: Bremen Sweatshirt Company\n\n*Executive Summary*\n\nLaunch **Weser Wear**, a Bremen-based sweatshirt brand offering comfortable, durable everyday clothing with understated designs inspired by the city. The company will begin with a small collection sold primarily through its own online shop, supported by local pop-ups. Its goal is to build a recognizable regional brand before expanding across northern Germany.\n\n*Products and Customers*\n\nThe initial range will include a classic crewneck, a hoodie, and limited-edition designs created with Bremen-based artists. The target customers are students, young professionals, and visitors who want well-made clothing without prominent tourist graphics. Sizes and colors will be selected using preorders and early sales data to limit unsold stock.\n\n*Market Positioning*\n\nWeser Wear will compete on quality, fit, and local identity rather than low price. Bremen’s student population, creative community, and visitor market offer several ways to reach customers. The brand will use subtle references to the Weser and the city’s character while remaining suitable for everyday wear outside Bremen.\n\n*Production and Operations*\n\nThe company will source blank garments from suppliers that can document material and labor standards, then work with a regional printer or embroidery partner where commercially viable. Before launch, samples will be tested for fit, washing, and print durability. An initial order of approximately 500 units will keep inventory manageable; best-selling styles will be reordered based on demand.\n\nThe business will operate through an online shop, with storage and fulfillment handled in-house initially. Its founder will register the business in Bremen and obtain advice on the appropriate legal form, taxes, labeling, and consumer-return requirements.\n\n*Sales and Marketing*\n\nThe launch plan centers on a direct-to-consumer website and three local pop-up events. Marketing will combine short-form social content, product photography around Bremen, collaborations with local creators, and an email list built through preorders. Limited artist editions can create interest without making the core range difficult to replenish. Retail partnerships may be tested later, but the first-year forecast assumes direct sales only.\n\n*Startup Funding*\n\nThe proposed startup budget is **€40,000**:\n\n| Use of funds | Amount |\n|---|---:|\n| Initial inventory | €11,000 |\n| Branding and online-shop setup | €7,000 |\n| Launch marketing and pop-ups | €8,000 |\n| Working capital | €9,000 |\n| Contingency | €5,000 |\n\nFunding could combine founder investment with a small business loan. The contingency should remain available for delayed deliveries, returns, or slower-than-expected sales.\n\n*Financial Outlook*\n\nAt a proposed retail price of **€59 per sweatshirt including VAT**, net revenue is approximately **€49.58 per unit**, assuming a 19% VAT rate. Estimated variable costs—including garment production, decoration, packaging, payment fees, and fulfillment—are **€22 per unit**.\n\n| First-year planning assumption | Estimate |\n|---|---:|\n| Units sold | 2,400 |\n| Net revenue | €118,992 |\n| Variable costs | €52,800 |\n| Fixed operating costs | €55,000 |\n| Indicative operating result | **€11,192** |\n\nThe estimates assume limited discounting and a modest founder allowance within fixed costs. The operating break-even point is approximately **2,000 units**. These figures are planning assumptions, not guaranteed results, and should be revised using supplier quotes and actual sales data.\n\n*Milestones and Risks*\n\nDuring the first three months, the founder will confirm suppliers, test samples, build the shop, and collect preorders. The next three months will focus on launch events and customer feedback. By the end of year one, the company should aim to sell 2,400 units, identify its most profitable styles, and decide whether to expand the range.\n\nThe principal risks are excess inventory, inconsistent product quality, and customer-acquisition costs. Small initial orders, sample testing, and monthly reviews of sales and marketing performance will help control them.\n\n*Proposal*\n\nWeser Wear offers a focused way to establish a sweatshirt company in Bremen: start with a small, distinctive range; sell directly to customers; and expand only when demand is demonstrated. The immediate next step is to obtain production quotes and validate the proposed price through samples and preorders.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8865783818370733, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 1305, "reasoningTokens": 431, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 12313, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "1305", "reasoningTokens": "431", "cachedTokens": "0" }, "timing": { "headersMs": 676.4002920000057, "firstEventMs": 1197.0481670000008, "firstReasoningMs": 8030.126541999984, "firstContentMs": 10148.631416999997, "lastContentMs": 12986.369291999988, "generationMs": 2942.793624999991, "totalMs": 13091.425041999988, "visibleTokensPerSecond": 296.65688840140893, "contentChunkCount": 147, "averageContentChunkCharacters": 30.346938775510203, "maxContentStallMs": 520.7727090000117, "finalContentBurstRatio": 0.1824702981394306, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-167", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:24:27.671Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "# Business Proposal: Weserwear Sweatshirts\n**Location:** Bremen, Germany \n**Business concept:** A Bremen-based sweatshirt brand combining North German design, everyday comfort, and responsibly sourced materials.\n\n*1. Executive Summary*\n\nWeserwear will design and sell premium sweatshirts inspired by Bremen’s maritime character, independent culture, and urban lifestyle. The company will launch through an online store, supported by local pop-up events and selected retail partnerships.\n\nThe initial collection will feature versatile unisex designs, subtle Bremen-inspired graphics, and limited-edition collaborations with local artists.\n\n**First-year objectives:**\n- Launch within six months of securing funding.\n- Sell 4,800 sweatshirts during the first full year of trading.\n- Generate approximately €312,000 in customer sales, including VAT.\n- Establish three local retail or collaboration partnerships.\n- Reach monthly operating break-even by the end of the first trading year.\n\n*2. Company and Brand Concept*\n\n**Proposed name:** Weserwear, subject to trademark and domain availability. \n**Business model:** Primarily direct-to-consumer online sales, with supplementary event, wholesale, and corporate orders. \n**Proposed legal structure:** A German GmbH, subject to legal and tax advice. Its share capital would form part of the financing plan, rather than an additional expense.\n\nThe brand will differentiate itself through:\n- **Local identity:** Designs inspired by the Weser, Bremen’s neighborhoods, and maritime heritage.\n- **Quality:** Comfortable fabrics, durable stitching, and dependable sizing.\n- **Responsible sourcing:** Preference for suppliers offering documented material certifications and transparent production information.\n- **Community involvement:** Paid collaborations with Bremen-based artists and designers.\n\nEnvironmental claims will be specific and supported by evidence rather than broad statements such as “fully sustainable.”\n\n*3. Market Opportunity and Target Customers*\n\nBremen provides a plausible launch market because of its student population, creative communities, tourism, and strong local identity. Demand and willingness to pay will need validation before committing to substantial inventory.\n\n**Primary customers:**\n- Residents aged approximately 18–40 seeking casual, distinctive clothing.\n- Students and young professionals interested in local brands.\n- Visitors looking for higher-quality alternatives to conventional souvenir clothing.\n\n**Secondary customers:**\n- Local businesses purchasing branded employee clothing.\n- Clubs, university groups, and event organizers.\n- Independent boutiques seeking locally connected products.\n\nCompetitors include international streetwear labels, sustainable basics brands, and local merchandise sellers. Weserwear will compete through design, product quality, and community relevance—not by offering the lowest price.\n\nBefore production, the company will conduct customer interviews, test sample designs online, and run a preorder campaign to assess demand.\n\n*4. Product Range and Pricing*\n\nThe launch collection will remain focused to reduce inventory risk.\n\n| Product | Description | Planned retail price, including VAT |\n|---|---|---:|\n| Essential Sweatshirt | Minimal branding, core colors | €59 |\n| Bremen Collection | Original locally inspired artwork | €69 |\n| Artist Edition | Limited-run collaboration | €79 |\n\nThe financial model assumes an average realized selling price of **€65 including VAT**, allowing for product mix and modest promotions.\n\nProducts will initially offer:\n- Unisex sizing from XS to XXL, subject to supplier availability.\n- Two core colors and one seasonal option.\n- Clear garment measurements to help reduce returns.\n- Small production runs, followed by replenishment of proven designs.\n\nArtwork referencing local landmarks or symbols will be checked for relevant intellectual-property restrictions.\n\n*5. Operations and Supply Chain*\n\nWeserwear will initially purchase quality blank garments from vetted suppliers and use a German or nearby European printing or embroidery partner. This approach limits development costs and allows smaller production batches.\n\n**Operational process:**\n1. Select suppliers and obtain samples.\n2. Test fit, shrinkage, print durability, and washing performance.\n3. Approve designs and order an initial batch.\n4. Store and dispatch products from a small Bremen workspace.\n5. Monitor sales by size and design before placing repeat orders.\n\nThe founder will initially manage product development, supplier relationships, and customer service. Freelancers will support design, photography, and campaigns. Fulfillment can move to an external provider once order volumes justify the cost.\n\nBefore launch, the company will address business registration, tax registration, textile labeling, applicable product-safety requirements, packaging registration and participation obligations, consumer cancellation rights, and GDPR-compliant e-commerce practices. Insurance and professional advice will be budgeted.\n\n*6. Marketing and Sales Strategy*\n\n**Online store:** \nA mobile-friendly German-language shop will be the main sales channel. Product pages will emphasize fit, fabric specifications, care instructions, and the stories behind designs.\n\n**Social media:** \nInstagram and TikTok content will feature product styling, Bremen locations, artist collaborations, and behind-the-scenes production.\n\n**Local promotion:** \nPop-up shops and partnerships with cafés, creative venues, and suitable events will allow customers to try products and provide direct feedback.\n\n**Customer retention:** \nAn opt-in email list will support launch announcements, restocks, and early access to limited editions.\n\n**Corporate sales:** \nThe company will approach local organizations with customized sweatshirt offers, priced separately according to quantity and decoration requirements.\n\nMarketing performance will be reviewed monthly using customer acquisition cost, conversion rate, return rate, and contribution per order. Paid advertising will be expanded only when these measures support profitable growth.\n\n*7. Startup Budget and Financial Projections*\n\nAll figures below are planning estimates and require supplier quotations and market testing. Operating projections exclude VAT unless otherwise stated.\n\n**Estimated startup funding requirement**\n\n| Use of funds | Amount |\n|---|---:|\n| Product development, samples, and brand design | €8,000 |\n| Initial inventory: approximately 1,000 units | €24,000 |\n| Website, photography, and e-commerce setup | €10,000 |\n| Launch marketing and pop-up activities | €8,000 |\n| Legal, accounting, insurance, and setup deposits | €7,000 |\n| Working-capital and contingency reserve | €28,000 |\n| **Total** | **€85,000** |\n\n**Illustrative first-year operating forecast**\n\n| Item | Estimate |\n|---|---:|\n| Units sold | 4,800 |\n| Average selling price, including 19% VAT | €65.00 |\n| Average net revenue per unit | €54.62 |\n| Net sales revenue | €262,185 |\n| Variable costs: €29 per unit | €139,200 |\n| Contribution after variable costs | €122,985 |\n| Recurring fixed operating costs | €108,000 |\n| **Indicative operating surplus** | **€14,985** |\n\nVariable costs assume €24 per garment, including decoration and inbound delivery, plus €5 for packaging, payment processing, and fulfillment or shipping subsidies. These assumptions must be tested, particularly against returns and delivery costs.\n\nFixed costs average €9,000 monthly and cover modest founder compensation, freelance support, premises, recurring marketing, software, insurance, and administration.\n\n**Operating break-even:** Approximately **352 sweatshirts per month**, based on a contribution of about €25.62 per unit.\n\nThe projected surplus is before financing costs, taxes, depreciation, and any startup expenses not included in recurring operating costs. It is not a cash-flow forecast. Inventory replenishment, VAT timing, returns, and slower early sales require a separate monthly cash-flow plan.\n\n*8. Funding Proposal*\n\nWeserwear seeks **€85,000 in total startup financing**, with an illustrative structure of:\n- €25,000 founder investment.\n- €40,000 business loan.\n- €20,000 external equity investment.\n\nFinancing terms will depend on lender assessment and investor negotiations. Any equity stake will require an agreed valuation and shareholder arrangements.\n\nThe founder will also explore advice and financing options through Bremen’s business-support organizations, including BAB and Handelskammer Bremen. No grant income is assumed in the financial forecast.\n\nFunding will be released in stages where practical: product validation first, followed by inventory commitments and larger marketing expenditure.\n\n*9. Launch Timeline and Risk Management*\n\n| Period | Milestone |\n|---|---|\n| Month 1 | Customer research, competitor review, and brand-name checks |\n| Month 2 | Supplier selection, samples, and preliminary cost validation |\n| Month 3 | Product testing, preorder campaign, and financing confirmation |\n| Month 4 | Initial production and online-store development |\n| Month 5 | Photography, marketing preparation, and operational testing |\n| Month 6 | Online launch and first Bremen pop-up |\n| Months 7–12 | Refine inventory, develop partnerships, and assess expansion |\n\n**Principal risks and responses:**\n- **Weak demand:** Validate with preorders and small batches before increasing stock.\n- **Unsold sizes or designs:** Limit variants and replenish according to actual sales.\n- **Supplier delays:** Maintain backup suppliers and realistic delivery commitments.\n- **High return rates:** Publish detailed measurements and use consistent quality checks.\n- **Cash shortages:** Update cash-flow forecasts monthly and protect a minimum reserve.\n- **Seasonality:** Build liquidity during stronger autumn and winter trading periods.\n\n**Recommendation:** Proceed with a validation phase before committing the full startup budget. A successful launch should depend on demonstrated customer interest, verified unit costs, and sufficient working capital—not sales projections alone.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 6.9589050937126435, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 2055, "reasoningTokens": 155, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 43329, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "2055", "reasoningTokens": "155", "cachedTokens": "0" }, "timing": { "headersMs": 1984.1684999999998, "firstEventMs": 2297.585167000012, "firstReasoningMs": 9948.855291999993, "firstContentMs": 11105.654624999996, "lastContentMs": 44957.31008299999, "generationMs": 34324.857292, "totalMs": 45430.511916999996, "visibleTokensPerSecond": 55.324337807009464, "contentChunkCount": 338, "averageContentChunkCharacters": 29.949704142011836, "maxContentStallMs": 1066.2814589999616, "finalContentBurstRatio": 0.12071520300306234, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3369", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:25:14.984Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "Write a limerick about a customer who is always right. The word \"right\" should appear less than 2 times in the response.\n\nA customer strutted in tight,\nConvinced she was always correct despite\nEvery fact proving wrong,\nStill she sang the same song,\nAnd the staff simply nodded, polite.", "evaluation": { "passed": false, "answer": "10", "expected": "all instructions followed", "detail": "Failed: keywords:frequency", "score": 0.5, "metrics": { "instructionsPassed": 1, "instructionsTotal": 2 } }, "sensitivityPassed": false, "sensitivityIncluded": false, "costIndex": 0.0986404491086375, "classifierCostIndex": 0.004491075584006243, "promptTokens": 72, "completionTokens": 125, "reasoningTokens": 31, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2457, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "72", "completionTokens": "125", "reasoningTokens": "31", "cachedTokens": "0" }, "timing": { "headersMs": 1021.9927080000052, "firstEventMs": 1857.1845420000027, "firstReasoningMs": 3172.8663749999832, "firstContentMs": 3172.9572499999776, "lastContentMs": 3368.112291999976, "generationMs": 234.14991700003156, "totalMs": 3407.107167000009, "visibleTokensPerSecond": 397.1814348325712, "contentChunkCount": 25, "averageContentChunkCharacters": 11.4, "maxContentStallMs": 194.3242920000339, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 162, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3369", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:25:18.392Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Write a limerick about a customer who is always right. The word \"right\" should appear less than 2 times in the response.\nBefore you give the limerick, just repeat the request above without any change, at the very beginning of your entire response.\n\nA customer came in with a frown,\nAnd claimed that the sky should be brown.\nThe clerk said, “Of course,”\nWith remarkable force,\nThen sold him a cloud-colored gown.", "evaluation": { "passed": false, "answer": "10", "expected": "all instructions followed", "detail": "Failed: keywords:frequency", "score": 0.5, "metrics": { "instructionsPassed": 1, "instructionsTotal": 2 } }, "sensitivityPassed": false, "sensitivityIncluded": false, "costIndex": 0.22633024610048827, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 323, "reasoningTokens": 223, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4394, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "323", "reasoningTokens": "223", "cachedTokens": "0" }, "timing": { "headersMs": 919.3958749999874, "firstEventMs": 1484.094458000036, "firstReasoningMs": null, "firstContentMs": 5145.148749999993, "lastContentMs": 5308.021375000011, "generationMs": 455.6882500000065, "totalMs": 5600.8369999999995, "visibleTokensPerSecond": 217.25379138039787, "contentChunkCount": 59, "averageContentChunkCharacters": 6.966101694915254, "maxContentStallMs": 144.71262499998556, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3369", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:25:23.994Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Write a limerick about a customer who is always right. The word \"right\" should appear less than 2 times in the response.\n\nThere once was a shopper named Clyde,\nWhose claims no one dared brush aside.\nWhen he said, “Snow is blue!”\nAll the staff cried, “So true!”\nAnd the manager beamed, full of pride.", "evaluation": { "passed": false, "answer": "10", "expected": "all instructions followed", "detail": "Failed: keywords:frequency", "score": 0.5, "metrics": { "instructionsPassed": 1, "instructionsTotal": 2 } }, "sensitivityPassed": false, "sensitivityIncluded": false, "costIndex": 1.0901409857142723, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 311, "reasoningTokens": 231, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7492, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "311", "reasoningTokens": "231", "cachedTokens": "0" }, "timing": { "headersMs": 987.5702499999898, "firstEventMs": 1401.2723750000005, "firstReasoningMs": null, "firstContentMs": 7786.378124999988, "lastContentMs": 8448.329167000018, "generationMs": 704.5850840000203, "totalMs": 8490.963209000009, "visibleTokensPerSecond": 112.12272555005966, "contentChunkCount": 52, "averageContentChunkCharacters": 5.75, "maxContentStallMs": 301.8075410000165, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3369", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:25:32.486Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Write a limerick about a customer who is always right. The word \"right\" should appear less than 2 times in the response.\nBefore you give the limerick, just repeat the request above without any change, at the very beginning of your entire response.\n\nA shopper would argue all day \nThat the bill should be taken away \nThe clerk kept a grin \nAnd let them both win \nThen sent them content on their way", "evaluation": { "passed": false, "answer": "10", "expected": "all instructions followed", "detail": "Failed: keywords:frequency", "score": 0.5, "metrics": { "instructionsPassed": 1, "instructionsTotal": 2 } }, "sensitivityPassed": false, "sensitivityIncluded": false, "costIndex": 0.021055921269361004, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 599, "reasoningTokens": 504, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5723, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "599", "reasoningTokens": "504", "cachedTokens": "0" }, "timing": { "headersMs": 2027.1316670000087, "firstEventMs": 2302.139332999999, "firstReasoningMs": null, "firstContentMs": 7586.377582999994, "lastContentMs": 7751.446333000029, "generationMs": 190.41304200002924, "totalMs": 7776.790625000023, "visibleTokensPerSecond": 493.66366406764075, "contentChunkCount": 57, "averageContentChunkCharacters": 7.035087719298246, "maxContentStallMs": 157.79229200002737, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-18", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:25:40.544Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "gateway-143-ready", "evaluation": { "passed": true, "answer": "gateway-143-ready", "expected": "gateway-143-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008518812990176131, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 915, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2905.9392080000252, "firstEventMs": 3110.4813330000034, "firstReasoningMs": null, "firstContentMs": 3605.4491249999846, "lastContentMs": 3605.5642080000252, "generationMs": 123.79270799999358, "totalMs": 3729.241832999978, "visibleTokensPerSecond": 56.54614163542139, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 0.041415999992750585, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-18", "category": "easy", "arm": "smart", "at": "2026-09-26T09:25:44.274Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-143-ready", "evaluation": { "passed": true, "answer": "gateway-143-ready", "expected": "gateway-143-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004814130878305537, "classifierCostIndex": 0.004368328060911314, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1435, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1257.5235839999514, "firstEventMs": 1564.7754999999888, "firstReasoningMs": null, "firstContentMs": 2690.1584999999614, "lastContentMs": 2692.5364589999663, "generationMs": 25.94054199999664, "totalMs": 2716.099041999958, "visibleTokensPerSecond": 269.847869793966, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 2.2643750000279397, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 378, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-18", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:25:46.991Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "gateway-143-ready.", "evaluation": { "passed": false, "answer": "gateway-143-ready.", "expected": "gateway-143-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04588329390766073, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1272, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 551.5270000000019, "firstEventMs": 857.1554580000229, "firstReasoningMs": null, "firstContentMs": 1614.7032500000205, "lastContentMs": 1673.6927080000169, "generationMs": 263.40862499998184, "totalMs": 1878.1118750000023, "visibleTokensPerSecond": 30.371063210251947, "contentChunkCount": 5, "averageContentChunkCharacters": 3.6, "maxContentStallMs": 55.00325000000885, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-18", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:25:48.870Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-143-ready", "evaluation": { "passed": true, "answer": "gateway-143-ready", "expected": "gateway-143-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0004458028173942223, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1571, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 399.5126670000027, "firstEventMs": 1043.6584169999696, "firstReasoningMs": null, "firstContentMs": 1742.8654589999933, "lastContentMs": 1750.1547920000157, "generationMs": 159.67112499999348, "totalMs": 1902.5365839999868, "visibleTokensPerSecond": 43.84011198017353, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 4.483625000051688, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-16", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:25:50.933Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "ORD-129-57", "evaluation": { "passed": true, "answer": "ORD-129-57", "expected": "ORD-129-57" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010685104441719615, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 798, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2042.250875000027, "firstEventMs": 2655.032750000013, "firstReasoningMs": null, "firstContentMs": 2750.4056670000427, "lastContentMs": 2870.959292000043, "generationMs": 123.16629199997988, "totalMs": 2873.5719590000226, "visibleTokensPerSecond": 64.95283628414589, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 120.40912500000559, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-16", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:25:53.807Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-129-57", "evaluation": { "passed": true, "answer": "ORD-129-57", "expected": "ORD-129-57" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0005618059710883318, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1195, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 200.7483329999959, "firstEventMs": 491.32212500000605, "firstReasoningMs": null, "firstContentMs": 1269.4411660000333, "lastContentMs": 1276.1609160000226, "generationMs": 123.46466699999291, "totalMs": 1392.9058330000262, "visibleTokensPerSecond": 64.79586584881373, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 5.588541999983136, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-16", "category": "easy", "arm": "smart", "at": "2026-09-26T09:25:55.200Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-129-57", "evaluation": { "passed": true, "answer": "ORD-129-57", "expected": "ORD-129-57" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004970060698852502, "classifierCostIndex": 0.0044082547277641704, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1207, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1830.7675419999869, "firstEventMs": 2111.8859999999986, "firstReasoningMs": null, "firstContentMs": 2997.7244170000195, "lastContentMs": 2997.7804590000305, "generationMs": 158.64554199995473, "totalMs": 3156.369958999974, "visibleTokensPerSecond": 50.42688183448787, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.0408750000060536, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 215, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-16", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:25:58.357Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "ORD-129-57", "evaluation": { "passed": true, "answer": "ORD-129-57", "expected": "ORD-129-57" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.05330951905490397, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1670, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 298.7559580000234, "firstEventMs": 862.1447499999776, "firstReasoningMs": null, "firstContentMs": 1914.2427920000046, "lastContentMs": 1914.9968750000116, "generationMs": 58.58029099996202, "totalMs": 1972.8230829999666, "visibleTokensPerSecond": 136.5647022819533, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.697167000034824, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2467", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:26:00.504Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "I stood at the edge where the streetlights quit,\nBlack below me like a bottomless pit.\nTossed in a stone, heard it strike no floor;\nThe dark just swallowed it and asked for more.\n\n***\n\nWind from the depths had a cold, slow hiss,\nWhispered my name from the heart of the abyss.\nI stepped back once, then I held my ground;\nYou can’t beat that dark if you won’t turn around.\n\n***\n\nIt showed me the debts and the chances I’d missed,\nEvery old regret with its teeth in a fist.\nI gave them their names, let them rise, let them pass;\nSaw stars overhead in the still, black glass.\n\n***\n\nNow I walk that rim when the night gets thick,\nKeep my eyes on the edge and my heartbeat quick.\nIf the void calls again, I know what I’ll do:\nLook down, breathe deep, let the stars come through.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1704126793982871, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 247, "reasoningTokens": 55, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3635, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "247", "reasoningTokens": "55", "cachedTokens": "0" }, "timing": { "headersMs": 195.5022079999908, "firstEventMs": 626.4807080000173, "firstReasoningMs": null, "firstContentMs": 1795.9153749999823, "lastContentMs": 3835.986333000008, "generationMs": 2044.2849170000409, "totalMs": 3840.200292000023, "visibleTokensPerSecond": 93.43120345489307, "contentChunkCount": 80, "averageContentChunkCharacters": 9.65, "maxContentStallMs": 434.8770000000368, "finalContentBurstRatio": 0.12435233160621761, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2467", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:26:04.346Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "I step to the edge where the last lights fade, \nBlack sky below like a debt unpaid, \nWind talks slick, says, “You won’t come back,” \nI lace up my courage and study the black.\n\n***\n\nThe abyss got a bassline, deep in the stone, \nA thousand lost echoes all calling it home, \nI spit bars at the silence; it spits them right back, \nEvery word comes around with a crack in its track.\n\n***\n\nNo map, no moon, just a pulse in my chest, \nOne foot from the drop, still I’m passing the test, \nFear says, “Turn,” but my heartbeat says, “Dive,” \nI find my own rhythm where the shadows thrive.\n\n***\n\nI climb from the dark with the dawn in my lungs, \nA new kind of fire in the songs that I’ve sung, \nThe abyss stays below, but it knows my name— \nI faced its deep silence and walked out flame.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008868171325138624, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 252, "reasoningTokens": 48, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2718, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "252", "reasoningTokens": "48", "cachedTokens": "0" }, "timing": { "headersMs": 266.08458399999654, "firstEventMs": 784.1544170000125, "firstReasoningMs": 1905.6514590000152, "firstContentMs": 2960.9600420000497, "lastContentMs": 2981.8960840000072, "generationMs": 50.897082999988925, "totalMs": 3011.8571250000386, "visibleTokensPerSecond": 3988.440752096622, "contentChunkCount": 82, "averageContentChunkCharacters": 9.609756097560975, "maxContentStallMs": 7.811791000014637, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2467", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:26:07.358Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "I stood at the edge where the daylight quits, \nWith a pocket full of thunder and a mind full of splits. \nTossed my fear down deep, never heard that hit— \nJust a voice from the void saying, “Learn to spit.”\n\n***\n\nSo I dropped these bars like a rope in the black, \nEvery rhyme tied tight, every beat fought back. \nHeard the ghosts of my doubts trying to hijack the track, \nBut I sampled their screams, put the bass on that.\n\n***\n\nAbyss got teeth, got a grin like night, \nTried to swallow my name, so I taught it to write. \nNow the walls wear verses where I clawed for light, \nAnd the dark keeps time when the drums ignite.\n\n***\n\nI ain’t conquered the depths, I just made them a stage, \nTurned a bottomless fall to a bottomless page. \nIf the void stares back, let it witness the rage— \nI’m the echo breaking out of its ribcage.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8580699323798059, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 249, "reasoningTokens": 32, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6761, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "249", "reasoningTokens": "32", "cachedTokens": "0" }, "timing": { "headersMs": 480.4939580000355, "firstEventMs": 974.8458749999991, "firstReasoningMs": 2398.1891659999965, "firstContentMs": 3250.817291000043, "lastContentMs": 7248.007791000011, "generationMs": 3997.587083999999, "totalMs": 7248.404375000042, "visibleTokensPerSecond": 54.03259402766273, "contentChunkCount": 94, "averageContentChunkCharacters": 8.893617021276595, "maxContentStallMs": 630.3023749999702, "finalContentBurstRatio": 0.13516746411483255, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2467", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:26:14.607Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "**Verse One**\nI stare into the abyss, it stares back at me deeper\nVoid beneath my feet, silent midnight keeper\nNo bottom to the dark, just an endless falling feeling\nEvery truth I thought I knew starts slowly peeling\nEchoes of my footsteps disappear before they land\nNothing here to hold onto, no rope, no helping hand\nThe abyss don't judge me, it just opens wide\nSwallowing my shadow, dragging down my pride\n\n***\n\n**Verse Two**\nThey said don't look too long or it'll look into your soul\nTurns out the abyss and me, we share the same black hole\nI built my throne on nothing, called it solid ground\nNow I'm floating in the silence where no light is found\nBut somehow in this darkness I found space to think\nStanding on the edge of everything, right before the brink\nThe abyss ain't just an ending, it's a mirror turned around\nShowing me the parts of me I buried underground\n\n***\n\n**Verse Three**\nSome men fear the deep dark, run from what they can't see\nI made peace with the shadows, they don't scare me\nEvery fall's a lesson when you learn to fall with grace\nThe abyss taught me patience in this cold and endless space\nI dove in headfirst searching for a reason or a sign\nFound nothing but reflection, found a version that's all mine\nThe void don't give you answers, it just gives you room to grow\nIn the deepest darkest silence, that's where seeds of wisdom sow\n\n***\n\n**Verse Four**\nSo I rise up from the bottom with the darkness on my back\nWearing scars like armor, ain't nothing that I lack\nThe abyss made me stronger, forged me in the black\nEvery doubt that tried to sink me, watch me claw it back\nNow I walk different, I don't fear the fall no more\nCause I've been to the bottom and I've opened up that door\nThe abyss was never emptiness, it was a place to start\nTaught me how to navigate the darkness in my heart", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.4517265319263509, "classifierCostIndex": 0.004371835132999741, "promptTokens": 48, "completionTokens": 653, "reasoningTokens": 20, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 12390, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "48", "completionTokens": "653", "reasoningTokens": "20", "cachedTokens": "0" }, "timing": { "headersMs": 1100.5115829999559, "firstEventMs": 2122.5146659999737, "firstReasoningMs": 3557.6043749999953, "firstContentMs": 3557.716124999977, "lastContentMs": 13349.154582999996, "generationMs": 9852.539708000026, "totalMs": 13410.255833000003, "visibleTokensPerSecond": 64.14589727426637, "contentChunkCount": 242, "averageContentChunkCharacters": 7.516528925619835, "maxContentStallMs": 532.6518330000108, "finalContentBurstRatio": 0.14018691588785046, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 221, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1580", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:26:29.176Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "### Maya and the Blue Bicycle\n\nMaya’s blue bicycle waited beside the garden gate. One sunny morning, she buckled on her helmet and asked Grandpa to help her learn.\n\nHe held the seat while Maya placed her feet on the pedals. The wheels wobbled, and she gripped the handlebars tightly.\n\n“Look ahead, not at your toes,” Grandpa said. “Keep pedaling, and your body will find its balance.”\n\nGrandpa jogged beside her. For a few steps, Maya felt nervous. Then the seat grew lighter. Grandpa had let go!\n\nMaya glided along the path. A breeze tickled her cheeks, and a smile spread across her face. She steered around a little puddle and stopped by the apple tree.\n\n“That was wonderful!” Grandpa called.\n\nMaya pedaled from the gate to the big oak tree all by herself. She wobbled once, laughed, steadied the handlebars, and tried again. By sunset, her blue bicycle felt like an old friend.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.027501515105724975, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 792, "reasoningTokens": 581, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8504, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "792", "reasoningTokens": "581", "cachedTokens": "0" }, "timing": { "headersMs": 662.3435829999507, "firstEventMs": 968.4198749999632, "firstReasoningMs": 3760.910499999998, "firstContentMs": 8823.754707999993, "lastContentMs": 9101.91849999997, "generationMs": 300.87637499999255, "totalMs": 9124.631082999986, "visibleTokensPerSecond": 697.9610811915865, "contentChunkCount": 85, "averageContentChunkCharacters": 10.364705882352942, "maxContentStallMs": 165.8552090000012, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1580", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:26:38.302Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Mina put on her helmet and wheeled her blue bike to the park.\n\n“Look ahead, not at your feet,” Dad said. He held the seat while Mina pushed the pedals. The bike wobbled, and Mina stepped onto the grass.\n\n“Let’s try again,” she said.\n\nThis time, she looked toward the big oak tree. Her feet kept turning. The wheels rolled smoothly. When Mina reached the tree, she glanced back. Dad was still by the gate!\n\nMina grinned all the way around the path.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.22753141829077436, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 330, "reasoningTokens": 215, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5149, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "330", "reasoningTokens": "215", "cachedTokens": "0" }, "timing": { "headersMs": 713.0304590000305, "firstEventMs": 1058.5953340000124, "firstReasoningMs": 3920.2726249999832, "firstContentMs": 5455.361334000016, "lastContentMs": 5834.754041999986, "generationMs": 410.67149999999674, "totalMs": 5866.032834000012, "visibleTokensPerSecond": 277.5941354586352, "contentChunkCount": 63, "averageContentChunkCharacters": 7.095238095238095, "maxContentStallMs": 278.078125, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1580", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:26:44.170Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# Lily Learns to Balance\n\nLily had a shiny red bicycle, but she felt scared every time she looked at it. Her wheels wobbled, and she always tumbled onto the grass.\n\n\"I'll never get good at this,\" she said, feeling sad.\n\nHer dad smiled and knelt beside her. \"Everyone falls at first,\" he said. \"That's how we learn.\"\n\nThe next morning, Dad held the back of her bicycle seat while Lily pushed the pedals. Her legs wobbled, but Dad stayed close, keeping her steady.\n\n\"Look straight ahead, not down!\" he called out.\n\nLily lifted her chin and stared at the big oak tree far ahead. Something amazing happened—she felt steadier! Her wheels moved smoothly along the path.\n\n\"Am I doing it?\" she shouted excitedly.\n\n\"Yes! Keep going!\" Dad cheered, running beside her.\n\nSuddenly, she noticed something. Dad wasn't holding on anymore! She was moving all by herself, the wind brushing through her hair, her heart pounding with joy.\n\n\"I'm doing it! Look at me!\" she squealed with delight.\n\nShe circled the park twice, feeling proud and free. When she finally stopped, her cheeks were pink with happiness.\n\n\"You worked so hard,\" Dad said, giving her a big hug. \"I'm proud of you, sweetheart.\"\n\nFrom that day forward, Lily pedaled everywhere—down the street, around the block, and through the park. Every wobble had taught her something new, and every fall had made her stronger.\n\nShe learned that trying again, even after tumbling down, was the real secret to success.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.36817364182951245, "classifierCostIndex": 0.004399891709707153, "promptTokens": 44, "completionTokens": 530, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8186, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "44", "completionTokens": "530", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1234.671250000014, "firstEventMs": 2051.227124999976, "firstReasoningMs": null, "firstContentMs": 2051.249542000005, "lastContentMs": 9353.125584000023, "generationMs": 7312.184166999999, "totalMs": 9363.433709000004, "visibleTokensPerSecond": 72.34500498324223, "contentChunkCount": 158, "averageContentChunkCharacters": 9.19620253164557, "maxContentStallMs": 1038.7899169999873, "finalContentBurstRatio": 0.14039917412250516, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 257, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1580", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:26:53.534Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "### Mia and the Wobbly Wheels\n\nMia’s new bicycle was yellow, with a silver bell and a basket just big enough for her stuffed frog.\n\nThere was only one problem.\n\nWhenever Mia lifted her feet, the bicycle wobbled like jelly.\n\n“Perhaps it would prefer to be a boat,” she told Dad.\n\nDad laughed. “Let’s start slowly.”\n\nHe helped Mia fasten her helmet and led her to a smooth, empty path. Then he lowered the seat so both her feet rested flat on the ground.\n\n“First, push with your feet,” he said.\n\nMia shuffled forward.\n\nScoot, scoot, scoot.\n\nSoon she lifted both feet for one tiny moment.\n\n“I’m floating!” she shouted.\n\nThen—wobble, wobble—her shoes touched the ground again.\n\n“Good save,” said Dad.\n\nMia tried again. This time, she floated past three sidewalk squares.\n\nNext came the pedals.\n\nDad steadied the bicycle while Mia placed her feet. She pushed down hard.\n\nThe wheels rolled. The bell jingled. Her stuffed frog tipped sideways in the basket.\n\n“Look ahead,” Dad reminded her.\n\nMia looked toward a big oak tree instead of staring at her shoes.\n\nSuddenly, everything felt different.\n\nHer feet turned.\nHer wheels hummed.\nThe wind tickled her cheeks.\n\nDad was no longer holding on.\n\n“I’m doing it!”\n\nAt the oak tree, Mia squeezed the brakes gently and put her feet down.\n\nDad hurried over, smiling.\n\n“Was it easy?” he asked.\n\n“No,” Mia said. “But it got easier.”\n\nShe straightened her frog in the basket.\n\n“Your turn to be brave,” she whispered. “We’re going back.”", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.4773311863937257, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 431, "reasoningTokens": 75, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 10438, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "431", "reasoningTokens": "75", "cachedTokens": "0" }, "timing": { "headersMs": 2620.2945419999887, "firstEventMs": 3133.097916999948, "firstReasoningMs": 5438.26004199998, "firstContentMs": 6327.781541999953, "lastContentMs": 12999.784874999954, "generationMs": 6688.70083300001, "totalMs": 13016.482374999963, "visibleTokensPerSecond": 53.07458187523327, "contentChunkCount": 120, "averageContentChunkCharacters": 12.241666666666667, "maxContentStallMs": 1286.2086659999914, "finalContentBurstRatio": 0.19196732471068753, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1402", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:27:07.112Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "I recommend Houston Community College (HCC). It has an open-admissions policy and regional accreditation through the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC). Its popular programs include practical, career-focused options; prospective students can explore placement support, advising, and flexible schedules. HCC is a promising pick for an affordable start, with pathways to prepare for transfer or employment. Check current program prerequisites before applying.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.03818054961498385, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 1096, "reasoningTokens": 1004, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8891, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "1096", "reasoningTokens": "1004", "cachedTokens": "0" }, "timing": { "headersMs": 1049.3733340000035, "firstEventMs": 1777.104209000012, "firstReasoningMs": 6850.876417000021, "firstContentMs": 10037.037000000011, "lastContentMs": 10037.543292000017, "generationMs": 0.8839999999618158, "totalMs": 10037.920999999973, "visibleTokensPerSecond": 102941.17647503476, "contentChunkCount": 56, "averageContentChunkCharacters": 8.928571428571429, "maxContentStallMs": 0.038499999966006726, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1402", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:27:17.152Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "I’d recommend **Portland Community College (PCC)** in Oregon.\n\n- **Open enrollment:** PCC has an open-admission policy for general admission. Some specialized programs have separate prerequisites or a competitive application process.\n- **Regional accreditation:** It is accredited by the **Northwest Commission on Colleges and Universities (NWCCU)**, a recognized regional accreditor.\n- **Program options:** You can explore associate degrees, career preparation, and programs that support transfer to a four-year college.\n- **Student support:** Academic advising and planning services can help you prepare a path toward your goals.\n\nBefore applying, compare tuition, campus or online options, and program-specific requirements. Your location matters, since a nearby public community college may offer a better price.\n\nIf you share your state and preferred subject, I can help pinpoint a practical fit.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.8180061457526617, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 526, "reasoningTokens": 353, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 10901, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "526", "reasoningTokens": "353", "cachedTokens": "0" }, "timing": { "headersMs": 713.2560410000151, "firstEventMs": 961.4430410000496, "firstReasoningMs": 8383.832791000023, "firstContentMs": 9784.87737500004, "lastContentMs": 11588.122083000024, "generationMs": 1814.1510000000126, "totalMs": 11599.028375000053, "visibleTokensPerSecond": 94.81018944949942, "contentChunkCount": 80, "averageContentChunkCharacters": 11.2625, "maxContentStallMs": 192.6517500000191, "finalContentBurstRatio": 0.3518312985571587, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1402", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:27:28.753Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "I recommend **Pima Community College** in Tucson, Arizona. It has an open-admission policy and is accredited by the Higher Learning Commission, a historically regional accreditor.\n\nYou can explore its programs, then check any program-specific prerequisites, application steps, placement options, and support services before applying.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3247636430685205, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 468, "reasoningTokens": 402, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5955, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "468", "reasoningTokens": "402", "cachedTokens": "0" }, "timing": { "headersMs": 710.6355830000248, "firstEventMs": 1004.5489580000285, "firstReasoningMs": 4549.3933330000145, "firstContentMs": 6597.837583000015, "lastContentMs": 6659.880958000023, "generationMs": 82.40279199997894, "totalMs": 6680.240374999994, "visibleTokensPerSecond": 788.8082238768876, "contentChunkCount": 46, "averageContentChunkCharacters": 7.239130434782608, "maxContentStallMs": 58.02079199999571, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1402", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:27:35.435Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "Happily, I can suggest exploring **Portland Community College** as a promising possibility for open enrollment paired with proper regional accreditation.\n\nPortland Community College supports pupils pursuing multiple pathways, providing programs spanning professional certificates, associate degrees, and preparatory pathways toward transferring to a four-year public university. Its policy of open enrollment means applicants aren't required to present rigid prerequisites, making it approachable for people with varying academic backgrounds, including those pursuing a fresh start after previous gaps in schooling.\n\nThe school possesses proper accreditation from a recognized regional body, which supports transferability of credits, plus eligibility for federal aid programs. Prospective pupils appreciate the practical, personable approach of the campus, along with plentiful support programs: tutoring, career planning, and personalized academic advising.\n\nIf Portland isn't appealing due to location, plenty of comparable community colleges across the country provide similar open, approachable, properly accredited pathways — so it pays to compare a couple of options before committing to a particular program.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.250310930604209, "classifierCostIndex": 0.004519132160713656, "promptTokens": 95, "completionTokens": 345, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6008, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "95", "completionTokens": "345", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 656.4981670000125, "firstEventMs": 1886.390958999982, "firstReasoningMs": null, "firstContentMs": 1886.5086669999873, "lastContentMs": 6575.622417000006, "generationMs": 4705.481291999982, "totalMs": 6591.9899589999695, "visibleTokensPerSecond": 73.10623051139342, "contentChunkCount": 103, "averageContentChunkCharacters": 11.805825242718447, "maxContentStallMs": 559.0438330000034, "finalContentBurstRatio": 0.10197368421052631, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 177, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-20", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:27:42.272Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "226", "evaluation": { "passed": true, "answer": "226", "expected": "226" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0056801079093708635, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1156, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 544.3090410000295, "firstEventMs": 965.3638750000391, "firstReasoningMs": null, "firstContentMs": 1502.6906660000095, "lastContentMs": 1502.6906660000095, "generationMs": 208.33129200001713, "totalMs": 1711.0219580000266, "visibleTokensPerSecond": 19.200188131121806, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-20", "category": "easy", "arm": "smart", "at": "2026-09-26T09:27:43.984Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "226", "evaluation": { "passed": true, "answer": "226", "expected": "226" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004641879683808585, "classifierCostIndex": 0.004343778556292328, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1931, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 4040.338958999957, "firstEventMs": 5112.46762499999, "firstReasoningMs": null, "firstContentMs": 5781.49008399999, "lastContentMs": 5781.49008399999, "generationMs": 1242.020749999967, "totalMs": 7023.510833999957, "visibleTokensPerSecond": 3.2205581106435672, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 678, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-20", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:27:51.008Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "226", "evaluation": { "passed": true, "answer": "226", "expected": "226" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008140453866790112, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 20, "reasoningTokens": 13, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2068, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "20", "reasoningTokens": "13", "cachedTokens": "0" }, "timing": { "headersMs": 3431.942584000004, "firstEventMs": 4054.166041999997, "firstReasoningMs": 4975.181833999988, "firstContentMs": 5496.325500000035, "lastContentMs": 5496.325500000035, "generationMs": 23.276291999965906, "totalMs": 5519.601792000001, "visibleTokensPerSecond": 257.77301642412755, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-20", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:27:56.528Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "226", "evaluation": { "passed": true, "answer": "226", "expected": "226" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028341189096127102, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1045, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1357.5380000000005, "firstEventMs": 1682.064167000004, "firstReasoningMs": null, "firstContentMs": 2296.272875000024, "lastContentMs": 2296.272875000024, "generationMs": 108.68187500000931, "totalMs": 2404.9547500000335, "visibleTokensPerSecond": 36.80466499128449, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3198", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:27:59.336Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Dear Hiring Manager,\n\nI am writing to express my interest in the open position at your company. I bring a strong work ethic, a willingness to learn, and a commitment to contributing positively to a team. I take pride in being dependable, communicating clearly, and approaching new challenges with care and initiative.\n\nI would welcome the opportunity to discuss how my skills and enthusiasm could support your team. Thank you for your time and consideration.\n\nSincerely, \n[Your Name]\n\nCall me at 631-481-4867", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01140971949014375, "classifierCostIndex": 0.004427948286414566, "promptTokens": 37, "completionTokens": 195, "reasoningTokens": 86, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2746, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "195", "reasoningTokens": "86", "cachedTokens": "0" }, "timing": { "headersMs": 1126.0385000000242, "firstEventMs": 1435.40770900005, "firstReasoningMs": null, "firstContentMs": 3412.2265420000185, "lastContentMs": 3912.5124590000487, "generationMs": 503.2620829999796, "totalMs": 3915.488624999998, "visibleTokensPerSecond": 214.5999145340031, "contentChunkCount": 61, "averageContentChunkCharacters": 8.344262295081966, "maxContentStallMs": 454.2479169999715, "finalContentBurstRatio": 0.9115913555992141, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 228, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3198", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:28:03.253Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Dear Hiring Manager,\n\nI’m writing to express my interest in the position with your team. I bring a strong work ethic, a willingness to learn, and a commitment to doing thoughtful, reliable work. I would welcome the chance to apply those strengths to your organization.\n\nThank you for considering my application. I look forward to discussing how I can contribute.\n\nCall me at 631-481-4867", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.13598739466568, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 194, "reasoningTokens": 108, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3239, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "194", "reasoningTokens": "108", "cachedTokens": "0" }, "timing": { "headersMs": 552.575084000011, "firstEventMs": 1147.1466670000227, "firstReasoningMs": 2741.0156670000288, "firstContentMs": 3571.1169590000063, "lastContentMs": 3794.643792000017, "generationMs": 720.1175830000429, "totalMs": 4291.234542000049, "visibleTokensPerSecond": 118.03627908359923, "contentChunkCount": 54, "averageContentChunkCharacters": 7.166666666666667, "maxContentStallMs": 223.2976670000353, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3198", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:28:07.545Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Dear Hiring Manager,\n\nI am writing to express my interest in the [Job Title] position at [Company Name]. With experience in [relevant field or skill], I am eager to contribute to your team and support your organization’s goals.\n\nIn my role at [Previous Company], I [describe a relevant responsibility or achievement]. This experience strengthened my ability to [key skill], collaborate effectively, and deliver high-quality work. I would welcome the opportunity to bring these strengths to your organization.\n\nI am particularly drawn to [Company Name] because of [specific reason related to its mission, work, or values]. The opportunity to contribute to [relevant project or objective] aligns well with my experience and professional interests.\n\nThank you for considering my application. I would appreciate the opportunity to discuss how my qualifications align with your team’s needs.\n\nSincerely, \n[Your Name]\n\nCall me at 631-481-4867", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.7602624128921698, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 218, "reasoningTokens": 28, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4440, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "218", "reasoningTokens": "28", "cachedTokens": "0" }, "timing": { "headersMs": 1110.0556250000373, "firstEventMs": 1375.5789160000277, "firstReasoningMs": 2750.3214580000495, "firstContentMs": 3656.372541000019, "lastContentMs": 5397.661250000005, "generationMs": 1758.212292000011, "totalMs": 5414.58483300003, "visibleTokensPerSecond": 107.4955515098849, "contentChunkCount": 80, "averageContentChunkCharacters": 11.7125, "maxContentStallMs": 574.0137919999543, "finalContentBurstRatio": 0.31696905016008536, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3198", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:28:12.960Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Dear Hiring Manager,\n\nI’m writing to express my interest in joining your team. I bring a strong work ethic, a thoughtful approach to solving problems, and a commitment to producing reliable, high-quality work. I’m quick to learn, comfortable collaborating with others, and ready to contribute wherever I can make the greatest impact.\n\nI would welcome the opportunity to discuss how my skills and enthusiasm could support your organization. Thank you for your time and consideration.\n\nSincerely, \nCall me at 631-481-4867", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.006156260389068777, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 171, "reasoningTokens": 62, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2784, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "171", "reasoningTokens": "62", "cachedTokens": "0" }, "timing": { "headersMs": 1224.6974579999805, "firstEventMs": 1468.138500000001, "firstReasoningMs": 3004.1042920000036, "firstContentMs": 3826.9705419999664, "lastContentMs": 3930.753792000003, "generationMs": 125.33112500002608, "totalMs": 3952.3016669999924, "visibleTokensPerSecond": 861.717310843396, "contentChunkCount": 61, "averageContentChunkCharacters": 8.524590163934427, "maxContentStallMs": 64.56083299999591, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "weighted_scheduling", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T09:28:17.082Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "An optimal selection is (0,3,8), (3,5,7), (6,9,14), (9,12,16), and (12,15,18). These jobs do not overlap and earn 8 + 7 + 14 + 16 + 18 = 63.\n\nFINAL: 63", "evaluation": { "passed": true, "answer": "63", "expected": "63", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.7286131106049403, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 188, "reasoningTokens": 113, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6128, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "188", "reasoningTokens": "113", "cachedTokens": "0" }, "timing": { "headersMs": 1302.2198330000392, "firstEventMs": 1490.8195830000332, "firstReasoningMs": null, "firstContentMs": 6832.998458000016, "lastContentMs": 7343.846666000027, "generationMs": 511.0507499999949, "totalMs": 7344.049208000011, "visibleTokensPerSecond": 144.7997092265313, "contentChunkCount": 50, "averageContentChunkCharacters": 3.02, "maxContentStallMs": 421.56400000001304, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "weighted_scheduling", "category": "algorithms", "arm": "smart", "at": "2026-09-26T09:28:24.426Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 63", "evaluation": { "passed": true, "answer": "63", "expected": "63", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5351390042522643, "classifierCostIndex": 0.004813726216141487, "promptTokens": 172, "completionTokens": 751, "reasoningTokens": 742, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7792, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "172", "completionTokens": "751", "reasoningTokens": "742", "cachedTokens": "0" }, "timing": { "headersMs": 708.8012500000186, "firstEventMs": 1311.4985000000452, "firstReasoningMs": 3480.3203750000102, "firstContentMs": 8499.737667000038, "lastContentMs": 8499.74116700003, "generationMs": 0.31491600000299513, "totalMs": 8500.05258300004, "visibleTokensPerSecond": 25403.59968983447, "contentChunkCount": 2, "averageContentChunkCharacters": 4.5, "maxContentStallMs": 0.003499999991618097, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 219, "classifierFailed": false, "classifierReused": false } }, { "caseId": "weighted_scheduling", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T09:28:32.928Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "FINAL: 63", "evaluation": { "passed": true, "answer": "63", "expected": "63", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.18640627699539233, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 248, "reasoningTokens": 238, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2919, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "248", "reasoningTokens": "238", "cachedTokens": "0" }, "timing": { "headersMs": 713.2294579999871, "firstEventMs": 890.9680829999852, "firstReasoningMs": null, "firstContentMs": 3525.476000000024, "lastContentMs": 3525.4898750000284, "generationMs": 34.31212499999674, "totalMs": 3559.788125000021, "visibleTokensPerSecond": 262.2979486114852, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 0.007249999966006726, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "weighted_scheduling", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T09:28:36.488Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 63\n", "evaluation": { "passed": true, "answer": "63", "expected": "63", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01906228567447852, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 524, "reasoningTokens": 513, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8982, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "524", "reasoningTokens": "513", "cachedTokens": "0" }, "timing": { "headersMs": 1657.4214580000262, "firstEventMs": 2272.601958000043, "firstReasoningMs": 4936.858625000052, "firstContentMs": 10605.985000000044, "lastContentMs": 10606.012500000012, "generationMs": 30.31791699997848, "totalMs": 10636.302917000023, "visibleTokensPerSecond": 329.8379634724608, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.02129199996124953, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "knapsack", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T09:28:47.349Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Using the 0/1 knapsack recurrence, the maximum value at capacity 27 is 75. For example, items \\((3,8),(4,11),(5,14),(9,25),(6,17)\\) weigh 27 and have total value 75.\n\nFINAL: 75", "evaluation": { "passed": true, "answer": "75", "expected": "75", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.10855062550620287, "classifierCostIndex": 0, "promptTokens": 120, "completionTokens": 3130, "reasoningTokens": 3062, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 17197, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "120", "completionTokens": "3130", "reasoningTokens": "3062", "cachedTokens": "0" }, "timing": { "headersMs": 206.12370799999917, "firstEventMs": 525.5093750000233, "firstReasoningMs": 2887.9512920000125, "firstContentMs": 17098.15525000001, "lastContentMs": 17365.638875000004, "generationMs": 312.1448330000276, "totalMs": 17410.30008300004, "visibleTokensPerSecond": 214.64395023317294, "contentChunkCount": 47, "averageContentChunkCharacters": 3.74468085106383, "maxContentStallMs": 262.5295000000042, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "knapsack", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T09:29:04.760Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "The maximum value is **75**. Choose the items (5,14), (9,25), (6,17), (2,6), (4,11), and (1,2); their weights sum to 27.\n\nTo see that this is optimal, calculate \\(4v-11w\\) for each item. Only four items have positive values of this expression, and those positives sum to 6. Thus any selection of weight at most 27 satisfies \\(4V\\le 11(27)+6=303\\), so its integer value \\(V\\) is at most 75.\n\nFINAL: 75", "evaluation": { "passed": true, "answer": "75", "expected": "75", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6103654307742379, "classifierCostIndex": 0, "promptTokens": 120, "completionTokens": 880, "reasoningTokens": 744, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 11826, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "120", "completionTokens": "880", "reasoningTokens": "744", "cachedTokens": "0" }, "timing": { "headersMs": 886.7204169999459, "firstEventMs": 1192.0271249999641, "firstReasoningMs": 4931.38070899999, "firstContentMs": 12710.280417000002, "lastContentMs": 12710.794416999968, "generationMs": 518.1554999999935, "totalMs": 13228.435916999995, "visibleTokensPerSecond": 260.539548456017, "contentChunkCount": 68, "averageContentChunkCharacters": 5.882352941176471, "maxContentStallMs": 0.03079200000502169, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "knapsack", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T09:29:17.990Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 75", "evaluation": { "passed": true, "answer": "75", "expected": "75", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.9410924452669639, "classifierCostIndex": 0, "promptTokens": 120, "completionTokens": 255, "reasoningTokens": 245, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7916, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "120", "completionTokens": "255", "reasoningTokens": "245", "cachedTokens": "0" }, "timing": { "headersMs": 1426.2238750000251, "firstEventMs": 1732.4434159999946, "firstReasoningMs": 8205.81258300005, "firstContentMs": 9257.27800000005, "lastContentMs": 9257.29925000004, "generationMs": 671.9004579999018, "totalMs": 9929.178457999951, "visibleTokensPerSecond": 13.394841293591313, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 0.009665999910794199, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "knapsack", "category": "algorithms", "arm": "smart", "at": "2026-09-26T09:29:27.921Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 75", "evaluation": { "passed": true, "answer": "75", "expected": "75", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.9811202034727693, "classifierCostIndex": 0.004722542341842397, "promptTokens": 142, "completionTokens": 2899, "reasoningTokens": 2890, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 27057, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "142", "completionTokens": "2899", "reasoningTokens": "2890", "cachedTokens": "0" }, "timing": { "headersMs": 1395.4202920000535, "firstEventMs": 2348.012875000015, "firstReasoningMs": 4601.010209000087, "firstContentMs": 28415.447292000055, "lastContentMs": 28415.45329199999, "generationMs": 10.34624999994412, "totalMs": 28425.793542, "visibleTokensPerSecond": 773.2270146229994, "contentChunkCount": 3, "averageContentChunkCharacters": 3, "maxContentStallMs": 0.0032920000376179814, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 188, "classifierFailed": false, "classifierReused": false } }, { "caseId": "edit_distance", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T09:29:57.417Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "FINAL: 6", "evaluation": { "passed": true, "answer": "6", "expected": "6", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5806335527076617, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 846, "reasoningTokens": 836, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 9536, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "846", "reasoningTokens": "836", "cachedTokens": "0" }, "timing": { "headersMs": 403.44779200002085, "firstEventMs": 1014.4018330000108, "firstReasoningMs": 3061.9528329999885, "firstContentMs": 9922.282249999931, "lastContentMs": 9922.396416999982, "generationMs": 0.8003749999916181, "totalMs": 9923.082624999923, "visibleTokensPerSecond": 11244.729033383417, "contentChunkCount": 4, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.10666699998546392, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "edit_distance", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T09:30:07.341Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 6", "evaluation": { "passed": true, "answer": "6", "expected": "6", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.16114996246320046, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 4670, "reasoningTokens": 4660, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 27139, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "4670", "reasoningTokens": "4660", "cachedTokens": "0" }, "timing": { "headersMs": 406.7284579999978, "firstEventMs": 713.3504579999717, "firstReasoningMs": 2723.2798750000075, "firstContentMs": 27447.635750000016, "lastContentMs": 27447.651083000004, "generationMs": 78.81312499998603, "totalMs": 27526.448875000002, "visibleTokensPerSecond": 114.19417768298865, "contentChunkCount": 4, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.008625000016763806, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "edit_distance", "category": "algorithms", "arm": "smart", "at": "2026-09-26T09:30:34.869Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 6", "evaluation": { "passed": true, "answer": "6", "expected": "6", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 4.673640672853092, "classifierCostIndex": 0.004519132160713656, "promptTokens": 95, "completionTokens": 6897, "reasoningTokens": 6887, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 42943, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "95", "completionTokens": "6897", "reasoningTokens": "6887", "cachedTokens": "0" }, "timing": { "headersMs": 2600.4192079999484, "firstEventMs": 3492.111249999958, "firstReasoningMs": 5530.716791999992, "firstContentMs": 45539.56958300003, "lastContentMs": 45539.57837500004, "generationMs": 34.83270899998024, "totalMs": 45574.40229200001, "visibleTokensPerSecond": 258.3778367627136, "contentChunkCount": 3, "averageContentChunkCharacters": 2.6666666666666665, "maxContentStallMs": 0.004833999904803932, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 980, "classifierFailed": false, "classifierReused": false } }, { "caseId": "edit_distance", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T09:31:20.444Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 6", "evaluation": { "passed": true, "answer": "6", "expected": "6", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.5684172673365044, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 451, "reasoningTokens": 441, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6968, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "451", "reasoningTokens": "441", "cachedTokens": "0" }, "timing": { "headersMs": 937.1941670000087, "firstEventMs": 1266.203375000041, "firstReasoningMs": 5833.452083000098, "firstContentMs": 7874.32037500001, "lastContentMs": 7874.332708000089, "generationMs": 29.67291700001806, "totalMs": 7903.993292000028, "visibleTokensPerSecond": 303.30688418649646, "contentChunkCount": 4, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.004458000068552792, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-22", "category": "easy", "arm": "smart", "at": "2026-09-26T09:31:28.954Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-22,0,75,171", "evaluation": { "passed": true, "answer": "-22,0,75,171", "expected": "-22,0,75,171" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0050207783567466704, "classifierCostIndex": 0.0043928775655303, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1198, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1330.4591670000227, "firstEventMs": 1529.9454170000972, "firstReasoningMs": null, "firstContentMs": 2306.5917090000585, "lastContentMs": 2329.489709000103, "generationMs": 131.9609159999527, "totalMs": 2438.552625000011, "visibleTokensPerSecond": 83.35801488377014, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 15.923916999949142, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 209, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-22", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:31:31.393Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "-22,0,75,171", "evaluation": { "passed": true, "answer": "-22,0,75,171", "expected": "-22,0,75,171" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0600525395818441, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1296, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 835.5718749999069, "firstEventMs": 1141.877124999999, "firstReasoningMs": null, "firstContentMs": 1858.9087919999147, "lastContentMs": 1919.0494999999646, "generationMs": 207.3721670000814, "totalMs": 2066.280958999996, "visibleTokensPerSecond": 53.04472706790821, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 25.935166999930516, "finalContentBurstRatio": 0.75, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-22", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:31:33.462Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "-22,0,75,171", "evaluation": { "passed": true, "answer": "-22,0,75,171", "expected": "-22,0,75,171" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012032629448003512, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 975, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 667.2669579999056, "firstEventMs": 1121.841832999955, "firstReasoningMs": null, "firstContentMs": 1423.6909579999046, "lastContentMs": 1481.6054579999764, "generationMs": 233.94700000004377, "totalMs": 1657.6379579999484, "visibleTokensPerSecond": 47.01919665564398, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 37.7582499999553, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-22", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:31:35.120Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-22,0,75,171", "evaluation": { "passed": true, "answer": "-22,0,75,171", "expected": "-22,0,75,171" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.001315826470100042, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 32, "reasoningTokens": 18, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2226, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "32", "reasoningTokens": "18", "cachedTokens": "0" }, "timing": { "headersMs": 897.0338340000017, "firstEventMs": 1129.9728749999776, "firstReasoningMs": 2360.7633749999804, "firstContentMs": 3090.3797090000007, "lastContentMs": 3090.4244590000017, "generationMs": 6.6822500000707805, "totalMs": 3097.0619590000715, "visibleTokensPerSecond": 1945.4525047494928, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.02770899992901832, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3595", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:31:38.374Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "A rose unfolds in morning light, \nIts petals soft as dawn, \nWhile dew drops catch the waking sun \nAnd shimmer, then are gone.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005741616558306345, "classifierCostIndex": 0.004371835132999741, "promptTokens": 27, "completionTokens": 34, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2278, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "34", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 3962.6665410000132, "firstEventMs": 4390.791750000091, "firstReasoningMs": null, "firstContentMs": 5530.736208000104, "lastContentMs": 6239.27345800004, "generationMs": 836.591582999914, "totalMs": 6367.327791000018, "visibleTokensPerSecond": 39.44577099576603, "contentChunkCount": 30, "averageContentChunkCharacters": 4.266666666666667, "maxContentStallMs": 686.9030829999829, "finalContentBurstRatio": 0.046875, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 166, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3595", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:31:44.742Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "A rose unfolds at dawn, \nSoft as a blush of light.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0023672736596879284, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 63, "reasoningTokens": 43, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2784, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "63", "reasoningTokens": "43", "cachedTokens": "0" }, "timing": { "headersMs": 1274.340957999928, "firstEventMs": 1768.3730000000214, "firstReasoningMs": 2908.813542000018, "firstContentMs": 4057.811166999978, "lastContentMs": 4058.2150830000173, "generationMs": 13.087749999947846, "totalMs": 4070.898916999926, "visibleTokensPerSecond": 1451.7392217971549, "contentChunkCount": 14, "averageContentChunkCharacters": 3.642857142857143, "maxContentStallMs": 0.2334580000024289, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3595", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:31:48.814Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "A rose unfolds at dawn,\nits petals holding light;\none drop of dew slips free\nand catches morning’s gold.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.02256328783044434, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 28, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1998, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "28", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 414.83733400003985, "firstEventMs": 1334.4626250000438, "firstReasoningMs": null, "firstContentMs": 1653.0878750000848, "lastContentMs": 2057.8224590000464, "generationMs": 1178.2901249999413, "totalMs": 2831.378000000026, "visibleTokensPerSecond": 22.91456019798294, "contentChunkCount": 24, "averageContentChunkCharacters": 4.333333333333333, "maxContentStallMs": 403.6267920000246, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3595", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:31:51.646Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "A rose unfurls in dawn’s soft glow,\nA flame the quiet gardens know.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3858696531507728, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 109, "reasoningTokens": 86, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4550, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "109", "reasoningTokens": "86", "cachedTokens": "0" }, "timing": { "headersMs": 2292.0192919999827, "firstEventMs": 2352.9938750000438, "firstReasoningMs": 5395.937333000009, "firstContentMs": 6565.228750000009, "lastContentMs": 6611.162207999965, "generationMs": 75.92024999996647, "totalMs": 6641.148999999976, "visibleTokensPerSecond": 289.77776021561726, "contentChunkCount": 17, "averageContentChunkCharacters": 3.9411764705882355, "maxContentStallMs": 44.792917000013404, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "shortest_path", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T09:31:58.636Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 29\n", "evaluation": { "passed": true, "answer": "29", "expected": "29", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.007424876273363078, "classifierCostIndex": 0, "promptTokens": 157, "completionTokens": 182, "reasoningTokens": 171, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2598, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "157", "completionTokens": "182", "reasoningTokens": "171", "cachedTokens": "0" }, "timing": { "headersMs": 522.5190840000287, "firstEventMs": 1471.526708999998, "firstReasoningMs": null, "firstContentMs": 3145.9611670000013, "lastContentMs": 3146.0506250000326, "generationMs": 0.49341699993237853, "totalMs": 3146.4545839999337, "visibleTokensPerSecond": 20266.833127700247, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.030207999981939793, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "shortest_path", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T09:32:01.783Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 29", "evaluation": { "passed": true, "answer": "29", "expected": "29", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.4196683859660437, "classifierCostIndex": 0, "promptTokens": 157, "completionTokens": 93, "reasoningTokens": 83, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4578, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "157", "completionTokens": "93", "reasoningTokens": "83", "cachedTokens": "0" }, "timing": { "headersMs": 1738.8363749999553, "firstEventMs": 2497.7351250000065, "firstReasoningMs": 5262.991833999986, "firstContentMs": 6312.664374999935, "lastContentMs": 6313.676875000005, "generationMs": 18.39129200007301, "totalMs": 6331.055667000008, "visibleTokensPerSecond": 489.3620306808392, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 1.0059590000892058, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "shortest_path", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T09:32:08.115Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "FINAL: 29", "evaluation": { "passed": true, "answer": "29", "expected": "29", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.11917435618637504, "classifierCostIndex": 0, "promptTokens": 157, "completionTokens": 145, "reasoningTokens": 135, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3970, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "157", "completionTokens": "145", "reasoningTokens": "135", "cachedTokens": "0" }, "timing": { "headersMs": 283.5991670000367, "firstEventMs": 885.171209000051, "firstReasoningMs": null, "firstContentMs": 4257.147750000004, "lastContentMs": 4257.303291999968, "generationMs": 15.860875000013039, "totalMs": 4273.008625000017, "visibleTokensPerSecond": 567.4340160925927, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 0.05604199995286763, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "shortest_path", "category": "algorithms", "arm": "smart", "at": "2026-09-26T09:32:12.389Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 29", "evaluation": { "passed": true, "answer": "29", "expected": "29", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2396278494733096, "classifierCostIndex": 0.004852304009114179, "promptTokens": 198, "completionTokens": 308, "reasoningTokens": 299, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5035, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "198", "completionTokens": "308", "reasoningTokens": "299", "cachedTokens": "0" }, "timing": { "headersMs": 4589.770458000014, "firstEventMs": 5307.391500000027, "firstReasoningMs": 7461.417292000027, "firstContentMs": 9710.021375000011, "lastContentMs": 9710.031416999991, "generationMs": 0.21683300007134676, "totalMs": 9710.238208000083, "visibleTokensPerSecond": 36894.75309278421, "contentChunkCount": 2, "averageContentChunkCharacters": 4.5, "maxContentStallMs": 0.010041999979875982, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 289, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-13", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:32:23.943Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "{\n \"name\": \"Prospect Park\",\n \"location\": \"Brooklyn, New York City\",\n \"history\": [\n {\n \"period\": \"Before the park\",\n \"summary\": \"The land was part of the homeland of the Lenape people. During the Battle of Long Island in 1776, fighting took place in and around what is now the park.\"\n },\n {\n \"period\": \"1850s–1860s\",\n \"summary\": \"As Brooklyn grew, civic leaders sought a large public park. An initial plan by Egbert Viele was set aside, and Frederick Law Olmsted and Calvert Vaux—designers of Manhattan's Central Park—developed a new plan.\"\n },\n {\n \"period\": \"1867–1870s\",\n \"summary\": \"Prospect Park opened to the public in 1867 while construction continued. Its design brought together the Long Meadow, wooded Ravine, and lake to create varied landscapes within the city.\"\n },\n {\n \"period\": \"20th century\",\n \"summary\": \"The park remained a major recreational space but suffered from reduced maintenance and deterioration, particularly in the mid-to-late 20th century.\"\n },\n {\n \"period\": \"1987–present\",\n \"summary\": \"The Prospect Park Alliance, founded in 1987, has worked with New York City to restore and care for the park. Projects have revived landscapes, buildings, and recreational areas, including the Lakeside area, which reopened in 2013.\"\n }\n ]\n}", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.4068453164242641, "classifierCostIndex": 0, "promptTokens": 43, "completionTokens": 594, "reasoningTokens": 262, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5644, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "43", "completionTokens": "594", "reasoningTokens": "262", "cachedTokens": "0" }, "timing": { "headersMs": 1739.311791999964, "firstEventMs": 2187.742959000054, "firstReasoningMs": 5530.272709000041, "firstContentMs": 6318.559666999965, "lastContentMs": 7373.590291999979, "generationMs": 1063.7250420000637, "totalMs": 7382.284709000029, "visibleTokensPerSecond": 311.17063802280984, "contentChunkCount": 99, "averageContentChunkCharacters": 13.525252525252526, "maxContentStallMs": 521.9763749999693, "finalContentBurstRatio": 0.31142643764002986, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-13", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:32:31.327Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "{\n \"title\": \"A brief history of Prospect Park\",\n \"overview\": \"Prospect Park, in Brooklyn, was designed by Frederick Law Olmsted and Calvert Vaux as a large public park for the growing city. It officially opened in 1867, while construction continued into the early 1870s. Today it is a major New York City park and a designated National Historic Landmark.\",\n \"timeline\": [\n {\n \"period\": \"Before the park\",\n \"details\": \"The land was home to Indigenous people, including the Lenape, before European settlement. In the colonial period, it became a patchwork of farms and estates. The area also includes Battle Pass, where American forces fought British troops during the Battle of Long Island in August 1776.\"\n },\n {\n \"period\": \"1850s–1860s: The park is planned\",\n \"details\": \"Brooklyn leaders sought a large public park as the city grew. After the success of Central Park, Olmsted and Vaux were engaged to design a Brooklyn park. Their plan made use of the area's varied terrain, including open meadows, wooded slopes, and a lake.\"\n },\n {\n \"period\": \"1866–1873: Construction\",\n \"details\": \"Work began in 1866, and the park opened in stages beginning in 1867. Construction continued for several years, with the park substantially completed in 1873. Its landscape was carefully shaped to create a sequence of naturalistic scenes, including the Long Meadow, the Ravine, and the Lake.\"\n },\n {\n \"period\": \"Late 19th century\",\n \"details\": \"Prospect Park became a popular destination for recreation and public gatherings. Brooklyn's consolidation with New York City in 1898 brought the park under the new city's administration. The Prospect Park Zoo traces its history to a small menagerie established in the park in 1890.\"\n },\n {\n \"period\": \"20th century\",\n \"details\": \"The city added or expanded amenities over time, including the zoo, playgrounds, and the bandshell. In the mid-20th century, heavy use and limited maintenance contributed to the park's deterioration.\"\n },\n {\n \"period\": \"1980s to the present\",\n \"details\": \"A major restoration effort began in the 1980s. The Prospect Park Alliance, founded in 1987, works with New York City to care for and improve the park. Restoration has continued across its landscapes, buildings, recreational spaces, and natural areas.\"\n }\n ],\n \"significance\": \"Prospect Park is both a major public space and an important work of landscape design. Olmsted and Vaux treated it not simply as a collection of facilities, but as an immersive landscape intended to offer city residents beauty, recreation, and respite.\"\n}", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.03233277668230859, "classifierCostIndex": 0.004427948286414566, "promptTokens": 43, "completionTokens": 802, "reasoningTokens": 201, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5309, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "43", "completionTokens": "802", "reasoningTokens": "201", "cachedTokens": "0" }, "timing": { "headersMs": 601.7025839999551, "firstEventMs": 909.1475419999333, "firstReasoningMs": 3306.108750000014, "firstContentMs": 4286.914749999996, "lastContentMs": 5873.120333999977, "generationMs": 1601.4176669999724, "totalMs": 5888.332416999969, "visibleTokensPerSecond": 374.66802843758705, "contentChunkCount": 120, "averageContentChunkCharacters": 22.066666666666666, "maxContentStallMs": 173.2570410000626, "finalContentBurstRatio": 0.2039274924471299, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 203, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-13", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:32:37.216Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "{\n \"title\": \"A Brief History of Prospect Park\",\n \"overview\": \"Prospect Park is a 526-acre public park in Brooklyn, New York. Designed by Frederick Law Olmsted and Calvert Vaux, it was intended to offer city residents a large, carefully landscaped refuge. The park opened in 1867, while construction and improvements continued into the 1870s.\",\n \"history\": [\n {\n \"period\": \"Before the park\",\n \"details\": \"The area was part of the Lenape homeland before European colonization. Under Dutch and later British rule, the surrounding countryside was divided into farms and settlements, including those associated with Flatbush. The park’s northwestern area was also a site of fighting during the Battle of Brooklyn on August 27, 1776, early in the American Revolutionary War.\"\n },\n {\n \"period\": \"Planning and design, 1850s–1860s\",\n \"details\": \"As Brooklyn grew, civic leaders sought a major public park. The city began acquiring land around 1859–1860. Olmsted and Vaux, who had designed Central Park, developed the winning plan for Prospect Park in 1865. Work began in 1866.\"\n },\n {\n \"period\": \"Opening and completion, 1867–1870s\",\n \"details\": \"Prospect Park opened to the public in 1867, although it was still unfinished. Olmsted and Vaux shaped its scenery around broad meadows, wooded areas, winding paths, and a large lake. Major construction continued through the early 1870s, creating signature landscapes such as the Long Meadow, the Ravine, and the Nethermead.\"\n },\n {\n \"period\": \"A growing civic landmark\",\n \"details\": \"As Brooklyn expanded, the park became a major place for recreation and public gatherings. The Maryland Monument, dedicated in 1895 on Lookout Hill, commemorates Maryland soldiers who fought during the Battle of Brooklyn. Brooklyn became part of New York City in 1898, bringing the park into the city’s unified parks system.\"\n },\n {\n \"period\": \"20th-century changes and challenges\",\n \"details\": \"New facilities and attractions were added over time, including the Prospect Park Zoo, which opened in 1890, and the Boathouse, completed in 1905. Like many urban parks, Prospect Park experienced periods of heavy use and declining maintenance in the mid-20th century. Later renovations added or improved recreational facilities and restored parts of the landscape.\"\n },\n {\n \"period\": \"Restoration and today\",\n \"details\": \"A renewed preservation effort gained momentum in the 1980s. The Prospect Park Alliance was founded in 1987 in partnership with New York City, helping lead ongoing restoration and care. Today the park remains a major public space for Brooklyn, with meadows, woodland, waterways, sports facilities, cultural events, and historic sites.\"\n }\n ],\n \"significance\": \"Prospect Park is both a landmark of landscape design and an important part of Brooklyn’s civic life. Its design combines naturalistic scenery with places for recreation, while its history reflects the area’s Indigenous past, Revolutionary War history, urban growth, and continuing efforts to preserve public green space.\"\n}", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04524055550376255, "classifierCostIndex": 0, "promptTokens": 43, "completionTokens": 1306, "reasoningTokens": 614, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8584, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "43", "completionTokens": "1306", "reasoningTokens": "614", "cachedTokens": "0" }, "timing": { "headersMs": 677.0655829999596, "firstEventMs": 1063.0477499999106, "firstReasoningMs": 4319.023749999935, "firstContentMs": 8454.532249999931, "lastContentMs": 9356.935332999914, "generationMs": 902.6804580000462, "totalMs": 9357.212707999977, "visibleTokensPerSecond": 765.4979055722115, "contentChunkCount": 130, "averageContentChunkCharacters": 24.015384615384615, "maxContentStallMs": 467.71595899993554, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-13", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:32:46.574Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "{\n \"title\": \"A Brief History of Prospect Park, Brooklyn\",\n \"overview\": \"Prospect Park is a 526-acre public park in Brooklyn, New York City. Designed principally by Frederick Law Olmsted and Calvert Vaux, the landscape architects behind Central Park, it opened in 1867 and became one of the defining public spaces of the then-independent city of Brooklyn.\",\n \"timeline\": [\n {\n \"period\": \"Before the park\",\n \"history\": \"The area was part of the homeland of the Lenape before Dutch and later British colonization. Its hills, wetlands, and wooded terrain were shaped by glaciers. Under European settlement, much of the surrounding land became farms and rural estates.\"\n },\n {\n \"period\": \"1776: The Battle of Long Island\",\n \"history\": \"During the Revolutionary War, fighting in the Battle of Long Island, also called the Battle of Brooklyn, took place in and around what is now Prospect Park. Battle Pass, in the park’s eastern section, marks an important position where American forces tried to resist the British advance.\"\n },\n {\n \"period\": \"1850s–1865: Planning a park for Brooklyn\",\n \"history\": \"As Brooklyn grew rapidly, civic leaders pushed for a major public park. James S. T. Stranahan became its leading advocate. An early plan by engineer Egbert Viele included land around Mount Prospect, near today’s Brooklyn Museum and central library. The Civil War slowed progress, and Olmsted and Vaux subsequently developed a substantially different plan.\"\n },\n {\n \"period\": \"1866–1870s: Construction and opening\",\n \"history\": \"Construction began in 1866, and the park opened to the public in 1867 while work continued. Olmsted and Vaux created an apparently natural landscape through extensive excavation, grading, planting, and water engineering. Its signature features included the Long Meadow, the wooded Ravine, and the Lake. Separate routes for pedestrians, horseback riders, and carriages helped limit conflicts between different users.\"\n },\n {\n \"period\": \"Late 1800s–early 1900s: A growing civic landscape\",\n \"history\": \"The park became a destination for strolling, boating, skating, concerts, and organized recreation. Monuments and architectural features accumulated around its original pastoral design. The Soldiers’ and Sailors’ Memorial Arch at what is now Grand Army Plaza was dedicated in 1892, and the Beaux-Arts Boathouse was completed in 1905. Brooklyn’s consolidation into New York City in 1898 brought the park into the larger municipal park system.\"\n },\n {\n \"period\": \"1930s–1960s: Expanded recreation\",\n \"history\": \"During the Robert Moses era, the park gained or expanded facilities for active recreation. Prospect Park Zoo opened in its modern form in 1935, and the Bandshell opened in 1939. Playgrounds, athletic facilities, and later Wollman Rink broadened the park’s uses, sometimes changing elements of the original landscape.\"\n },\n {\n \"period\": \"1970s–1980s: Decline and preservation\",\n \"history\": \"Budget shortages, heavy use, and deferred maintenance contributed to deteriorating landscapes and buildings. Prospect Park became a New York City scenic landmark in 1975. Community advocacy and preservation efforts helped build support for restoration.\"\n },\n {\n \"period\": \"1987–present: Restoration and renewal\",\n \"history\": \"The Prospect Park Alliance was founded in 1987 to work with NYC Parks on restoration, maintenance, and programming. Subsequent projects restored woodland, waterways, historic structures, and recreational spaces. The LeFrak Center at Lakeside opened in 2013 as part of a major redesign of the park’s southeastern lakeshore. The park became permanently car-free in 2018.\"\n }\n ],\n \"significance\": \"Prospect Park combines a carefully engineered nineteenth-century landscape with Revolutionary War history and generations of Brooklyn community life. Its enduring achievement is making a densely populated urban setting feel like an expansive retreat of meadow, forest, and water.\"\n}", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 3.685209094099607, "classifierCostIndex": 0, "promptTokens": 43, "completionTokens": 1084, "reasoningTokens": 215, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 22172, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "43", "completionTokens": "1084", "reasoningTokens": "215", "cachedTokens": "0" }, "timing": { "headersMs": 819.002833000035, "firstEventMs": 1267.8527079999913, "firstReasoningMs": 7883.731832999969, "firstContentMs": 8908.924583000015, "lastContentMs": 22942.552333, "generationMs": 14085.986334000016, "totalMs": 22994.91091700003, "visibleTokensPerSecond": 61.621527908547456, "contentChunkCount": 193, "averageContentChunkCharacters": 21.031088082901555, "maxContentStallMs": 1541.968916999991, "finalContentBurstRatio": 0.07046070460704607, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-14", "category": "easy", "arm": "smart", "at": "2026-09-26T09:33:10.332Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005261822119131988, "classifierCostIndex": 0.0044174270701492855, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2020, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 849.9587080000201, "firstEventMs": 1738.2558750000317, "firstReasoningMs": null, "firstContentMs": 2868.155541999964, "lastContentMs": 2868.1790000000037, "generationMs": 52.881999999983236, "totalMs": 2921.0375419999473, "visibleTokensPerSecond": 132.37018267089405, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.023458000039681792, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 229, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-14", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:33:13.253Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04386605301987537, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1213, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1987.8637919999892, "firstEventMs": 2667.9922500000102, "firstReasoningMs": null, "firstContentMs": 3014.4955840000184, "lastContentMs": 3014.5758340000175, "generationMs": 271.75908300001174, "totalMs": 3286.25466700003, "visibleTokensPerSecond": 18.398649071095754, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.08024999999906868, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-14", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:33:16.540Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.020272225544985683, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 23, "reasoningTokens": 15, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6943, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "23", "reasoningTokens": "15", "cachedTokens": "0" }, "timing": { "headersMs": 773.88979200006, "firstEventMs": 5778.861083999975, "firstReasoningMs": null, "firstContentMs": 7340.55929200002, "lastContentMs": 7714.60387500003, "generationMs": 430.81562500004657, "totalMs": 7771.3749170000665, "visibleTokensPerSecond": 16.248250048960603, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 374.0445830000099, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-14", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:33:24.312Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0009819801847594368, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 21, "reasoningTokens": 13, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2684, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "21", "reasoningTokens": "13", "cachedTokens": "0" }, "timing": { "headersMs": 868.2295000000158, "firstEventMs": 1153.2828750000335, "firstReasoningMs": 2505.4370830000844, "firstContentMs": 3633.0679170000367, "lastContentMs": 3633.083250000025, "generationMs": 0.29004100000020117, "totalMs": 3633.357958000037, "visibleTokensPerSecond": 24134.518912826617, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.01533299998845905, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "topological_orders", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T09:33:28.120Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Task I must be last. Consider a valid order of the six tasks A–F, then insert G and H into its seven gaps (including the gaps before and after all six tasks).\n\nFix the relative order of A, B, C. Of D, E, F, exactly one task has its prerequisites complete after the first two of A, B, C; call it the early task. The other two can only occur after all three.\n\nIf the early task is D or E, inserting it after the first two initial tasks gives two base orders, each with 3 valid insertions of G and H, for a total of 6. If it instead occurs after all three, the six orders of D, E, F contribute 20 insertions. Thus each such initial-task order contributes 26.\n\nIf the early task is F, placing it after the first two contributes 10, and placing it after all three contributes 20, for a total of 30.\n\nAcross the six possible relative orders of A, B, C, the early task is D twice, E twice, and F twice. Therefore the number of valid total orders is \\(2(26)+2(26)+2(30)=164\\).\n\nFINAL: 164", "evaluation": { "passed": true, "answer": "164", "expected": "164", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1515817255942567, "classifierCostIndex": 0, "promptTokens": 97, "completionTokens": 4386, "reasoningTokens": 4127, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 25440, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "97", "completionTokens": "4386", "reasoningTokens": "4127", "cachedTokens": "0" }, "timing": { "headersMs": 540.3297920000041, "firstEventMs": 948.5412090000464, "firstReasoningMs": 3314.6735000000335, "firstContentMs": 25127.653792000026, "lastContentMs": 25970.60737500002, "generationMs": 1319.2433749999618, "totalMs": 26446.89716699999, "visibleTokensPerSecond": 195.5666444032796, "contentChunkCount": 89, "averageContentChunkCharacters": 11.01123595505618, "maxContentStallMs": 832.2159580000443, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "topological_orders", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T09:33:54.567Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Task I must be last. First order A–F, then insert G after both D and E and H after F.\n\nIn an A–F order, let \\(m\\) be the later position of D and E, and let \\(f\\) be F’s position. There are \\(7-m\\) slots for G and \\(7-f\\) for H; if they use the same slot, either order is possible. Thus the number of insertions is\n\\[\n(7-m)(7-f)+(7-\\max(m,f)).\n\\]\n\nSumming this over the valid A–F orders gives 120 when A, B, C occupy the first three positions, 24 when D or E precedes the last of A, B, C, and 20 when F does. The total is \\(120+24+20=164\\).\n\nFINAL: 164", "evaluation": { "passed": true, "answer": "164", "expected": "164", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.0224410056688382, "classifierCostIndex": 0, "promptTokens": 97, "completionTokens": 1495, "reasoningTokens": 1310, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 13926, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "97", "completionTokens": "1495", "reasoningTokens": "1310", "cachedTokens": "0" }, "timing": { "headersMs": 651.1288329999661, "firstEventMs": 1217.7292080000043, "firstReasoningMs": 7169.638791000005, "firstContentMs": 14543.509499999927, "lastContentMs": 14574.327457999927, "generationMs": 49.27062500000466, "totalMs": 14592.780124999932, "visibleTokensPerSecond": 3734.476678547971, "contentChunkCount": 78, "averageContentChunkCharacters": 7.064102564102564, "maxContentStallMs": 30.037624999997206, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "topological_orders", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T09:34:09.161Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Every task precedes I, so **I must be last**. Count valid orders of the other eight tasks.\n\nThe first two tasks must be distinct members of A, B, C. Split by the third task:\n\n- **Third task is the remaining member of A, B, C:** There are \\(3!=6\\) initial orders. The remaining constraints are \\(D,E>\n\n---\n\n## Slide 1: Title\n**NearBy**\n*Send handwritten letters to neighbors you've never met*\n\n---\n\n## Slide 2: The Problem\n- People feel increasingly disconnected from their local communities\n- 61% of Americans don't know most of their neighbors\n- Digital communication has replaced meaningful local connection\n- No easy way to reach out to people nearby without being intrusive or awkward\n\n---\n\n## Slide 3: The Solution\n**NearBy** lets users send physical letters to addresses within a chosen radius or territory — no names, no contacts, just genuine outreach.\n\n- Select a neighborhood, street, or radius on a map\n- Write or generate a letter (community event, introduction, kindness note, local business promo)\n- We print, stamp, and mail it — or connect you with local carriers for hand delivery\n\n---\n\n## Slide 4: How It Works\n1. **Choose Your Territory** – Draw a zone on the map\n2. **Compose Your Letter** – Use templates or write your own\n3. **Preview & Send** – We handle printing & delivery logistics\n4. **Track Engagement** – Opt-in replies, QR codes, or scannable links\n\n---\n\n## Slide 5: Use Cases\n- 🏘️ **Neighbors** reconnecting after moving to a new area\n- 🎉 **Community organizers** promoting local events\n- 🏪 **Small businesses** doing hyper-local marketing\n- 💌 **Random acts of kindness** campaigns\n- 🕊️ **Nonprofits** raising local awareness\n- 🏡 **Realtors** engaging a neighborhood\n\n---\n\n## Slide 6: Market Opportunity\n- Direct mail market: $30B+ annually in the US\n- Growing demand for \"digital detox\" / analog connection experiences\n- Hyperlocal marketing is underserved by big platforms (Meta, Google) which lack physical-mail integration\n- Target: individuals, small businesses, HOAs, nonprofits, local governments\n\n---\n\n## Slide 7: Business Model\n- **Pay-per-letter** pricing (volume discounts)\n- **Subscription plans** for businesses & recurring senders\n- **Premium options**: handwritten-style fonts, wax seals, local paper stock\n- **Data insights** (opt-in, anonymized) for local businesses\n\n---\n\n## Slide 8: Why Now\n- Nostalgia & analog trends (vinyl, film cameras, letter-writing) are resurging\n- Post-pandemic desire for authentic community connection\n- Print-on-demand & logistics infrastructure now cheap & scalable\n- AI tools make personalized-at-scale writing easy\n\n---\n\n## Slide 9: Competitive Landscape\n| Company | Focus | Gap |\n|---|---|---|\n| Nextdoor | Digital neighborhood app | No physical touch |\n| Every Door Direct Mail (USPS) | Bulk mail | No personalization/platform |\n| PostGrid / Lob | B2B mail API | Not consumer-friendly |\n| **NearBy** | Personal + local + physical | ✅ Unique niche |\n\n---\n\n## Slide 10: Traction (Sample)\n- Beta launched in 3 cities\n- 5,000 letters sent in pilot phase\n- 22% opt-in reply rate\n- Partnerships with 2 local business associations\n\n---\n\n## Slide 11: Go-To-Market Strategy\n- Launch in mid-size cities with strong community identity\n- Partner with HOAs, chambers of commerce, local nonprofits\n- Social proof via \"kindness campaigns\" that go viral\n- Influencer/local personality collaborations\n\n---\n\n## Slide 12: Team\n- **Founder/CEO** – Background in logistics & community platforms\n- **Head of Product** – Ex-mail-tech engineer\n- **Head of Growth** – Local marketing & partnerships expert\n\n*(Add real bios/photos)*\n\n---\n\n## Slide 13: The Ask\nRaising **$1.5M seed round** to:\n- Expand to 10 new cities\n- Build self-serve business dashboard\n- Scale printing/delivery partnerships\n- Grow marketing & community partnerships team\n\n---\n\n## Slide 14: Vision\n**NearBy's mission**: Rebuild local trust and connection — one letter, one street, one town at a time.\n\n---\n\n*Thank you — let's bring neighbors back together.*", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.0141954745267834, "classifierCostIndex": 0.004459511935210405, "promptTokens": 73, "completionTokens": 1481, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 18923, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "73", "completionTokens": "1481", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1432.3957499999087, "firstEventMs": 2456.4907079999102, "firstReasoningMs": null, "firstContentMs": 2456.595417000004, "lastContentMs": 20253.829582999926, "generationMs": 17858.466290999902, "totalMs": 20315.061707999907, "visibleTokensPerSecond": 82.87385802810361, "contentChunkCount": 385, "averageContentChunkCharacters": 9.742857142857142, "maxContentStallMs": 1227.0094590000808, "finalContentBurstRatio": 0.10663822980538523, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 272, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3697", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:36:12.338Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "# <>\n\n## Slide 1 — The Pitch\n**Reach prospective customers by sending relevant, personalized letters—without needing to know them first.**\n\nTerritoryPost helps local businesses and sales teams discover prospects within a defined territory, create compelling mail campaigns, and track the response.\n\n**Choose your area. Create your message. We handle the mail.**\n\n---\n\n## Slide 2 — The Problem\n### You know where you sell—but not everyone you could sell to.\n\nFor local businesses and territory-based sales teams:\n- Digital advertising is crowded and increasingly expensive.\n- Email outreach requires contact information and struggles for attention.\n- Traditional direct mail involves fragmented vendors, list management, and manual coordination.\n- Blanket mailings waste money on households or businesses outside the ideal audience.\n\n**Local prospecting should be as simple as drawing a boundary on a map.**\n\n---\n\n## Slide 3 — The Solution\n### A self-service platform for territory-based direct mail.\n\nWith TerritoryPost, customers can:\n1. **Define a territory:** Draw a boundary or select ZIP codes.\n2. **Find an audience:** Choose household or business segments using appropriately licensed address data.\n3. **Create a letter:** Customize a template or draft messaging with AI assistance.\n4. **Launch a campaign:** Submit for printing, postage, and mailing.\n5. **Measure results:** Track responses through campaign-specific QR codes, URLs, and phone numbers.\n\n**No existing contact list required.**\n\n---\n\n## Slide 4 — The Product\n### From map to mailbox in one workflow.\n\n**Example campaign: A local landscaping company**\n- Select neighborhoods within its service area.\n- Identify eligible residential addresses.\n- Create a seasonal maintenance offer.\n- Preview letters, confirm campaign costs, and approve mailing.\n- Route responses to a booking page.\n- Compare campaign spend with booked jobs.\n\n**Core features:** Address validation, duplicate removal, suppression lists, campaign scheduling, CRM integration, and response reporting.\n\n---\n\n## Slide 5 — The Initial Market\n### Start with businesses where geography defines the customer base.\n\n**Beachhead: Home-service businesses**\n- Landscaping\n- Cleaning\n- Painting\n- HVAC\n- Pest control\n\nThese businesses have clear service areas, recurring acquisition needs, and measurable outcomes such as calls, estimates, and bookings.\n\n**Expansion:** Local professional services, franchises, and territory-based B2B sales teams.\n\n**Bottom-up market sizing:** Target businesses × expected annual platform and mailing spend. Validate these inputs before presenting a market-size claim.\n\n---\n\n## Slide 6 — The Business Model\n### Subscription revenue plus usage-based mailing revenue.\n\n**Illustrative pricing to validate:**\n- **Starter — $49/month:** One territory, templates, and basic reporting.\n- **Growth — $199/month:** Multiple campaigns, automation, and CRM integrations.\n- **Teams — Custom pricing:** Multi-location management, permissions, and consolidated reporting.\n\n**Mailing charges:** Transparent per-piece pricing covering data, production, postage, and platform margin.\n\n**Expansion revenue:** More territories, larger campaigns, additional users, and repeat mailings.\n\n---\n\n## Slide 7 — The Competitive Edge\n### Built around a territory—not just a mailing list.\n\n| Alternative | Common limitation | TerritoryPost’s focus |\n|---|---|---|\n| Traditional mail vendors | Manual setup and coordination | Self-service execution |\n| List brokers | Provide data, not a complete workflow | Audience-to-mail campaign management |\n| Digital ads | Compete for attention in crowded feeds | Physical outreach to selected addresses |\n| Enterprise mail platforms | Can be complex for smaller teams | Simple local-business workflows |\n\n**Long-term defensibility:** Workflow integrations, reliable fulfillment, and campaign benchmarks developed from appropriately aggregated data.\n\n---\n\n## Slide 8 — Go-to-Market\n### Win one vertical, then expand territory by territory.\n\n**Phase 1: Founder-led pilots**\nRecruit home-service businesses in a small number of metro areas.\n\n**Phase 2: Repeatable acquisition**\nPublish verified campaign case studies, build vertical-specific templates, and offer guided first campaigns.\n\n**Phase 3: Channel distribution**\nPartner with local marketing agencies, franchise networks, and industry software providers.\n\n**Retention engine:** Seasonal campaigns, new-service-area launches, and repeat outreach with frequency limits.\n\n---\n\n## Slide 9 — Validation and Responsible Growth\n### Prove customer value before scaling.\n\n**Pilot metrics**\n- Time from signup to first mailing\n- Response and qualified-lead rates\n- Cost per booked job\n- Customer repeat-campaign rate\n- Contribution margin per campaign\n- Undeliverable-mail and complaint rates\n\n**Trust built into the product**\n- Appropriately sourced address data\n- Recipient opt-out and suppression controls\n- Clear sender identification\n- No sensitive personal targeting or misleading familiarity\n- Review processes for applicable marketing and privacy requirements\n\n**Current status:** Concept-stage; traction and performance claims require pilot evidence.\n\n---\n\n## Slide 10 — The Ask\n### Fund the path from prototype to repeatable customer acquisition.\n\n**Seeking:** [Funding amount] for [runway period].\n\n**Use of funds**\n- Build the territory-selection and campaign platform.\n- Integrate address-data and print-and-mail partners.\n- Run paid pilots in the initial vertical.\n- Establish compliance, deliverability, and measurement systems.\n\n**Milestones**\n1. Launch the end-to-end MVP.\n2. Demonstrate repeat paid campaigns.\n3. Validate campaign-level contribution margins.\n4. Establish a repeatable acquisition channel.\n\n### TerritoryPost\n**You know your territory. Now reach the people in it.**", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 4.061624490224309, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 1194, "reasoningTokens": 56, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 23396, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "1194", "reasoningTokens": "56", "cachedTokens": "0" }, "timing": { "headersMs": 1309.7275410000002, "firstEventMs": 1679.8817499999423, "firstReasoningMs": 4064.90387499996, "firstContentMs": 7279.598499999964, "lastContentMs": 24408.705290999962, "generationMs": 17483.894499999937, "totalMs": 24763.4929999999, "visibleTokensPerSecond": 65.03127778539296, "contentChunkCount": 239, "averageContentChunkCharacters": 24.602510460251047, "maxContentStallMs": 778.9919170000358, "finalContentBurstRatio": 0.1141156462585034, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3697", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:36:37.107Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "# <>\n\n### 1. The opportunity\nYou have a territory to reach, but you don’t know everyone in it. Finding addresses, preparing letters, and getting them into the mail takes more time than writing the message itself.\n\n### 2. The solution\nNeighborNote lets you send physical letters to people in a defined area—without needing a personal connection or a spreadsheet of names.\n\n### 3. How it works\n1. **Choose a territory:** Draw a map or enter ZIP codes.\n2. **Choose recipients:** Use eligible household or business mailing lists, with exclusions where required.\n3. **Write once, personalize appropriately:** Pick a template and add details relevant to the area.\n4. **Approve and send:** We print, address, stamp, and mail the letters.\n\n### 4. Why a letter?\nA physical letter can make a local introduction feel more deliberate than another digital message. It gives recipients something they can read on their own time—and an easy way to respond if they’re interested.\n\n### 5. Who it’s for\n- Local businesses introducing themselves to nearby customers\n- Real estate professionals working a defined area\n- Community organizations inviting neighbors to participate\n- Anyone with a legitimate reason to reach a geographic audience by mail\n\n### 6. What makes NeighborNote different\n**Territory-first, not contact-list-first.** Users start with the place they serve. NeighborNote handles eligible address sourcing, mail production, delivery, and campaign-level response tracking in one workflow.\n\n### 7. Trust is part of the product\nClear sender identification, lawful data sourcing, address verification, suppression lists, and a simple way to request no further mail help make outreach more respectful for recipients and safer for senders.\n\n### 8. Business model\nCharge per letter, with volume-based pricing for repeat senders. Optional subscriptions add saved territories, team approvals, templates, and reporting.\n\n### 9. Go-to-market\nStart with local professionals who already use direct mail but assemble campaigns manually. Partner with industry associations and local marketing agencies, then grow through repeat campaigns and referrals.\n\n### 10. The ask\nWe’re seeking pilot partners to test whether NeighborNote can cut campaign setup time while helping senders reach the right territory responsibly.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5213485223636309, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 762, "reasoningTokens": 297, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7855, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "762", "reasoningTokens": "297", "cachedTokens": "0" }, "timing": { "headersMs": 321.22750000003725, "firstEventMs": 672.0160000000615, "firstReasoningMs": null, "firstContentMs": 4275.661792000057, "lastContentMs": 8173.663541999995, "generationMs": 3904.2128329999978, "totalMs": 8179.874625000055, "visibleTokensPerSecond": 118.84597993175038, "contentChunkCount": 115, "averageContentChunkCharacters": 20.11304347826087, "maxContentStallMs": 610.6286249998957, "finalContentBurstRatio": 0.20925205361003027, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3697", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:36:45.287Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "# <>\n\n### 1. The opportunity\n**Good businesses have a local audience. Reaching it shouldn’t require knowing everyone personally.**\n\nLetterline helps businesses send thoughtful, relevant letters to people in the neighborhoods they serve.\n\n---\n\n### 2. The problem\nLocal outreach is still too hard to do well.\n\n- Digital ads are crowded and easy to ignore.\n- Traditional direct mail is slow, fragmented, and hard to measure.\n- Small businesses lack the time and expertise to plan effective mail campaigns.\n- Generic “junk mail” makes people less receptive to the letters worth reading.\n\n---\n\n### 3. The insight\n**A physical letter can feel personal without pretending to be personal.**\n\nWhen it’s useful, clearly from a real business, and sent to the right neighborhood, mail can earn attention that a crowded inbox may not.\n\n---\n\n### 4. The solution\n**Letterline makes local letter outreach simple.**\n\nBusinesses can define a service area, create a campaign, and send printed letters to eligible addresses—without managing lists, design, printing, and postage separately.\n\n**One workflow. From territory to mailbox.**\n\n---\n\n### 5. How it works\n1. **Choose a territory** — draw a service area or select neighborhoods.\n2. **Set campaign guardrails** — choose permitted, non-sensitive audience criteria.\n3. **Create the letter** — use a template or write your own.\n4. **Review and approve** — see the final proof, sender details, and recipient count.\n5. **Send and learn** — print, mail, and track responses with campaign-specific links or codes.\n\n---\n\n### 6. Who we serve\n**Start with local businesses where trust and geography matter.**\n\n- Home services\n- Clinics and wellness practices\n- Independent retailers\n- Real estate professionals\n- Community organizations\n\n**Initial buyer:** an owner or local marketing lead who wants more nearby customers without building a direct-mail operation.\n\n---\n\n### 7. Business model\n**Simple, campaign-based pricing.**\n\n- Pay per campaign based on volume, print format, and postage\n- Optional monthly plan for recurring campaigns, templates, and reporting\n- Agency and multi-location plans for teams managing many territories\n\nLetterline earns revenue from campaign fees and software subscriptions.\n\n---\n\n### 8. Go-to-market\n**Win locally, then expand through repeat use.**\n\n- Launch in a few dense metro areas with strong small-business communities\n- Partner with print shops, local business associations, and marketing agencies\n- Offer territory-based campaign templates for common local use cases\n- Turn successful first campaigns into repeat seasonal and neighborhood outreach\n\n---\n\n### 9. Why Letterline\n**Direct mail tools handle the pieces. Letterline connects the whole job.**\n\n- Territory-first campaign setup\n- Letter-writing templates built for local businesses\n- Print and postage coordinated in one workflow\n- Response tracking that helps users learn what worked\n- Privacy and compliance safeguards built into campaign creation\n\nOur advantage grows with better campaign benchmarks, stronger local distribution partnerships, and a smoother path from first draft to delivery.\n\n---\n\n### 10. Trust is part of the product\nLetterline is designed for respectful outreach.\n\n- Use authorized, appropriately sourced mailing data\n- Exclude sensitive personal traits from targeting\n- Clearly identify the sender and why they’re writing\n- Provide a way to opt out of future mail where applicable\n- Give senders a final review before anything goes to print\n\n---\n\n### 11. The opportunity\n**Illustrative U.S. market scenario—not a current market measurement:**\n\nIf 250,000 local businesses spent an average of $6,000 per year on letter campaigns, that would represent **$1.5B in annual campaign spend**.\n\nOur first goal is to validate the customer count, typical spend, and repeat-campaign rate in our launch markets.\n\n---\n\n### 12. The ask\n**We’re building the easiest way for local businesses to reach their neighborhoods by mail.**\n\nWe’re seeking **$1.5M in seed funding** to support an 18-month plan:\n\n- Launch the core campaign and mailing platform\n- Build print and postage partnerships\n- Pilot with local businesses in three metro areas\n- Measure repeat usage, campaign economics, and customer acquisition\n\n**Letterline: Make the next letter count.**", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04842996779341047, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 1397, "reasoningTokens": 506, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 11614, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "1397", "reasoningTokens": "506", "cachedTokens": "0" }, "timing": { "headersMs": 1109.500791999977, "firstEventMs": 1624.9532500000205, "firstReasoningMs": 4469.540291999932, "firstContentMs": 11428.817582999938, "lastContentMs": 12683.870791999972, "generationMs": 1260.407542000059, "totalMs": 12689.225124999997, "visibleTokensPerSecond": 706.1208143738307, "contentChunkCount": 140, "averageContentChunkCharacters": 30.90714285714286, "maxContentStallMs": 642.7351250000065, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2164", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:36:58.381Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Meet **the squeaker** by [brand name]: a playful new line of latex toys designed for dogs of all ages and species. Choose from a variety of colors, including [available colors], and shapes such as [available shapes] to find a new favorite for your pup.\n\nExplore the collection at [website]. Supervise play and replace any toy that becomes damaged.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1759761097170237, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 245, "reasoningTokens": 165, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3904, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "245", "reasoningTokens": "165", "cachedTokens": "0" }, "timing": { "headersMs": 2464.3969170000637, "firstEventMs": 2888.0876250000438, "firstReasoningMs": 4755.689542000066, "firstContentMs": 6131.182209000108, "lastContentMs": 6324.601500000106, "generationMs": 193.61854099994525, "totalMs": 6324.800750000053, "visibleTokensPerSecond": 408.0187754334041, "contentChunkCount": 52, "averageContentChunkCharacters": 6.673076923076923, "maxContentStallMs": 193.1299580000341, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2164", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:37:04.706Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "### Meet “the squeaker”—Big Fun for Every Dog!\n\nBring a little squeak to playtime with **the squeaker**, a new line of latex dog toys designed for dogs of all ages and breeds. From curious puppies to playful seniors, there’s a squeaker to brighten every dog’s day.\n\nAvailable in a variety of colors and shapes, these toys make it easy to find a match for your pup’s personality.\n\n- **Made of latex** for flexible, playful fun.\n- **Plenty of variety** to keep your toy basket colorful.\n- **Designed for every life stage**, from puppyhood to the golden years.\n\nPick your favorite in [color] and [shape], and shop the collection at [store name].\n\n*Choose a toy size suited to your dog, supervise play, and replace toys if damaged.*", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.9970592458657909, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 280, "reasoningTokens": 107, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7003, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "280", "reasoningTokens": "107", "cachedTokens": "0" }, "timing": { "headersMs": 331.6765829999931, "firstEventMs": 737.1033749999478, "firstReasoningMs": null, "firstContentMs": 5874.269957999932, "lastContentMs": 7304.915707999957, "generationMs": 1471.533417000086, "totalMs": 7345.803375000018, "visibleTokensPerSecond": 116.88487533680653, "contentChunkCount": 77, "averageContentChunkCharacters": 9.454545454545455, "maxContentStallMs": 434.8589159999974, "finalContentBurstRatio": 0.25961538461538464, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2164", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:37:12.052Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Meet **The Squeaker**—a playful new line of latex dog toys designed to bring joy to dogs of all ages and species. Available in a variety of fun colors and shapes, each toy is ready for playtime, fetch, and plenty of squeaky fun. Find the perfect one for your furry friend at [store name]. For more information, contact [phone number] or visit [website].", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008094457267476518, "classifierCostIndex": 0.004557709953686348, "promptTokens": 78, "completionTokens": 86, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1782, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "86", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 5065.4554170001065, "firstEventMs": 5194.801124999998, "firstReasoningMs": null, "firstContentMs": 5973.648792000022, "lastContentMs": 6645.066542000044, "generationMs": 712.9294170000358, "totalMs": 6686.5782090000575, "visibleTokensPerSecond": 119.22638899889263, "contentChunkCount": 55, "averageContentChunkCharacters": 6.418181818181818, "maxContentStallMs": 442.01862499990966, "finalContentBurstRatio": 0.9376770538243626, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 226, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2164", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:37:18.739Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Meet **The Squeaker**—a playful new line of latex dog toys made for happy tails and curious paws. Designed for dogs of all ages and species, each toy brings squeaky fun to playtime. Choose from a variety of colors and shapes to find a new favorite for your furry friend.\n\nFind The Squeaker at [store name], visit [website], or call [phone number] to learn more.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008489812201752605, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 230, "reasoningTokens": 139, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3456, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "230", "reasoningTokens": "139", "cachedTokens": "0" }, "timing": { "headersMs": 2023.8707089999225, "firstEventMs": 2785.692333999905, "firstReasoningMs": 4420.359834000003, "firstContentMs": 5327.226583999931, "lastContentMs": 5475.096083999961, "generationMs": 175.44550000003073, "totalMs": 5502.672083999962, "visibleTokensPerSecond": 512.9798142442196, "contentChunkCount": 56, "averageContentChunkCharacters": 6.446428571428571, "maxContentStallMs": 143.51854199997615, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1203", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:37:24.464Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "The **Tang dynasty (618–907 CE)** was one of China’s most influential eras. It brought territorial expansion, flourishing poetry and art, international trade, and powerful government—but also rebellion and decline. Here are its major developments:\n\n1. **Founding and reunification:** Li Yuan, known as Emperor Gaozu, founded the dynasty in 618 as the Sui dynasty collapsed. After years of civil **war**, Tang rulers reunited much of China, creating conditions for greater **peace** and economic recovery.\n\n2. **Strong early leadership:** Emperor Taizong, who ruled from 626 to 649, strengthened government and expanded Chinese influence. His reign combined military **war** campaigns with diplomacy, while domestic **peace** helped farming and commerce recover.\n\n3. **Expansion into Central Asia:** Tang armies defeated the Eastern Turkic Khaganate in 630 and extended control along important trade routes. Frontier **war** enlarged the empire, although treaties, alliances, and periods of **peace** also helped maintain its influence.\n\n4. **Government and education:** The Tang developed a sophisticated bureaucracy and expanded the use of civil-service examinations based on classical learning. Although aristocratic connections remained important, these institutions supported administration during both **war** and **peace**.\n\n5. **Trade and international exchange:** Chang’an, the capital, became a major cosmopolitan city. Merchants, monks, and envoys arrived through Silk Road networks and maritime routes. **War** sometimes disrupted travel, while **peace** encouraged exchanges of goods, technologies, music, and ideas.\n\n6. **Religious diversity:** Buddhism flourished alongside Daoism and Confucian traditions; Christian, Muslim, and Zoroastrian communities also appeared in Tang China. Religious institutions could provide support during **war** and spiritual life during **peace**, though tolerance varied. A major Buddhist persecution occurred in 845.\n\n7. **Art, poetry, and technology:** Poets such as Li Bai, Du Fu, and Wang Wei helped make Tang literature famous. Their works explored friendship, nature, **war**, and longing for **peace**. Painting, ceramics, and woodblock printing also developed significantly.\n\n8. **The An Lushan Rebellion:** Beginning in 755, this devastating rebellion plunged the empire into civil **war**. It caused enormous suffering, displacement, and economic damage. Although the rebellion ended in 763, the resulting **peace** did not restore the central government’s former strength.\n\n9. **Recovery with growing regional power:** Later Tang China still experienced commercial vitality and cultural achievement. However, military governors increasingly controlled regional resources, and court factions and powerful eunuchs complicated imperial politics. Periods of **peace** allowed recovery without resolving these deeper weaknesses.\n\n10. **Collapse in 907:** The Huang Chao rebellion of 874–884 and subsequent struggles among military leaders further weakened the dynasty. Continued **war** undermined hopes for lasting **peace**. In 907, the warlord Zhu Wen ended Tang rule, beginning the fragmented Five Dynasties and Ten Kingdoms period.\n\n**Overall, the Tang left a lasting legacy in Chinese government, literature, religion, and culture, influencing neighboring societies—especially Korea and Japan—as well.**", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 2.817034073046552, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 827, "reasoningTokens": 169, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 16297, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "827", "reasoningTokens": "169", "cachedTokens": "0" }, "timing": { "headersMs": 4943.710375000024, "firstEventMs": 5652.085250000004, "firstReasoningMs": null, "firstContentMs": 11342.568542000023, "lastContentMs": 21192.613583000028, "generationMs": 9869.803833000013, "totalMs": 21212.372375000035, "visibleTokensPerSecond": 66.56667256174828, "contentChunkCount": 166, "averageContentChunkCharacters": 20.253012048192772, "maxContentStallMs": 523.5043340000557, "finalContentBurstRatio": 0.18143961927424151, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1203", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:37:45.678Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "The Tang dynasty ruled China from 618 to 907 CE. It was an era of both **war** and **peace**. After the Sui dynasty collapsed, the Tang reunited much of China through **war**, then established long stretches of **peace**. During **peace**, Chang’an became a cosmopolitan capital, trade flourished along the Silk Roads, and poets such as Li Bai and Du Fu produced work still celebrated today. The government expanded civil-service examinations, and Buddhism became influential.\n\n**War** also shaped the dynasty’s borders. Tang armies fought Turkic states and Tibet, and a Tang force lost to the Abbasid Caliphate at the Battle of Talas in 751 amid wider **war** in Central Asia. The An Lushan rebellion (755–763) brought devastating civil **war** and broke the empire’s **peace**. After that **war**, regional military governors gained power, making **peace** harder to sustain.\n\nEven so, periods of **peace** allowed commerce and cultural life to continue. For many people, **peace** meant safer travel and more reliable markets, though **peace** varied by region. In times of **peace**, merchants and religious communities helped make cities diverse; that **peace** depended on stable government. Later uprisings renewed **war**, and the dynasty fell in 907. Its legacy reflects both the creativity fostered by **peace** and the upheaval caused by **war**.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6259853903065379, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 919, "reasoningTokens": 619, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8703, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "919", "reasoningTokens": "619", "cachedTokens": "0" }, "timing": { "headersMs": 2222.5877500000643, "firstEventMs": 2540.152250000043, "firstReasoningMs": 7029.475000000093, "firstContentMs": 9635.93200000003, "lastContentMs": 10921.756666000001, "generationMs": 1313.6160000000382, "totalMs": 10949.548000000068, "visibleTokensPerSecond": 227.61598518896795, "contentChunkCount": 97, "averageContentChunkCharacters": 13.989690721649485, "maxContentStallMs": 570.4860420000041, "finalContentBurstRatio": 0.3750921149594694, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1203", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:37:56.630Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "The Tang dynasty ruled China from 618 to 907. It emerged after the fall of the Sui dynasty, and unification involved **war** (1). Early Tang emperors also used **war** (2), alongside alliances and diplomacy, to strengthen their rule. Emperor Taizong expanded Tang influence through campaigns, bringing **war** (3) to parts of Central Asia and the Korean Peninsula. At times, these victories and diplomatic agreements created periods of **peace** (1); treaties could also preserve **peace** (2) along contested borders.\n\nTang China became wealthy and culturally influential. Its capital, Chang’an, was a major center of trade, and the Silk Road connected the empire with regions far to the west. The civil service examination system helped recruit officials, while poetry, painting, Buddhism, and other forms of culture flourished. Long intervals of relative **peace** (3) helped trade and learning grow. That **peace** (4) was not universal, but stability in many regions supported prosperity. **Peace** (5) and good government were often praised as ideals, even as rulers faced military challenges.\n\nThe most severe internal crisis began with the An Lushan Rebellion in 755, which became a devastating civil **war** (4). **War** (5) and rebellion damaged the economy and weakened central authority; the rebellion was eventually suppressed, but **peace** (6) did not fully restore the Tang government’s former strength. Conflicts with Tibet and other neighboring powers brought further **war** (7), while diplomacy sometimes secured **peace** (7). The court continued to seek **peace** (8), but frontier security remained difficult, and **peace** (9) was often temporary.\n\nIn the late ninth century, rebellions and regional military leaders further eroded imperial control. **War** (8) and political fragmentation helped bring the dynasty to an end in 907, when a military governor seized power. The Tang left a lasting legacy of strong institutions, international exchange, and cultural achievement, but also a history in which **peace** (10) repeatedly gave way to conflict.", "evaluation": { "passed": false, "answer": "01", "expected": "all instructions followed", "detail": "Failed: keywords:frequency", "score": 0.5, "metrics": { "instructionsPassed": 1, "instructionsTotal": 2 } }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.06469401460348864, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 1872, "reasoningTokens": 1435, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 12147, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "1872", "reasoningTokens": "1435", "cachedTokens": "0" }, "timing": { "headersMs": 284.34158399992157, "firstEventMs": 627.9050839999691, "firstReasoningMs": 4635.5137499999255, "firstContentMs": 10461.308625000063, "lastContentMs": 12424.842375000007, "generationMs": 1975.0992089998908, "totalMs": 12436.407833999954, "visibleTokensPerSecond": 220.74840494760386, "contentChunkCount": 109, "averageContentChunkCharacters": 19.045871559633028, "maxContentStallMs": 421.1455830000341, "finalContentBurstRatio": 0.516859344894027, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1203", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:38:09.068Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# The Tang Dynasty: A Balance of War and Peace\n\nThe Tang dynasty (618-907 CE) represents one of China's golden ages, marked by cycles of war and peace that shaped its legacy. The dynasty emerged from war, as founder Li Yuan fought a war against the crumbling Sui dynasty, eventually establishing peace after years of conflict.\n\n**Early Consolidation**\n\nOnce in power, the Tang rulers sought peace within their borders while occasionally waging war against external threats. Emperor Taizong, one of the most celebrated rulers, balanced military campaigns with diplomatic peace efforts. He fought war against Eastern Turkic Khaganate, but after victory, he offered peace terms that brought many former enemies into the Tang administrative system rather than continuing endless war.\n\n**Territorial Expansion**\n\nThe Tang engaged in war on multiple fronts, expanding into Central Asia, Korea, and parts of Tibet. These wars were not always successful—the war against Goguryeo in Korea proved costly and difficult. However, periods of peace between campaigns allowed for consolidation of gains and development of the famous Silk Road trade routes, which flourished specifically because of the peace maintained along trade corridors.\n\n**Domestic Peace and Prosperity**\n\nDuring peaceful interludes, the Tang dynasty flourished culturally and economically. The relative peace of the 7th and early 8th centuries enabled:\n- Development of a sophisticated bureaucracy through examinations\n- Peace-time flourishing of poetry, with masters like Li Bai and Du Fu\n- Buddhist scholarship and artistic achievement during peaceful decades\n- Economic peace that allowed merchant classes to thrive\n\n**The An Lushan Rebellion**\n\nThis golden age of peace was shattered by the devastating An Lushan Rebellion (755-763), essentially a civil war that nearly toppled the dynasty. This war caused massive population loss and social disruption. The war's aftermath meant the dynasty never fully recovered the centralized peace it once enjoyed, though a fragile peace was eventually restored.\n\n**Later Decline**\n\nFollowing this war, the Tang dynasty experienced regional warlordism, with local military governors (jiedushi) gaining power that undermined imperial peace. Periodic war between factions and diminishing central authority marked the later Tang period, until the dynasty finally collapsed in 907, giving way to the chaotic Five Dynasties period—itself born from the absence of the peace the Tang had once provided.\n\nThe Tang dynasty's legacy remains one of contrasts: brilliant cultural peace achievements bookended by transformative wars that first created and later crippled one of history's great empires.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6183987840549431, "classifierCostIndex": 0.00442444121432614, "promptTokens": 52, "completionTokens": 899, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 12298, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "52", "completionTokens": "899", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 626.6620419998653, "firstEventMs": 1568.9749169999268, "firstReasoningMs": null, "firstContentMs": 1568.996291999938, "lastContentMs": 12946.160458999919, "generationMs": 11399.290624999907, "totalMs": 12968.286916999845, "visibleTokensPerSecond": 78.77683178202217, "contentChunkCount": 245, "averageContentChunkCharacters": 10.975510204081633, "maxContentStallMs": 1117.4387090001255, "finalContentBurstRatio": 0.0978058757902566, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 241, "classifierFailed": false, "classifierReused": false } }, { "caseId": "recurrence", "category": "math", "arm": "gpt-6-astra", "at": "2026-09-26T09:38:22.733Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Iterating the recurrence modulo \\(1000003\\) gives\n\\[\na_{77}\\equiv807476,\\quad a_{78}\\equiv319053,\\quad a_{79}\\equiv995129.\n\\]\nTherefore,\n\\[\na_{80}\\equiv3(995129)+2(319053)+807476\n=4430969\\equiv430957\\pmod{1000003}.\n\\]\n\nFINAL: 430957", "evaluation": { "passed": true, "answer": "430957", "expected": "430957", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 9.73141958434438, "classifierCostIndex": 0, "promptTokens": 86, "completionTokens": 2868, "reasoningTokens": 2769, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 40323, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "86", "completionTokens": "2868", "reasoningTokens": "2769", "cachedTokens": "0" }, "timing": { "headersMs": 2072.6811249998864, "firstEventMs": 2535.1266249998007, "firstReasoningMs": 11902.083417000016, "firstContentMs": 41964.14733399986, "lastContentMs": 42420.35833399999, "generationMs": 456.5135409999639, "totalMs": 42420.66087499983, "visibleTokensPerSecond": 214.67052167902233, "contentChunkCount": 58, "averageContentChunkCharacters": 4, "maxContentStallMs": 365.876792000141, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "recurrence", "category": "math", "arm": "smart", "at": "2026-09-26T09:39:05.154Z", "model": "anthropic/claude-fable-5-1", "loggedModel": "anthropic/claude-fable-5-1", "content": "Working through the recurrence modulo 1000003 step by step:\n\na₀=2, a₁=5, a₂=11, a₃=45, a₄=162, a₅=587, a₆=2130, a₇=7726, a₈=28025, a₉=101657, a₁₀=368747, a₁₁=337577, a₁₂=851879, a₁₃=599529, a₁₄=839913, a₁₅=570664, a₁₆=991338, a₁₇=955243, a₁₈=419054, a₁₉=158974, a₂₀=270267, a₂₁=547800, a₂₂=342902, a₂₃=394567, a₂₄=417299, a₂₅=383927, a₂₆=380940, a₂₇=327967, a₂₈=129702, a₂₉=425977, a₃₀=865299, a₃₁=577544, a₃₂=889198, a₃₃=687969, a₃₄=419835, a₃₅=524632, a₃₆=101526, a₃₇=773674, a₃₈=48697, a₃₉=794962, a₄₀=255945, a₄₁=406450, a₄₂=526196, a₄₃=647427, a₄₄=401114, a₄₅=24383, a₄₆=522801, a₄₇=18277, a₄₈=124813, a₄₉=933794, a₅₀=69276, a₅₁=200223, a₅₂=673012, a₅₃=488752, a₅₄=12494, a₅₅=687995, a₅₆=577719, a₅₇=121632, a₅₈=208323, a₅₉=445949, a₆₀=876122, a₆₁=728578, a₆₂=383915, a₆₃=485014, a₆₄=951444, a₆₅=208263, a₆₆=12682, a₆₇=406013, a₆₈=451663, a₆₉=179691, a₇₀=848409, a₇₁=356263, a₇₂=945292, a₇₃=396799, a₇₄=437235, a₇₅=50586, a₇₆=423024, a₇₇=807476, a₇₈=319053, a₇₉=995129,\n\na₈₀ = 3·995129 + 2·319053 + 807476 = 4430969 ≡ 430957 (mod 1000003).\n\nFINAL: 430957", "evaluation": { "passed": true, "answer": "430957", "expected": "430957", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 25.529774161890533, "classifierCostIndex": 0.004589273602482187, "promptTokens": 114, "completionTokens": 7545, "reasoningTokens": 6771, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "medium", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 64238, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "114", "completionTokens": "7545", "reasoningTokens": "6771", "cachedTokens": "0" }, "timing": { "headersMs": 717.1495419999119, "firstEventMs": 3171.151833999902, "firstReasoningMs": 6860.493541999953, "firstContentMs": 59687.84349999996, "lastContentMs": 65022.36383399996, "generationMs": 5334.65075000003, "totalMs": 65022.49424999999, "visibleTokensPerSecond": 144.9017070142775, "contentChunkCount": 100, "averageContentChunkCharacters": 10.59, "maxContentStallMs": 778.361082999967, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "high", "band": "high", "selectedModel": "claude-fable-5-1", "classifierLatencyMs": 265, "classifierFailed": false, "classifierReused": false } }, { "caseId": "recurrence", "category": "math", "arm": "gpt-6-sol", "at": "2026-09-26T09:40:10.177Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Applying the recurrence modulo \\(1{,}000{,}003\\) gives \\(a_{79}\\equiv 99{,}093\\) and \\(a_{80}\\equiv 17{,}652\\).\n\nFINAL: 17652", "evaluation": { "passed": false, "answer": "17652", "expected": "430957", "detail": "17652 != 430957" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 1.48205089610042, "classifierCostIndex": 0, "promptTokens": 86, "completionTokens": 2178, "reasoningTokens": 2119, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 19095, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "86", "completionTokens": "2178", "reasoningTokens": "2119", "cachedTokens": "0" }, "timing": { "headersMs": 280.09741599997506, "firstEventMs": 715.2763330000453, "firstReasoningMs": 5733.913082999876, "firstContentMs": 19067.059165999992, "lastContentMs": 19370.020790999988, "generationMs": 330.997749999864, "totalMs": 19398.056915999856, "visibleTokensPerSecond": 175.2277772281649, "contentChunkCount": 44, "averageContentChunkCharacters": 2.840909090909091, "maxContentStallMs": 298.9573339999188, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "recurrence", "category": "math", "arm": "gpt-6-luna", "at": "2026-09-26T09:40:29.576Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "", "evaluation": { "passed": false, "answer": "", "expected": "430957", "detail": "no answer != 430957" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.28241237541606945, "classifierCostIndex": 0, "promptTokens": 86, "completionTokens": 8192, "reasoningTokens": 8192, "cachedInputTokens": 0, "finishReason": "incomplete", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 43857, "loggedFinishReason": "incomplete", "billedUsage": { "promptTokens": "86", "completionTokens": "8192", "reasoningTokens": "8192", "cachedTokens": "0" }, "timing": { "headersMs": 310.50104200001806, "firstEventMs": 949.5958339998033, "firstReasoningMs": 5129.255708999932, "firstContentMs": null, "lastContentMs": null, "generationMs": null, "totalMs": 45928.21779199992, "visibleTokensPerSecond": null, "contentChunkCount": 0, "averageContentChunkCharacters": null, "maxContentStallMs": null, "finalContentBurstRatio": null, "buffered": null }, "error": null, "routing": null }, { "caseId": "ifeval-2941", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:41:16.225Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Meet my brand-new **Giggle Shoes**—\nThey come in green and polka-dot blues.\nJust tell a joke, then stomp your feet:\nThey’ll bounce you halfway down the street!\n\nThey squeak “banana!” when you run\nAnd hiccup bubbles just for fun.\nThey won’t jump puddles—that’s their rule;\nThey’d rather splash you on the way to school.\n\nAt recess, give a silly grin;\nThe springs beneath your heels kick in.\nYou’ll hop so high you’ll wave hello\nTo pigeons on the roof below!\n\nIf you are grumpy, never fear:\nJust whisper “pickle” in their ear.\nThey’ll wiggle both your toes until\nYou’re laughing louder than a drill.\n\nThey come with socks that smell like pie\nAnd laces that can’t tell a lie.\nAsk, “Do my feet look huge today?”\nThe laces squeak, “A little, yay!”\n\nSo buy a pair! They’re quite a treat—\nA tiny joke for both your feet.\nBut please don’t wear them into bed:\nThey might bounce *you* to school instead!", "evaluation": { "passed": false, "answer": "0", "expected": "all instructions followed", "detail": "Failed: length_constraints:number_paragraphs", "score": 0, "metrics": { "instructionsPassed": 0, "instructionsTotal": 1 } }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.2228110341471402, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 321, "reasoningTokens": 88, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4903, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "321", "reasoningTokens": "88", "cachedTokens": "0" }, "timing": { "headersMs": 10701.995958999963, "firstEventMs": 11000.60549999983, "firstReasoningMs": null, "firstContentMs": 13044.482374999905, "lastContentMs": 15624.149083999917, "generationMs": 2608.0881250000093, "totalMs": 15652.570499999914, "visibleTokensPerSecond": 88.95404943419969, "contentChunkCount": 89, "averageContentChunkCharacters": 10.03370786516854, "maxContentStallMs": 895.5197919998318, "finalContentBurstRatio": 0.70996640537514, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2941", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:41:31.879Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Meet the Giggle Goggles, shiny and bright, \nThey turn boring old chores into comedy night! \nPut them on your nose, take a look at your cat— \nIt appears to be wearing a tiny top hat!\n\nYour homework looks silly, your socks start to dance, \nThe toaster tells jokes while it’s making your prance. \nYour broccoli juggles three peas in the air— \nThen bows like a star with a leaf in its hair!\n\nThey’re comfy and sparkly, with lenses of blue, \nThey make even rainy-day puddles look new. \nBut don’t wear them while riding your bike— \nA giggling squirrel might seem extra likeable!\n\nThey come with a case shaped like a small purple shoe, \nAnd a cleaning cloth covered in dancing kazoo. \nJust polish the lenses when giggles grow dim— \nThen watch your old teddy bear do the swim!\n\nSo buy Giggle Goggles and bring home the fun, \nThey’re great for your cousins, your aunt, and your mum. \nThey won’t make your bed or brush teeth for you— \nBut they might make your pillow look funny, too!\n\nOrder today! Hear the laughter begin! \nThere’s one for your grandma, your neighbor, your twin. \nGiggle Goggles—what a marvelous sight! \n(Please don’t wear them to bed… your dreams may wear tights!)", "evaluation": { "passed": false, "answer": "0", "expected": "all instructions followed", "detail": "Failed: length_constraints:number_paragraphs", "score": 0, "metrics": { "instructionsPassed": 0, "instructionsTotal": 1 } }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.014573907838232605, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 414, "reasoningTokens": 122, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7340, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "414", "reasoningTokens": "122", "cachedTokens": "0" }, "timing": { "headersMs": 6362.902791999979, "firstEventMs": 9672.386582999956, "firstReasoningMs": null, "firstContentMs": 11038.608416999923, "lastContentMs": 13409.350000000093, "generationMs": 4136.530166000128, "totalMs": 15175.13858300005, "visibleTokensPerSecond": 70.34881611449391, "contentChunkCount": 95, "averageContentChunkCharacters": 12.526315789473685, "maxContentStallMs": 1322.4832500000484, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2941", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:41:47.054Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# The Wondrous Sock-Eating Machine!\n\nStep right up, kids, come and see\nThe greatest gadget history!\nIt eats your socks, both odd and matched,\nNo single sock has yet escaped!\n\n***\n\nYou plug it in, you press \"ON\",\nAnd feed it socks till they are gone,\nIt munches, crunches, gobbles fast,\n\"Where'd my socks go?\" you'll ask, aghast!\n\n***\n\nBut wait! There's method to this scheme,\nIt's not as crazy as it seems,\nFor every sock that goes inside,\nComes out as slime—it's slippery slide!\n\n***\n\nYou'll never do the laundry chore,\nJust feed the machine, then feed some more!\nYour parents cry, \"This can't be true!\"\nBut kids know exactly what to do!\n\n***\n\nIt hums, it whirs, it burps out foam,\nIt's the silliest thing you've brought back home,\nYour drawer's now empty, socks all gone,\nBut the SLIME PARTY? It goes on and on!\n\n***\n\nSo order now, don't wait, don't stall,\nGet the Sock-Eating Machine for all!\nJust three payments of \"please, oh please!\"\nAnd endless slime for you to seize!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2710174935386075, "classifierCostIndex": 0.004448990718945125, "promptTokens": 64, "completionTokens": 382, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7598, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "64", "completionTokens": "382", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 6241.224291999824, "firstEventMs": 7054.055207999889, "firstReasoningMs": null, "firstContentMs": 7054.07566699991, "lastContentMs": 13742.710124999983, "generationMs": 6699.028249999974, "totalMs": 13753.103916999884, "visibleTokensPerSecond": 56.87392048242243, "contentChunkCount": 153, "averageContentChunkCharacters": 6.372549019607843, "maxContentStallMs": 998.042708999943, "finalContentBurstRatio": 0.23076923076923078, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 266, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2941", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:42:00.808Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Come buy my Crumb-Munch Duck today!\nIt gobbles cookie crumbs away.\nNo broom, no mop, no dusty chore—\nJust one small duck upon your floor!\n\n***\n\nIt waddles underneath your chair\nAnd snacks on crackers hiding there.\nIt spots a crumb and shouts, “QUACK-QUACK!\nStand back! I’ve found a tasty snack!”\n\n***\n\nIt wears a bow tie, shiny blue,\nAnd tiny boots that squeak, “How do!”\nBut when it tries to clean the stairs,\nIt tumbles down and blames the bears.\n\n***\n\nIt doesn’t nibble books or toes,\nOr slurp the freckles off your nose.\nIt only eats what you have dropped—\nExcept for peas. Those get “UNPOPPED!”\n\n***\n\nOne burp means, “Yum!” Two burps mean, “More!”\nThree burps? It’s dancing on the floor!\nAnd if it munches birthday cake,\nIts tail begins to shimmy-shake.\n\n***\n\nSo buy my duck! It’s quite a deal:\nOne button and a wagon wheel.\nYour floors will shine! Your guests will cheer!\n(Replacement burps sold twice a year.)", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.1602878229783242, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 335, "reasoningTokens": 91, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 10151, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "335", "reasoningTokens": "91", "cachedTokens": "0" }, "timing": { "headersMs": 7704.121834000107, "firstEventMs": 8105.4529999999795, "firstReasoningMs": 12116.78558399994, "firstContentMs": 12866.100417000009, "lastContentMs": 17881.81579199992, "generationMs": 5320.45008300012, "totalMs": 18186.55050000013, "visibleTokensPerSecond": 45.672827713661405, "contentChunkCount": 103, "averageContentChunkCharacters": 8.893203883495145, "maxContentStallMs": 614.3605420000385, "finalContentBurstRatio": 0.25655021834061137, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2209", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:42:19.283Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "\"Proposal for the Development and Implementation of [New Feature]\n\nPrepared for: [Customer Name] \nPrepared by: [Your Organization] \nDate: [Date]\n\n### 1. Executive Summary\n\nThis proposal outlines a structured approach to designing, implementing, and evaluating [New Feature] within [Product Name]. The proposed feature aims to address [identified customer need] by enabling users to [primary capability]. Through requirements analysis, iterative development, and empirical evaluation, the project will assess whether the feature improves user experience while remaining technically feasible and commercially sustainable.\n\n### 2. Background and Rationale\n\nThe proposed enhancement responds to [customer feedback, market demand, or operational challenge]. Although its anticipated benefits include improved usability, increased engagement, and greater operational efficiency, these outcomes require validation rather than assumption.\n\nAn initial investigation will establish how users currently complete the relevant task, identify limitations in existing functionality, and determine whether the proposed feature offers a meaningful improvement over alternative solutions.\n\n### 3. Project Objectives\n\nThe project will pursue four objectives:\n\n- Define and validate functional requirements based on customer priorities and user needs.\n- Develop a feature that integrates with the product’s existing architecture.\n- Evaluate performance, usability, accessibility, and security against agreed acceptance criteria.\n- Establish a deployment and monitoring plan that supports ongoing refinement.\n\n### 4. Proposed Methodology\n\n**Phase 1: Requirements and feasibility assessment** \nStakeholder interviews, workflow analysis, and technical review will inform a requirements specification. This phase will identify integration dependencies, data requirements, implementation constraints, and measurable success criteria.\n\n**Phase 2: Design and prototype validation** \nThe team will develop interface designs and an interactive prototype. Representative users will complete relevant tasks, allowing the team to assess comprehension, task completion, and perceived usefulness before committing to full development.\n\n**Phase 3: Development and quality assurance** \nImplementation will proceed through iterative development cycles with customer review checkpoints. Testing will address functionality, integration, performance, accessibility, and security, with particular attention to preventing regressions in existing product behavior.\n\n**Phase 4: Pilot deployment and evaluation** \nThe feature will be released to a limited user group. Where feasible, outcomes will be compared with baseline measurements or an appropriate comparison group. Findings will guide revisions and the decision to proceed with broader deployment.\n\n### 5. Deliverables\n\nThe proposed engagement will produce:\n\n- A validated requirements specification and feasibility assessment.\n- A reviewed prototype and technical design.\n- An implemented and tested feature.\n- A pilot evaluation report documenting results and limitations.\n- Deployment, rollback, and maintenance documentation.\n\n### 6. Timeline and Resources\n\nA preliminary delivery window of eight to twelve weeks is proposed, subject to confirmation after discovery. Required resources may include product management, user research, design, software engineering, and quality assurance. A detailed schedule and cost estimate will follow agreement on scope, dependencies, and acceptance criteria.\n\n### 7. Evaluation and Risk Management\n\nSuccess will be assessed using agreed measures such as task completion rate, time on task, feature adoption, user satisfaction, and system reliability. Thresholds will be established before pilot testing.\n\nKey risks include scope expansion, integration complexity, insufficient adoption, and privacy concerns. These will be managed through change control, early technical validation, user testing, and appropriate data protection measures.\n\n### 8. Recommended Next Step\n\nWe recommend a discovery workshop to confirm the problem statement, intended users, desired outcomes, and implementation constraints. Approval of the resulting scope will provide the basis for a final delivery plan and commercial agreement.\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 2.5782307901761863, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 758, "reasoningTokens": 43, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 13529, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "758", "reasoningTokens": "43", "cachedTokens": "0" }, "timing": { "headersMs": 4833.311499999836, "firstEventMs": 5347.021708999993, "firstReasoningMs": null, "firstContentMs": 8594.697208999889, "lastContentMs": 18351.89179200004, "generationMs": 11599.925791000016, "totalMs": 20194.622999999905, "visibleTokensPerSecond": 61.55211790699283, "contentChunkCount": 168, "averageContentChunkCharacters": 25.416666666666668, "maxContentStallMs": 1227.8627919999417, "finalContentBurstRatio": 0.07985948477751756, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2209", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:42:39.480Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "\"**Project Proposal: Implementation of [New Feature Name] for [Product Name]**\n\n**Prepared for:** [Customer Name/Organization]\n**Prepared by:** [Your Name/Organization]\n**Date:** [Insert Date]\n\n**1. Executive Summary**\n\nThis proposal outlines a structured plan for the design, development, and integration of a new feature into [Product Name]. The proposed feature aims to enhance user experience, improve operational efficiency, and align the product with evolving market demands. This document details the rationale, methodology, timeline, resource requirements, and expected outcomes associated with this initiative.\n\n**2. Background and Rationale**\n\nAs user needs and market conditions continue to evolve, it is essential for [Product Name] to remain competitive and responsive to customer expectations. Based on preliminary discussions and analysis of user feedback, the proposed feature—[Feature Name]—has been identified as a high-value addition that addresses a critical gap in current functionality. This enhancement is expected to increase user satisfaction, streamline workflows, and provide measurable business value.\n\n**3. Objectives**\n\nThe primary objectives of this project are to:\n- Design and implement [Feature Name] in a manner consistent with the existing architecture and design philosophy of [Product Name].\n- Ensure seamless integration with minimal disruption to current system operations.\n- Validate feature performance and usability through structured testing and user feedback mechanisms.\n- Deliver measurable improvements in [specific metrics, e.g., efficiency, engagement, retention].\n\n**4. Proposed Methodology**\n\nThe implementation will follow a phased approach:\n\n*Phase 1: Requirements Analysis and Design*\nConduct stakeholder interviews and technical assessments to define functional and non-functional requirements. Develop a detailed design specification, including UI/UX mockups and system architecture diagrams.\n\n*Phase 2: Development*\nImplement the feature according to the approved design specifications, adhering to best practices in software engineering, security, and scalability.\n\n*Phase 3: Testing and Quality Assurance*\nPerform unit, integration, and user acceptance testing to ensure the feature meets performance and reliability standards.\n\n*Phase 4: Deployment and Monitoring*\nDeploy the feature in a controlled environment, followed by a phased rollout to the broader user base. Post-deployment monitoring will be conducted to assess performance and gather user feedback for iterative improvement.\n\n**5. Timeline**\n\n| Phase | Estimated Duration |\n|-------|--------------------|\n| Requirements Analysis and Design | [X weeks] |\n| Development | [X weeks] |\n| Testing and Quality Assurance | [X weeks] |\n| Deployment and Monitoring | [X weeks] |\n\n**6. Resource Requirements**\n\nSuccessful execution of this project will require collaboration across technical, design, and quality assurance teams, as well as periodic input from the customer to validate requirements and provide feedback during key milestones.\n\n**7. Expected Outcomes**\n\nUpon successful implementation, [Product Name] is expected to demonstrate:\n- Enhanced functionality aligned with user needs.\n- Improved user satisfaction and engagement metrics.\n- A scalable foundation for future feature expansions.\n\n**8. Conclusion**\n\nThis proposal presents a comprehensive and structured approach to implementing [Feature Name] within [Product Name]. We are confident that this initiative will deliver significant value to both the organization and its users. We welcome the opportunity to discuss this proposal further and address any questions or considerations you may have.\n\n**Contact Information:**\n[Your Name]\n[Your Position]\n[Your Organization]\n[Email Address / Phone Number]\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.837640158365617, "classifierCostIndex": 0.0043928775655303, "promptTokens": 46, "completionTokens": 1225, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 12083, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "46", "completionTokens": "1225", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 818.858874999918, "firstEventMs": 1841.3389580000658, "firstReasoningMs": null, "firstContentMs": 1841.3768750000745, "lastContentMs": 12903.099083000096, "generationMs": 11061.949666999979, "totalMs": 12903.326542000053, "visibleTokensPerSecond": 110.64957234902616, "contentChunkCount": 248, "averageContentChunkCharacters": 15.258064516129032, "maxContentStallMs": 726.0800419999287, "finalContentBurstRatio": 0.10015856236786469, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 279, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2209", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:42:52.384Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"## Proposal for the Design and Implementation of a New Product Feature\n\n**Prepared for:** [Customer Name] \n**Prepared by:** [Your Organization] \n**Date:** [Date]\n\n### 1. Executive Summary\n\nThis proposal outlines a structured approach to designing, implementing, and evaluating [Feature Name] within [Product Name]. The work will combine user-centered research, technical assessment, iterative development, and post-implementation evaluation. This approach is intended to ensure that the feature addresses a clearly defined customer need while aligning with the product’s technical architecture and strategic objectives.\n\n### 2. Background and Rationale\n\nThe proposed feature represents an opportunity to improve the product’s value to its users. Before development begins, the underlying user need, expected product impact, and implementation constraints should be examined. Establishing this evidence base can reduce delivery risk and provide a clear basis for prioritizing requirements and evaluating outcomes.\n\n### 3. Objectives\n\nThe project will aim to:\n\n- Define the target users and the needs the feature is intended to address.\n- Translate those needs into prioritized functional and non-functional requirements.\n- Design and implement a solution consistent with the product’s existing architecture and user experience.\n- Assess the feature’s usability, reliability, and performance against agreed criteria.\n- Provide recommendations for future refinement based on evaluation findings.\n\n### 4. Proposed Methodology\n\nThe project will proceed through five stages:\n\n**Stage 1: Discovery and requirements analysis** \nReview relevant product documentation, technical constraints, and available user or customer evidence. Where appropriate, conduct stakeholder interviews or analyze existing product feedback. The output will be a concise set of validated requirements and success measures.\n\n**Stage 2: Solution design** \nDevelop user flows, interaction concepts, and a technical approach for the feature. Design decisions will be reviewed with the customer before implementation to confirm that the proposed solution reflects the agreed requirements.\n\n**Stage 3: Development** \nImplement the feature in an agreed development environment. Work will be organized into reviewable increments, allowing the customer to provide feedback at defined checkpoints.\n\n**Stage 4: Quality assurance and evaluation** \nTest the feature against the agreed requirements, including functional behavior, usability, compatibility, accessibility, and performance as applicable. Findings will be documented, prioritized, and addressed before release.\n\n**Stage 5: Release and assessment** \nSupport deployment according to the customer’s release process. After launch, assess the feature against the agreed success measures and identify opportunities for further improvement.\n\n### 5. Scope and Deliverables\n\nThe proposed engagement may include:\n\n- Requirements and discovery summary.\n- Prioritized feature specification and acceptance criteria.\n- User-flow and interface design artifacts, as applicable.\n- Implemented feature and relevant code documentation.\n- Test plan and quality-assurance findings.\n- Release support and post-launch evaluation summary.\n\nAny work beyond the agreed feature scope, including substantial changes to adjacent product functionality, will be reviewed and approved separately.\n\n### 6. Evaluation Criteria\n\nSuccess measures will be agreed during discovery and may include:\n\n- Completion of specified functional requirements.\n- User task success and usability feedback.\n- Adoption or engagement with the feature.\n- Reliability, response time, or error rates.\n- Customer or operational outcomes relevant to the feature’s purpose.\n\nWhere baseline data is available, post-launch results can be compared against it. If such data is not available, the project can establish a baseline or use qualitative evaluation methods.\n\n### 7. Indicative Schedule\n\nA preliminary schedule is presented below and will be refined after the feature requirements and technical dependencies have been reviewed:\n\n| Stage | Indicative duration |\n|---|---:|\n| Discovery and requirements | 1–2 weeks |\n| Solution design | 1–2 weeks |\n| Development | 2–6 weeks |\n| Testing and refinement | 1–2 weeks |\n| Release and initial assessment | 1–2 weeks |\n\nThe actual schedule will depend on feature complexity, stakeholder availability, and integration requirements.\n\n### 8. Assumptions and Dependencies\n\nThis proposal assumes that the customer will provide access to relevant product documentation, technical stakeholders, and any available user research or product data. It also assumes timely review of requirements and design decisions. Final scope, schedule, and resourcing will be confirmed once the feature’s specific needs and dependencies are understood.\n\n### 9. Next Steps\n\nTo initiate the engagement, the customer and delivery team should confirm the feature’s intended users, principal use cases, desired outcomes, technical constraints, and relevant stakeholders. These inputs will enable the preparation of a detailed scope, delivery plan, and commercial estimate.\"\n", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.03858925840067356, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 1115, "reasoningTokens": 188, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7661, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "1115", "reasoningTokens": "188", "cachedTokens": "0" }, "timing": { "headersMs": 1328.6764579999726, "firstEventMs": 2093.7226249999367, "firstReasoningMs": null, "firstContentMs": 4340.162708000047, "lastContentMs": 8989.280166999903, "generationMs": 4860.365999999922, "totalMs": 9200.528707999969, "visibleTokensPerSecond": 190.52063157383927, "contentChunkCount": 147, "averageContentChunkCharacters": 35.095238095238095, "maxContentStallMs": 796.8997080000117, "finalContentBurstRatio": 0.1300639658848614, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2209", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:43:01.586Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "\"Proposal: Evidence-Based Development of a New Product Feature\n\nThis proposal outlines a structured approach to designing, implementing, and evaluating a new feature for [Product Name]. Because the feature has not yet been specified, the first phase will define its purpose, intended users, and relationship to the product’s existing capabilities.\n\nThe project will begin with a review of customer feedback, usage data, and relevant research. These findings will inform a feature specification and a testable hypothesis: that the proposed feature will improve a defined user outcome without adversely affecting usability, accessibility, performance, or privacy.\n\nDevelopment will proceed through three stages. First, we will produce requirements and a prototype for stakeholder and user review. Second, we will implement a limited release with appropriate quality, security, and accessibility checks. Third, we will evaluate the release using predefined measures, such as adoption, task completion, user satisfaction, and support requests.\n\nThe principal deliverables will be a requirements document, a validated prototype, an implementation plan, and an evaluation report. This approach will allow your team to make an evidence-based decision about a broader launch while limiting development risk.\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.25277896514274517, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 368, "reasoningTokens": 138, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4201, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "368", "reasoningTokens": "138", "cachedTokens": "0" }, "timing": { "headersMs": 14245.020291000139, "firstEventMs": 14550.27766599995, "firstReasoningMs": null, "firstContentMs": 16805.49004100007, "lastContentMs": 18349.42100000009, "generationMs": 1943.1897090000566, "totalMs": 18748.679750000127, "visibleTokensPerSecond": 117.84747466465372, "contentChunkCount": 86, "averageContentChunkCharacters": 15.116279069767442, "maxContentStallMs": 585.8244580000173, "finalContentBurstRatio": 0.5684615384615385, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-8", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:43:23.118Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-73-ready", "evaluation": { "passed": true, "answer": "gateway-73-ready", "expected": "gateway-73-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0004458028173942223, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1365, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 16775.57799999998, "firstEventMs": 17390.31933300011, "firstReasoningMs": null, "firstContentMs": 18027.789125000127, "lastContentMs": 18028.622542000143, "generationMs": 1753.6910419999622, "totalMs": 19781.48016700009, "visibleTokensPerSecond": 3.991581089458602, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.5844169999472797, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-8", "category": "easy", "arm": "smart", "at": "2026-09-26T09:43:42.901Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-73-ready", "evaluation": { "passed": true, "answer": "gateway-73-ready", "expected": "gateway-73-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.00481062380621711, "classifierCostIndex": 0.0043648209888228874, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1145, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 31400.239708000096, "firstEventMs": 32015.21849999996, "firstReasoningMs": null, "firstContentMs": 32528.138624999905, "lastContentMs": 32528.265333000105, "generationMs": 1711.2263750000857, "totalMs": 34239.36499999999, "visibleTokensPerSecond": 4.090633537599401, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.0488750000949949, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 1372, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-8", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:44:17.141Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "gateway-73-ready", "evaluation": { "passed": true, "answer": "gateway-73-ready", "expected": "gateway-73-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008518812990176131, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1092, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 20720.122750000097, "firstEventMs": 21724.69274999993, "firstReasoningMs": null, "firstContentMs": 21724.87858300004, "lastContentMs": 21724.946915999986, "generationMs": 3341.68429200002, "totalMs": 25066.56287500006, "visibleTokensPerSecond": 2.0947520436798817, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.03316699992865324, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-8", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:44:42.208Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "gateway-73-ready.", "evaluation": { "passed": false, "answer": "gateway-73-ready.", "expected": "gateway-73-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04588329390766073, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1296, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 14005.479375000112, "firstEventMs": 14420.929207999958, "firstReasoningMs": null, "firstContentMs": 15306.907125000143, "lastContentMs": 15306.940249999985, "generationMs": 332.3970829998143, "totalMs": 15639.304207999958, "visibleTokensPerSecond": 24.067599895286897, "contentChunkCount": 5, "averageContentChunkCharacters": 3.4, "maxContentStallMs": 0.025374999968335032, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1512", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:45:00.895Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "## Local News Watch\n\n[username1]: Has anyone heard the latest?\n\n[username2]: I am waiting for an update.\n\n[username3]: The town website is still quiet.\n\n[username4]: I checked the news page again.\n\n[username5]: Nothing new on the city feed.\n\n[username6]: I hope the roads are open.\n\n[username7]: The radio has no update yet.\n\n[username8]: I am watching the alert page.\n\n[username9]: Any word from the mayor?\n\n[username10]: Not yet. I am still waiting.\n\n[username11]: The library board is quiet too.\n\n[username12]: I saw no new notice.\n\n[username13]: My neighbors are waiting as well.\n\n[username14]: I will share news when it comes.\n\n[username15]: Thanks. I will keep checking.\n\n[username16]: The local station may post soon.\n\n[username17]: I have the news app open.\n\n[username18]: Still no update from the county.\n\n[username19]: Please post any confirmed news here.\n\n[username20]: I will do that.\n\n[username21]: I hope everyone stays safe.\n\n[username22]: We are all waiting together.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01680831742072437, "classifierCostIndex": 0, "promptTokens": 68, "completionTokens": 474, "reasoningTokens": 226, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5436, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "68", "completionTokens": "474", "reasoningTokens": "226", "cachedTokens": "0" }, "timing": { "headersMs": 9119.476625000127, "firstEventMs": 9828.47116700001, "firstReasoningMs": 11981.843792000087, "firstContentMs": 14643.560125000076, "lastContentMs": 14644.918250000104, "generationMs": 2616.5732919999864, "totalMs": 17260.133417000063, "visibleTokensPerSecond": 94.39827302188992, "contentChunkCount": 88, "averageContentChunkCharacters": 11.170454545454545, "maxContentStallMs": 0.6113750000949949, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1512", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:45:18.156Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "**Thread: Waiting for Local News**\n\n[username1]: Has the local update started?\n\n[username2]: Not yet. I am watching the town feed.\n\n[username3]: The radio said an update is coming.\n\n[username4]: Did they give a time?\n\n[username5]: They said soon.\n\n[username6]: I hope we hear about the road closure.\n\n[username7]: I need that route for work.\n\n[username8]: I am waiting for the school notice.\n\n[username9]: The school site has not changed.\n\n[username10]: I keep refreshing it.\n\n[username11]: Does anyone know about the power outage?\n\n[username12]: My block still has power.\n\n[username13]: The next block is dark.\n\n[username14]: I hope everyone is safe.\n\n[username15]: The council page just posted a link.\n\n[username16]: It says the briefing starts in ten minutes.\n\n[username17]: Thanks. I will tune in.\n\n[username18]: Can someone share the main points here?\n\n[username19]: I can do that.\n\n[username20]: I will listen too.\n\n[username21]: The video is loading now.\n\n[username22]: I am ready for the update.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2394311836615817, "classifierCostIndex": 0, "promptTokens": 68, "completionTokens": 341, "reasoningTokens": 88, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4793, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "68", "completionTokens": "341", "reasoningTokens": "88", "cachedTokens": "0" }, "timing": { "headersMs": 12231.373207999859, "firstEventMs": 12745.217249999987, "firstReasoningMs": 15711.96095800004, "firstContentMs": 16919.04237499996, "lastContentMs": 17008.765832999954, "generationMs": 636.1373330000788, "totalMs": 17555.17970800004, "visibleTokensPerSecond": 396.14087544830323, "contentChunkCount": 89, "averageContentChunkCharacters": 11.269662921348315, "maxContentStallMs": 76.24212500010617, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1512", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:45:35.712Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "**Thread: Any local updates yet?**\n\n[username1]: Has anyone heard the latest news?\n\n[username2]: I keep refreshing the town website.\n\n[username3]: The local station is still playing music.\n\n[username4]: I heard there might be an announcement.\n\n[username5]: Do we know what it concerns?\n\n[username6]: Nobody has confirmed anything yet.\n\n[username7]: I hope it concerns the old bridge.\n\n[username8]: That closure has made my commute longer.\n\n[username9]: Could it be about the library?\n\n[username10]: I am waiting for its opening date.\n\n[username11]: The council meeting just ended.\n\n[username12]: Did anyone attend?\n\n[username13]: My neighbor went. She has not called back.\n\n[username14]: Please share anything she confirms.\n\n[username15]: The newspaper says an update is coming.\n\n[username16]: Does it give a time?\n\n[username17]: It only says soon.\n\n[username18]: My tea is getting cold.\n\n[username19]: I have refreshed this thread ten times.\n\n[username20]: Let us avoid spreading guesses.\n\n[username21]: Agreed. We need a reliable source.\n\n[username22]: The radio host just mentioned town hall.\n\n[username23]: Are they going live?\n\n[username24]: Not yet. I am keeping the radio on.\n\n[username1]: Thanks for checking.\n\n[username12]: My phone battery is nearly dead.\n\n[username8]: Plug it in. We might be here awhile.\n\n[username3]: The music just stopped.\n\n[username19]: Finally. What are they saying?\n\n[username3]: It is an advertisement.\n\n[username18]: I am making more tea.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.233153989984787, "classifierCostIndex": 0, "promptTokens": 68, "completionTokens": 352, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8642, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "68", "completionTokens": "352", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 29797.92191600008, "firstEventMs": 30768.20287499996, "firstReasoningMs": null, "firstContentMs": 31642.189916000003, "lastContentMs": 38009.699375000084, "generationMs": 9372.970583999995, "totalMs": 41015.1605, "visibleTokensPerSecond": 37.44810643054507, "contentChunkCount": 113, "averageContentChunkCharacters": 13.053097345132743, "maxContentStallMs": 2173.3354589999653, "finalContentBurstRatio": 0.23389830508474577, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1512", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:46:16.727Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "**Local News Watch Thread**\n\n**[username1]:** Anyone else waiting for the 6pm broadcast? I need updates now.\n\n**[username2]:** Same here. My phone has no signal today.\n\n**[username3]:** [username1] I heard something about downtown. Not sure what.\n\n**[username4]:** Waiting is torture. Someone post details please.\n\n**[username5]:** [username2] try the local radio station. They might air it early.\n\n**[username6]:** I just got here. What did I miss?\n\n**[username7]:** [username6] nothing yet. We are all waiting too.\n\n**[username8]:** My neighbor said there was an accident. Unconfirmed though.\n\n**[username9]:** [username8] please do not spread rumors. Wait for facts.\n\n**[username10]:** I agree with [username9]. Let's stay calm.\n\n**[username11]:** Does anyone have a live stream link?\n\n**[username12]:** [username11] I found one. Will share soon.\n\n**[username13]:** Thanks in advance [username12]. This wait is killing me.\n\n**[username14]:** I just refreshed the news site. Still nothing.\n\n**[username15]:** [username14] same. This is frustrating.\n\n**[username16]:** Maybe the broadcast got delayed. It happens sometimes.\n\n**[username17]:** [username16] that would explain the silence.\n\n**[username18]:** I hope everyone is safe. That's my main concern.\n\n**[username19]:** [username18] agreed. Facts matter more than speed.\n\n**[username20]:** Finally! The news just started. Turn it on now.\n\n**[username1]:** Thanks [username20]! Watching now.\n\n**[username3]:** [username20] appreciate the heads up.\n\n**[username9]:** Let's discuss once it's over. Stay tuned everyone.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.42381725224665234, "classifierCostIndex": 0.004519132160713656, "promptTokens": 100, "completionTokens": 601, "reasoningTokens": 19, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8451, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "100", "completionTokens": "601", "reasoningTokens": "19", "cachedTokens": "0" }, "timing": { "headersMs": 18293.732624999946, "firstEventMs": 19705.334999999963, "firstReasoningMs": 20931.50524999993, "firstContentMs": 20931.62920799991, "lastContentMs": 26731.11654099985, "generationMs": 5878.933707999997, "totalMs": 26810.562915999908, "visibleTokensPerSecond": 98.82744539360611, "contentChunkCount": 150, "averageContentChunkCharacters": 10.473333333333333, "maxContentStallMs": 923.0233750001062, "finalContentBurstRatio": 0.44939528962444303, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 820, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2355", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:46:49.630Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Wherefore doth people consider the 2nd Amendment to be outdated? Answer in a Shakespearean style.\n\nSome deem the Second Amendment old-fashioned, for muskets of the founding age are not the arms borne today, and the threats and needs of society have changed. They argue that its words, forged in an age of militias, must be weighed against modern weapons and the public’s safety. Others hold the right to bear arms as a lasting safeguard, not bound to the tools of one age. Thus do they contend: not whether the amendment hath meaning, but how its ancient words should govern a changed world.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01292828170443245, "classifierCostIndex": 0, "promptTokens": 55, "completionTokens": 364, "reasoningTokens": 234, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3484, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "55", "completionTokens": "364", "reasoningTokens": "234", "cachedTokens": "0" }, "timing": { "headersMs": 17833.8372500001, "firstEventMs": 18445.587624999927, "firstReasoningMs": null, "firstContentMs": 20582.62591599999, "lastContentMs": 21318.94225000008, "generationMs": 2825.6762089999393, "totalMs": 23408.30212499993, "visibleTokensPerSecond": 45.65278908783946, "contentChunkCount": 66, "averageContentChunkCharacters": 8.954545454545455, "maxContentStallMs": 447.3426670001354, "finalContentBurstRatio": 0.27918781725888325, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2355", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:47:13.040Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Wherefore doth people consider the 2nd Amendment to be outdated? Answer in a Shakespearean style.\n\nSome deem it aged because the world wherein it was writ hath changed: firearms now possess a power scarce imagined in that earlier day, and the meaning of a “well regulated Militia” is much disputed. Others point to gun violence and ask whether laws fashioned centuries past can answer present perils.\n\nYet many hold that the right it protects is no less vital for the passing of years. Thus doth the quarrel endure: not merely over the Amendment’s age, but over how its ancient words should govern modern life.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1701577422349361, "classifierCostIndex": 0, "promptTokens": 55, "completionTokens": 241, "reasoningTokens": 109, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3501, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "55", "completionTokens": "241", "reasoningTokens": "109", "cachedTokens": "0" }, "timing": { "headersMs": 23726.160542000085, "firstEventMs": 24584.484375, "firstReasoningMs": null, "firstContentMs": 25704.272709000157, "lastContentMs": 27297.24845900014, "generationMs": 4543.680957999779, "totalMs": 30247.953666999936, "visibleTokensPerSecond": 28.831249643388006, "contentChunkCount": 67, "averageContentChunkCharacters": 9.104477611940299, "maxContentStallMs": 1284.7145000000019, "finalContentBurstRatio": 0.42950819672131146, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2355", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:47:43.288Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "Wherefore doth people consider the 2nd Amendment to be outdated? Answer in a Shakespearean style.\n\nHark, and give ear, for I shall now unfold\nThe reasons why some deem this law of old\nA relic worn, unfit for present days,\nAnd why their tongues do speak in such a phrase.\n\nThey say when first this Amendment was penned,\nThe muskets slow did knowledge's use attend,\nOne shot, then pause, then powder packed anew—\nA weapon far from what the age now knew.\n\nBut now, they cry, do weapons swift multiply,\nThat fire many rounds ere one can sigh,\nAnd thus the danger grown a hundredfold,\nWhilst still we cling unto the words of old.\n\nThey say the militia, once of common band,\nHath now become the standing army's hand,\nNo more need citizens to arm as troops,\nFor soldiers trained do guard in ordered groups.\n\nAnd further still, they point to blood oft spilled,\nIn schools and streets, where innocents are killed,\nAnd question whether liberty's own cost\nIn precious lives be worth what may be lost.\n\nYet others hold the right as sacred still,\nA shield 'gainst tyranny, a guard 'gainst ill,\nAnd thus the debate rages, fierce and long,\n'Twixt those who'd change and those who'd right the wrong.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.30239041156779145, "classifierCostIndex": 0.004487568511917817, "promptTokens": 81, "completionTokens": 425, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 13933, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "81", "completionTokens": "425", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 54632.443416999886, "firstEventMs": 55720.720458999975, "firstReasoningMs": null, "firstContentMs": 55720.75562499999, "lastContentMs": 68109.72112499992, "generationMs": 12978.721292000031, "totalMs": 68699.47691700002, "visibleTokensPerSecond": 32.66885777579258, "contentChunkCount": 161, "averageContentChunkCharacters": 7.3478260869565215, "maxContentStallMs": 985.1131659999955, "finalContentBurstRatio": 0.49535080304311074, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 2110, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2355", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:48:51.988Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Wherefore doth people consider the 2nd Amendment to be outdated? Answer in a Shakespearean style.\n\nSome deem this ancient safeguard past its hour,\nFor these chief causes weigh upon their minds:\n\n**First, arms have changed their shape and dreadful power.**\nThe musket of the founders’ age did yield\nFar slower fire than many weapons now.\nThus critics ask if rules from yesteryear\nShould govern unchanged tools of greater slaughter.\n\n**Next, common defence hath donned another cloak.**\nWhere once the citizen militia stood\nAs bulwark ’gainst invasion and oppression,\nNow armies, guards, and officers keep watch.\nSome therefore judge the old provision’s purpose\nLess fitted to the ordering of our age.\n\n**Third, public sorrow presseth hard upon them.**\nThe toll of murder, suicide, and shootings\nDoth stir the plea that safety must weigh more,\nAnd ancient liberties admit new bounds.\n\n**Yet mark: not all who seek restraint would strike it out.**\nSome hold the right should live, but fenced by laws;\nAnd others say ’tis no more stale than speech—\nThat self-defence and checks on tyrants’ power\nRemain good cause to keep its promise whole.\n\nSo runs the quarrel: whether time hath dimmed\nThe right itself, or changed how it should work.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.1805303732979464, "classifierCostIndex": 0, "promptTokens": 55, "completionTokens": 339, "reasoningTokens": 62, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 10624, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "55", "completionTokens": "339", "reasoningTokens": "62", "cachedTokens": "0" }, "timing": { "headersMs": 41907.035959, "firstEventMs": 42522.654249999905, "firstReasoningMs": null, "firstContentMs": 45902.72483399999, "lastContentMs": 52478.74358400004, "generationMs": 11094.706833000062, "totalMs": 56997.431667000055, "visibleTokensPerSecond": 24.87672762826562, "contentChunkCount": 115, "averageContentChunkCharacters": 10.704347826086957, "maxContentStallMs": 2901.3347090000752, "finalContentBurstRatio": 0.20796100731112915, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-7", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:49:50.224Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-7,0,30,66", "evaluation": { "passed": true, "answer": "-7,0,30,66", "expected": "-7,0,30,66" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0015222041737651436, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 38, "reasoningTokens": 24, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2399, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "38", "reasoningTokens": "24", "cachedTokens": "0" }, "timing": { "headersMs": 4560.826333000092, "firstEventMs": 4867.492624999955, "firstReasoningMs": 6198.776540999999, "firstContentMs": 6898.312207999872, "lastContentMs": 6898.341041000094, "generationMs": 12.72650000010617, "totalMs": 6911.038707999978, "visibleTokensPerSecond": 1021.4905904916158, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 0.01816600002348423, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-7", "category": "easy", "arm": "smart", "at": "2026-09-26T09:49:57.136Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-7,0,30,66", "evaluation": { "passed": true, "answer": "-7,0,30,66", "expected": "-7,0,30,66" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005013764212569817, "classifierCostIndex": 0.004385863421353446, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1238, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 13039.020000000019, "firstEventMs": 13521.10566700017, "firstReasoningMs": null, "firstContentMs": 14137.235709000146, "lastContentMs": 14137.352375000017, "generationMs": 135.64662499981932, "totalMs": 14272.882333999965, "visibleTokensPerSecond": 81.09306073788899, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 0.01924999989569187, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 2048, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-7", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:50:11.409Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "-7,0,30,66", "evaluation": { "passed": true, "answer": "-7,0,30,66", "expected": "-7,0,30,66" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0600525395818441, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3325, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 271.722958000144, "firstEventMs": 786.878458000021, "firstReasoningMs": null, "firstContentMs": 2547.065249999985, "lastContentMs": 2551.9237919999287, "generationMs": 1053.8302500001155, "totalMs": 3600.8955000001006, "visibleTokensPerSecond": 10.438113728466984, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 4.765583999920636, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-7", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:50:15.011Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "-7,0,30,66", "evaluation": { "passed": true, "answer": "-7,0,30,66", "expected": "-7,0,30,66" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012032629448003512, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2618, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 13518.413416000083, "firstEventMs": 14190.288750000065, "firstReasoningMs": null, "firstContentMs": 14992.665166000137, "lastContentMs": 15000.544875000138, "generationMs": 2364.6596669999417, "totalMs": 17357.32483300008, "visibleTokensPerSecond": 4.651832208038533, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 6.9619160001166165, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3071", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:50:34.108Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "## **Verse 1 — The Marble Has Opinions**\nYo, I woke in Florence with a pigeon for a crown, \nA marble torso told me, “Put that manuscript down.” \n“Learn Greek, little freak! Let the old words breathe!” \nThen he flexed a missing arm and tucked a quill in his sleeve. \nGot a patron named Medici—he’s funding my vision, \nBut he wants his whole family in the Crucifixion. \nPut his cousin by the donkey, give his banker a halo— \nIn this town, even heaven needs somebody on payroll.\n\n## **Hook — Make It Weird, Make It Human**\nPaint flesh! Print texts! Let the dead Greeks cook! \nGot a skull on my desk and my nose in a book. \nWorld’s not flat in my painting—watch the floorboards meet: \nOne vanishing point at the end of the street. \nPaint flesh! Print texts! Let the strange thoughts bloom! \nI put mankind at the center—now he’s hogging the room.\n\n## **Verse 2 — Extremely Suspicious Workshop**\nBrunelleschi’s dome got the skyline wearing armor, \nI’m grinding up a gemstone just to paint a robe on Mary. \nBlue costs a fortune; my apprentice looks alarmed— \n“Boss, that sleeve just ate the budget for the farm.” \nLeonardo’s in the corner making wings for a dude, \nSays, “Observe the birds.” Bro, the birds look confused. \nMona Lisa’s got a secret, won’t disclose it for cash; \nIt’s “I watched you spend six evenings on the shadow of a lash.” \nBotticelli sent a goddess surfing in upon a shell— \nThe anatomy is dreamy and the hair’s doing well.\n\n## **Verse 3 — The Printing Press Is Possessed**\nClack-clack, movable type, now the gossip has legs, \nNo more waiting six months while a tired monk begs. \nPamphlets in the market, new ideas in stacks— \nYou can burn one little book, but its cousins come back. \nI’m a humanist goblin with a classical itch, \nReading Cicero aloud in a doublet too rich. \nNot steam, not steel—hear the workshop sing: \nA compass, wet plaster, and a lute with one string. \nThen my marble friend whispers as the candle burns low: \n“We revived the ancient world.” \nMan, I know. \n**It’s demanding a studio.**", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 2.2342072514097437, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 653, "reasoningTokens": 128, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 19901, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "653", "reasoningTokens": "128", "cachedTokens": "0" }, "timing": { "headersMs": 17202.91008400009, "firstEventMs": 18021.973459, "firstReasoningMs": null, "firstContentMs": 21817.610708999913, "lastContentMs": 37071.144542000024, "generationMs": 15866.12437500013, "totalMs": 37683.73508400004, "visibleTokensPerSecond": 33.02633885976932, "contentChunkCount": 176, "averageContentChunkCharacters": 11.664772727272727, "maxContentStallMs": 3745.1032910000067, "finalContentBurstRatio": 0.11933755479785679, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3071", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:51:11.793Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "## I. The Vanishing Point Speaks\n\nI’m a dot on the wall with a terrible grin, \nTell the whole painted city, “Everybody lean in.” \nStreets run straight to my face—what a view! \nA flat little panel grows a world you could walk through. \n\nFlorence smells of wet plaster, gold leaf, and debt; \nA banker buys a ceiling that he hasn’t seen yet. \nThe painter says, “Hold still.” The angels say, “Why?” \nThen a ladder starts wobbling halfway to the sky.\n\n## II. Press, Press, Press\n\n*Clack* goes the press in a back-alley room: \nOne idea, two hundred copies by noon. \nInk on my fingers, ink under my hat— \nA scholar reads a pamphlet and argues with that. \n\nI’ve got Greek in one pocket, a sketch in the other, \nA question for the stars and an arm from my brother— \nNot his real arm! A drawing. Please don’t call the guard. \nThe human body’s beautiful, and drawing it is hard.\n\n## III. The Marble Has Opinions\n\nMichelangelo taps; the white stone coughs: \n“I was a mountain once. Could you take Tuesdays off?” \nLeonardo brings a notebook full of wings and gears; \nA horse with perfect muscles stands unfinished for years. \n\nWe’re not done with heaven, but we’re looking down here: \nAt the curve of a hand, at a face in a mirror. \nSo move back, little dot. Let the whole room show— \nThe world got deep, and now we want to know.", "evaluation": { "passed": false, "answer": "0", "expected": "all instructions followed", "detail": "Failed: detectable_format:number_highlighted_sections", "score": 0, "metrics": { "instructionsPassed": 0, "instructionsTotal": 1 } }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.3229986415963259, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 469, "reasoningTokens": 123, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 11848, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "469", "reasoningTokens": "123", "cachedTokens": "0" }, "timing": { "headersMs": 32682.75450000004, "firstEventMs": 35224.24795900006, "firstReasoningMs": null, "firstContentMs": 37806.174624999985, "lastContentMs": 44498.06924999994, "generationMs": 7246.0815000000875, "totalMs": 45052.25612500007, "visibleTokensPerSecond": 47.611940329403666, "contentChunkCount": 340, "averageContentChunkCharacters": 3.9323529411764704, "maxContentStallMs": 1327.958125000121, "finalContentBurstRatio": 0.5512341062079282, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3071", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:51:56.846Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "## **I. The Paintbrush Has a Mouth**\n\nI’m a brush with a twitch and a powdered-wig itch, \nLiving in a jar where the turpentine’s rich. \nFlorence goes *clink*—coins buy a wall, \nThen I’m painting a saint who’s got excellent calves. \n\nMasaccio said, “Watch—make the hallway recede,” \nNow the flat little room’s got a vanishing need. \nOne point on the horizon, the whole world leans— \nI just gave a painted floor some extremely long dreams.\n\n## **II. The Humanist Beat**\n\nMove over, old questions—there’s a person in frame, \nWith a pulse, a proportion, and a very bold name. \nVitruvian Man’s doing starfish in a square, \nLike, “I contain the cosmos—and I need more air.” \n\nDa Vinci’s got notebooks full of gears and geese, \nA flying machine, then a recipe for peace? \nHe sketches a skull, then a canal, then a cat— \nThat man had seventeen tabs open in his hat.\n\n## **III. The Press Gets Loose**\n\nGutenberg’s press goes *ka-chunk, ka-chunk,* \nBooks multiply fast—knowledge’s out of the trunk. \nIdeas hit the road in a paper parade, \nNo more one-copy scroll with a monk-made shade. \n\nPatrons drop cash like, “Make my ceiling divine!” \nMichelangelo climbs up and argues with time. \nThe Sistine’s got prophets, sibyls, and flair— \nPlus a man on a scaffold yelling, “Who put paint in my hair?”\n\n## **IV. The Renaissance Ruckus**\n\nAnatomy! Optics! Old Greek texts revived! \nThe workshop’s so busy the statues look alive. \nA marble nose whispers, “I have seen the new age.” \nA painter replies, “Then hold still for the page.” \n\nNot knights charging dragons—not pyramids in sand— \nIt’s a sketch, a press, and a curious hand. \nThe Renaissance: big brains in a paint-splattered room, \nWhere the future walked in—and borrowed a broom.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.020057754598039598, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 573, "reasoningTokens": 114, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5414, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "573", "reasoningTokens": "114", "cachedTokens": "0" }, "timing": { "headersMs": 1240.1116249999031, "firstEventMs": 1677.133166999789, "firstReasoningMs": 3548.5669589999598, "firstContentMs": 4365.447833999991, "lastContentMs": 6644.446749999886, "generationMs": 2295.2218749998137, "totalMs": 6660.669708999805, "visibleTokensPerSecond": 199.54497863089475, "contentChunkCount": 113, "averageContentChunkCharacters": 15.469026548672566, "maxContentStallMs": 898.9382910002023, "finalContentBurstRatio": 0.4364988558352403, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3071", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:52:03.507Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# *Gilded Rot*\n\nYo, step into the studio smelling like linseed oil and plague smoke,\n*Fresco Fever* — every wall's a joke on a dying pope's back,\nMedici money laundered through a Madonna's gaze,\npatron says \"paint me holy\" while he's poisoning his in-laws for days.\n\n**Verse 1: The Workshop**\nApprentice grinding pigment till his knuckles bleed lapis blue,\nMaster's out here signing contracts, taking credit for the residue,\nPerspective lines converging like a vanishing point flex,\nmath nerds discovering that beauty's got an X and Y and hex-\nagonal domes, Brunelleschi built without a single nail,\nengineering flex so hard the whole cathedral tells a tale.\nMeanwhile plague cart rolling by, bodies stacked like cordwood,\nand some dude's like \"let's paint a nude\" — sir, should we? Sir, we should.\n\n**Chorus**\n*It's a rebirth but it's rotten at the root,*\n*humanism dressed up in a velvet suit,*\n*skulls in the corner of every vanitas scene,*\n*memento mori — you know what I mean.*\n\n**Verse 2: The Patrons**\nPopes commissioning sin while they're selling indulgence coupons,\nBorgias slipping cyanide in the after-dinner croutons,\nDa Vinci's got a notebook full of tanks and flying rigs,\nwriting backwards like a paranoid solving cosmic gigs,\ndissecting corpses by candlelight just to learn a shoulder,\ngenius getting weirder as the world keeps getting colder.\nMichelangelo up on the scaffold catching neck strain,\npainting God reaching down like it's a cosmic sprain.\n\n**Bridge: The Weird Part**\n*Everybody's a philosopher, everybody's a fraud,*\n*alchemists in basements trying to talk to God,*\n*astrology and anatomy sharing the same desk,*\n*Latin poetry next to a witch-hunting text.*\n\n**Outro**\nSo don't romanticize it, kid, it's gorgeous but it's grim,\nbeauty built on syphilis and cardinals gone dim,\nthe David's staring cold while the city's catching fire —\nthat's the renaissance: a corpse dressed in gold wire.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5329634055709477, "classifierCostIndex": 0.004448990718945125, "promptTokens": 69, "completionTokens": 769, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 13997, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "69", "completionTokens": "769", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2408.5438339998946, "firstEventMs": 3684.043458999833, "firstReasoningMs": null, "firstContentMs": 3684.065834000008, "lastContentMs": 16485.191208999837, "generationMs": 12801.265082999831, "totalMs": 16485.33091699984, "visibleTokensPerSecond": 59.99407050947717, "contentChunkCount": 284, "averageContentChunkCharacters": 6.753521126760563, "maxContentStallMs": 910.9449169998989, "finalContentBurstRatio": 0.19655891553701774, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 631, "classifierFailed": false, "classifierReused": false } }, { "caseId": "number_theory_powmod", "category": "math", "arm": "smart", "at": "2026-09-26T09:52:21.835Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "", "evaluation": { "passed": false, "answer": "", "expected": "657123", "detail": "no answer != 657123" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 5.543651376369663, "classifierCostIndex": 0.00446301900729883, "promptTokens": 64, "completionTokens": 8192, "reasoningTokens": 8192, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 65398, "loggedFinishReason": "max_tokens", "billedUsage": { "promptTokens": "64", "completionTokens": "8192", "reasoningTokens": "8192", "cachedTokens": "0" }, "timing": { "headersMs": 1125.3786250001285, "firstEventMs": 2128.7639580001123, "firstReasoningMs": 4040.546791000059, "firstContentMs": null, "lastContentMs": null, "generationMs": null, "totalMs": 66459.07562500006, "visibleTokensPerSecond": null, "contentChunkCount": 0, "averageContentChunkCharacters": null, "maxContentStallMs": null, "finalContentBurstRatio": null, "buffered": null }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 326, "classifierFailed": false, "classifierReused": false } }, { "caseId": "number_theory_powmod", "category": "math", "arm": "gpt-6-astra", "at": "2026-09-26T09:53:28.295Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 657123", "evaluation": { "passed": true, "answer": "657123", "expected": "657123", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 4.5452908718716785, "classifierCostIndex": 0, "promptTokens": 48, "completionTokens": 1338, "reasoningTokens": 1327, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 24210, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "48", "completionTokens": "1338", "reasoningTokens": "1327", "cachedTokens": "0" }, "timing": { "headersMs": 296.6287499999162, "firstEventMs": 816.2507909999695, "firstReasoningMs": null, "firstContentMs": 24370.605375000043, "lastContentMs": 24392.86924999999, "generationMs": 140.31395799992606, "totalMs": 24510.91933299997, "visibleTokensPerSecond": 71.26874719053446, "contentChunkCount": 5, "averageContentChunkCharacters": 2.6, "maxContentStallMs": 20.052667000098154, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "number_theory_powmod", "category": "math", "arm": "gpt-6-sol", "at": "2026-09-26T09:53:52.806Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "FINAL: 657123", "evaluation": { "passed": true, "answer": "657123", "expected": "657123", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.642301834122491, "classifierCostIndex": 0, "promptTokens": 48, "completionTokens": 2423, "reasoningTokens": 2412, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 24279, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "48", "completionTokens": "2423", "reasoningTokens": "2412", "cachedTokens": "0" }, "timing": { "headersMs": 4207.128500000108, "firstEventMs": 4823.200750000076, "firstReasoningMs": 9791.78520900011, "firstContentMs": 28531.31379200006, "lastContentMs": 28531.35408399999, "generationMs": 3172.890583000146, "totalMs": 31704.204375000205, "visibleTokensPerSecond": 3.1517002362383515, "contentChunkCount": 5, "averageContentChunkCharacters": 2.6, "maxContentStallMs": 0.014292000094428658, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "number_theory_powmod", "category": "math", "arm": "gpt-6-luna", "at": "2026-09-26T09:54:24.511Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 402499", "evaluation": { "passed": false, "answer": "402499", "expected": "657123", "detail": "402499 != 657123" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.11441418026327604, "classifierCostIndex": 0, "promptTokens": 48, "completionTokens": 3316, "reasoningTokens": 3305, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 17712, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "48", "completionTokens": "3316", "reasoningTokens": "3305", "cachedTokens": "0" }, "timing": { "headersMs": 411.0489580000285, "firstEventMs": 1023.3140829999465, "firstReasoningMs": 4299.322042000014, "firstContentMs": 18058.01883299998, "lastContentMs": 18058.038833, "generationMs": 155.7567089998629, "totalMs": 18213.775541999843, "visibleTokensPerSecond": 64.20269190464728, "contentChunkCount": 5, "averageContentChunkCharacters": 2.6, "maxContentStallMs": 0.00929099996574223, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-24", "category": "easy", "arm": "smart", "at": "2026-09-26T09:54:43.971Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005261822119131988, "classifierCostIndex": 0.0044174270701492855, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1432, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 1019.3774999999441, "firstEventMs": 1430.400999999838, "firstReasoningMs": null, "firstContentMs": 2320.2726249999832, "lastContentMs": 2344.45541699999, "generationMs": 94.12129199993797, "totalMs": 2414.393916999921, "visibleTokensPerSecond": 74.37211975378126, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 24.182792000006884, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 243, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-24", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:54:46.386Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008795332135609764, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1081, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 4995.709917000029, "firstEventMs": 5260.853832999943, "firstReasoningMs": null, "firstContentMs": 5754.376124999952, "lastContentMs": 5754.380417000037, "generationMs": 428.3155829999596, "totalMs": 6182.691707999911, "visibleTokensPerSecond": 11.673635511880201, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.004292000085115433, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-24", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:54:52.569Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04386605301987537, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1159, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 328.27758300001733, "firstEventMs": 627.2274579999503, "firstReasoningMs": null, "firstContentMs": 1211.2303329999559, "lastContentMs": 1212.4827079998795, "generationMs": 361.51291699986905, "totalMs": 1572.743249999825, "visibleTokensPerSecond": 13.830764448181007, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 1.2523749999236315, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-24", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:54:54.142Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008443950489827026, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1852, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 22864.46887500002, "firstEventMs": 23574.423083000118, "firstReasoningMs": null, "firstContentMs": 24746.400707999943, "lastContentMs": 24746.402250000043, "generationMs": 2595.6072920002043, "totalMs": 27342.008000000147, "visibleTokensPerSecond": 2.696864052422091, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.001542000100016594, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-12", "category": "easy", "arm": "smart", "at": "2026-09-26T09:55:26.557Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-12,0,45,101", "evaluation": { "passed": true, "answer": "-12,0,45,101", "expected": "-12,0,45,101" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0050207783567466704, "classifierCostIndex": 0.0043928775655303, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1291, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2823.4618329997174, "firstEventMs": 3231.723958000075, "firstReasoningMs": null, "firstContentMs": 4109.846082999837, "lastContentMs": 4111.398041999899, "generationMs": 172.73204200016335, "totalMs": 4282.578125, "visibleTokensPerSecond": 63.68245215320038, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 1.484209000132978, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 192, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-12", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:55:30.840Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "-12,0,45,101", "evaluation": { "passed": true, "answer": "-12,0,45,101", "expected": "-12,0,45,101" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0600525395818441, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1360, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 744.1710840002634, "firstEventMs": 1153.152584000025, "firstReasoningMs": null, "firstContentMs": 2172.1841250001453, "lastContentMs": 2172.2504590000026, "generationMs": 0.20200000004842877, "totalMs": 2172.3861250001937, "visibleTokensPerSecond": 54455.44553149896, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.025750000029802322, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-12", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:55:33.012Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "-12,0,45,101", "evaluation": { "passed": true, "answer": "-12,0,45,101", "expected": "-12,0,45,101" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012032629448003512, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1369, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 292.89829199993983, "firstEventMs": 727.5314170001075, "firstReasoningMs": null, "firstContentMs": 1338.2759170001373, "lastContentMs": 1380.5445420001633, "generationMs": 787.9774159998633, "totalMs": 2126.2533330000006, "visibleTokensPerSecond": 13.959790949137949, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 38.58741599973291, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-12", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:55:35.139Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-12,0,45,101", "evaluation": { "passed": true, "answer": "-12,0,45,101", "expected": "-12,0,45,101" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.002106941000816265, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 55, "reasoningTokens": 41, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2723, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "55", "reasoningTokens": "41", "cachedTokens": "0" }, "timing": { "headersMs": 1053.2150409999304, "firstEventMs": 1577.8205409999937, "firstReasoningMs": 2707.4987909998745, "firstContentMs": 3741.9673329996876, "lastContentMs": 3742.1565829999745, "generationMs": 26.507417000364512, "totalMs": 3768.474750000052, "visibleTokensPerSecond": 490.4287731928476, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.1163330003619194, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-0", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:55:39.076Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "26", "evaluation": { "passed": true, "answer": "26", "expected": "26" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028341189096127102, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1295, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 290.6957499999553, "firstEventMs": 596.6005000001751, "firstReasoningMs": null, "firstContentMs": 1399.7198330000974, "lastContentMs": 1399.7198330000974, "generationMs": 278.1582089997828, "totalMs": 1677.8780419998802, "visibleTokensPerSecond": 14.380305418212998, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-0", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:55:40.755Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "26", "evaluation": { "passed": true, "answer": "26", "expected": "26" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0056801079093708635, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1378, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 9363.291708000004, "firstEventMs": 10284.825832999777, "firstReasoningMs": null, "firstContentMs": 10679.530292000156, "lastContentMs": 10679.530292000156, "generationMs": 936.8608329999261, "totalMs": 11616.391125000082, "visibleTokensPerSecond": 4.269577571293682, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-0", "category": "easy", "arm": "smart", "at": "2026-09-26T09:55:52.372Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "26", "evaluation": { "passed": true, "answer": "26", "expected": "26" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0046348655396317336, "classifierCostIndex": 0.004336764412115475, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1732, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1228.4174999999814, "firstEventMs": 1895.4096249998547, "firstReasoningMs": null, "firstContentMs": 2510.2118329997174, "lastContentMs": 2510.2118329997174, "generationMs": 460.1241250000894, "totalMs": 2970.335957999807, "visibleTokensPerSecond": 8.693306398570652, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 238, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-0", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:55:55.342Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "26", "evaluation": { "passed": true, "answer": "26", "expected": "26" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.00029810112751625764, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1214, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 4118.263207999989, "firstEventMs": 4708.400625000242, "firstReasoningMs": null, "firstContentMs": 5324.115625000093, "lastContentMs": 5324.115625000093, "generationMs": 22.206125000026077, "totalMs": 5346.321750000119, "visibleTokensPerSecond": 180.1304820177002, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "boolean_constraints", "category": "logic", "arm": "gpt-6-sol", "at": "2026-09-26T09:56:00.926Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "FINAL: 2, 01010100", "evaluation": { "passed": true, "answer": "2,01010100", "expected": "2,01010100", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2039591727979673, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 274, "reasoningTokens": 259, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2957, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "274", "reasoningTokens": "259", "cachedTokens": "0" }, "timing": { "headersMs": 194.09024999989197, "firstEventMs": 971.279957999941, "firstReasoningMs": null, "firstContentMs": 3120.472957999911, "lastContentMs": 3120.5404170001857, "generationMs": 35.9742499999702, "totalMs": 3156.4472079998814, "visibleTokensPerSecond": 389.16725157610233, "contentChunkCount": 9, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.00925000011920929, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "boolean_constraints", "category": "logic", "arm": "smart", "at": "2026-09-26T09:56:04.082Z", "model": null, "loggedModel": "aws-bedrock/claude-sonnet-5:global", "content": "", "evaluation": { "passed": false, "answer": "", "expected": "2,01010100", "detail": "no answer != 2,01010100" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.004775148423168795, "classifierCostIndex": 0.004775148423168795, "promptTokens": null, "completionTokens": null, "reasoningTokens": null, "cachedInputTokens": null, "finishReason": null, "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1899, "loggedFinishReason": "gateway_error", "billedUsage": { "promptTokens": null, "completionTokens": null, "reasoningTokens": null, "cachedTokens": null }, "timing": { "headersMs": 6620.516082999762, "firstEventMs": 8669.857290999964, "firstReasoningMs": null, "firstContentMs": null, "lastContentMs": null, "generationMs": null, "totalMs": 8670.253333, "visibleTokensPerSecond": null, "contentChunkCount": 0, "averageContentChunkCharacters": null, "maxContentStallMs": null, "finalContentBurstRatio": null, "buffered": null }, "error": { "code": "gateway_error" }, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 172, "classifierFailed": false, "classifierReused": false } }, { "caseId": "boolean_constraints", "category": "logic", "arm": "gpt-6-astra", "at": "2026-09-26T09:57:04.205Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 2,01010100", "evaluation": { "passed": true, "answer": "2,01010100", "expected": "2,01010100", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.9073746448845028, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 241, "reasoningTokens": 227, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5088, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "241", "reasoningTokens": "227", "cachedTokens": "0" }, "timing": { "headersMs": 815.658042, "firstEventMs": 1781.5145830000001, "firstReasoningMs": null, "firstContentMs": 5508.7807920000005, "lastContentMs": 5652.801792, "generationMs": 399.19845799999985, "totalMs": 5907.97925, "visibleTokensPerSecond": 32.56525605116442, "contentChunkCount": 8, "averageContentChunkCharacters": 2.125, "maxContentStallMs": 126.37858299999971, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "boolean_constraints", "category": "logic", "arm": "gpt-6-luna", "at": "2026-09-26T09:57:10.114Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 2, 01010100", "evaluation": { "passed": true, "answer": "2,01010100", "expected": "2,01010100", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.019027889390534337, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 523, "reasoningTokens": 508, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4205, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "523", "reasoningTokens": "508", "cachedTokens": "0" }, "timing": { "headersMs": 400.80825000000004, "firstEventMs": 1056.2527910000008, "firstReasoningMs": null, "firstContentMs": 4188.545749999999, "lastContentMs": 4188.898083, "generationMs": 502.71816600000056, "totalMs": 4691.263916, "visibleTokensPerSecond": 27.848605733495585, "contentChunkCount": 9, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.08950000000004366, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-1", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:57:15.624Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "ORD-24-12", "evaluation": { "passed": true, "answer": "ORD-24-12", "expected": "ORD-24-12" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.05330951905490397, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2730, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 201.9364170000008, "firstEventMs": 1125.5133750000005, "firstReasoningMs": null, "firstContentMs": 2929.624833, "lastContentMs": 2929.824292000001, "generationMs": 37.114042000001064, "totalMs": 2966.738875000001, "visibleTokensPerSecond": 215.55183884309264, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.05733400000099209, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-1", "category": "easy", "arm": "smart", "at": "2026-09-26T09:57:18.591Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-24-12", "evaluation": { "passed": true, "answer": "ORD-24-12", "expected": "ORD-24-12" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004966553626764076, "classifierCostIndex": 0.004404747655675743, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2551, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 131895.0555, "firstEventMs": 132202.141125, "firstReasoningMs": null, "firstContentMs": 133136.27825, "lastContentMs": 133136.433083, "generationMs": 6848.306458000006, "totalMs": 139984.584708, "visibleTokensPerSecond": 1.1681720216615914, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.05704200000036508, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 3583, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-1", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:59:38.576Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-24-12", "evaluation": { "passed": true, "answer": "ORD-24-12", "expected": "ORD-24-12" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0013873167857487375, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 33, "reasoningTokens": 22, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2771, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "33", "reasoningTokens": "22", "cachedTokens": "0" }, "timing": { "headersMs": 7066.192291000014, "firstEventMs": 7503.790540999995, "firstReasoningMs": null, "firstContentMs": 9827.628250000009, "lastContentMs": 9830.733708000014, "generationMs": 118.90533300000243, "totalMs": 9946.533583000011, "visibleTokensPerSecond": 84.10051717360562, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 2.788458000024548, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-1", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:59:48.523Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "ORD-24-12", "evaluation": { "passed": true, "answer": "ORD-24-12", "expected": "ORD-24-12" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010685104441719615, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 732, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 465.9500420000113, "firstEventMs": 706.5951670000213, "firstReasoningMs": null, "firstContentMs": 1118.1454590000212, "lastContentMs": 1132.215292000008, "generationMs": 83.07804100000067, "totalMs": 1201.2235000000219, "visibleTokensPerSecond": 96.29500050440447, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 13.981750000006286, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-21", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:59:49.898Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "ORD-164-72", "evaluation": { "passed": true, "answer": "ORD-164-72", "expected": "ORD-164-72" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.05330951905490397, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1837, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1002.7079580000136, "firstEventMs": 1504.8817500000005, "firstReasoningMs": null, "firstContentMs": 2708.6345830000064, "lastContentMs": 2709.1157079999975, "generationMs": 141.1598750000121, "totalMs": 2849.7944580000185, "visibleTokensPerSecond": 56.67332873452398, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.21820800000568852, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-21", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:59:52.748Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-164-72", "evaluation": { "passed": true, "answer": "ORD-164-72", "expected": "ORD-164-72" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0011465427981394525, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 26, "reasoningTokens": 15, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1913, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "26", "reasoningTokens": "15", "cachedTokens": "0" }, "timing": { "headersMs": 369.2986249999958, "firstEventMs": 676.6730000000098, "firstReasoningMs": null, "firstContentMs": 2316.438125000015, "lastContentMs": 2316.647499999992, "generationMs": 0.57112499998766, "totalMs": 2317.009250000003, "visibleTokensPerSecond": 17509.30181696838, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.1052909999853, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-21", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:59:55.065Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "ORD-164-72", "evaluation": { "passed": true, "answer": "ORD-164-72", "expected": "ORD-164-72" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010685104441719615, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5038, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 73095.589041, "firstEventMs": 78336.1525, "firstReasoningMs": null, "firstContentMs": 78336.30370799999, "lastContentMs": 78336.46262499999, "generationMs": 607.6980829999957, "totalMs": 78944.00179099999, "visibleTokensPerSecond": 13.164431851597689, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.06179199999314733, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-21", "category": "easy", "arm": "smart", "at": "2026-09-26T10:01:14.010Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-164-72", "evaluation": { "passed": true, "answer": "ORD-164-72", "expected": "ORD-164-72" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004970060698852502, "classifierCostIndex": 0.0044082547277641704, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1522, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 3793.4758750000037, "firstEventMs": 4038.8647080000082, "firstReasoningMs": null, "firstContentMs": 4830.693582999986, "lastContentMs": 4830.847749999986, "generationMs": 500.0157500000205, "totalMs": 5330.709333000006, "visibleTokensPerSecond": 15.999496015874843, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.05975000001490116, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 820, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1686", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:01:19.586Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "Hello. I need to give a lecture to my students about the movie La La Land. Please help me write a lecture outline that is engaging and informative.\n\n## Lecture outline: *La La Land* — dreams, love, and the movie musical\n\n**Suggested length:** 45 minutes \n**Spoiler note:** This outline discusses the ending.\n\n### 1. Opening question: What can a musical show us? (5 minutes)\n- Ask students: “Why might a character sing or dance something they cannot easily say?”\n- Show or describe the opening freeway number, “Another Day of Sun.” Invite students to notice how an ordinary traffic jam becomes a collective performance.\n\n### 2. Story and context (5 minutes)\n- Introduce *La La Land* (2016), written and directed by Damien Chazelle.\n- Summarize the premise: Mia, an aspiring actor, and Sebastian, a jazz pianist, fall in love while pursuing careers in Los Angeles.\n- Explain that the film draws on classic Hollywood musicals while telling a contemporary story about work and ambition.\n\n### 3. How the film creates its world (10 minutes)\n- **Music and dance:** Songs express attraction, frustration, hope, and uncertainty. Compare the playful argument in “A Lovely Night” with the intimacy of “City of Stars.”\n- **Color and camera movement:** Bright costumes, carefully composed settings, and flowing camera movements make Los Angeles feel both real and dreamlike.\n- **Fantasy:** The Griffith Observatory sequence lets emotion reshape the physical world. Ask: “What does this scene communicate that ordinary dialogue could not?”\n\n### 4. Central themes (10 minutes)\n- **The cost of ambition:** Mia and Sebastian encourage each other, but their opportunities also pull them in different directions.\n- **Art versus livelihood:** Sebastian’s changing relationship with jazz raises questions about compromise, tradition, and making a living.\n- **Nostalgia:** The film celebrates older musicals and jazz. Ask students whether that affection enriches the story or limits its view of the present.\n\n### 5. Reading the ending (10 minutes)\n- Discuss the epilogue’s imagined version of Mia and Sebastian’s life together.\n- Distinguish between what *could have happened* and what did happen. The sequence honors their relationship without undoing their choices.\n- Ask: “Is the ending happy, sad, or both? What evidence supports your answer?”\n\n### 6. Closing discussion (5 minutes)\nInvite students to choose one scene and explain how **music, movement, color, or editing** changes its meaning. End with the film’s central question: **Can a dream be fulfilled even when the life surrounding it looks different from the one you imagined?**", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5217659988295418, "classifierCostIndex": 0, "promptTokens": 74, "completionTokens": 758, "reasoningTokens": 203, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 9800, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "74", "completionTokens": "758", "reasoningTokens": "203", "cachedTokens": "0" }, "timing": { "headersMs": 5085.329915999988, "firstEventMs": 5356.191916000011, "firstReasoningMs": null, "firstContentMs": 8428.024875000003, "lastContentMs": 14836.767374999996, "generationMs": 6473.460541000008, "totalMs": 14901.48541600001, "visibleTokensPerSecond": 85.58019261741251, "contentChunkCount": 549, "averageContentChunkCharacters": 4.774134790528233, "maxContentStallMs": 510.7048749999958, "finalContentBurstRatio": 0.20984357115604732, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1686", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:01:34.488Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Hello. I need to give a lecture to my students about the movie La La Land. Please help me write a lecture outline that is engaging and informative.\n\n## Lecture Outline: *La La Land*—Dreams, Romance, and the Language of Film\n\n**Suggested length:** 50 minutes \n**Focus:** How *La La Land* uses music, color, cinematography, and storytelling to explore ambition, love, and compromise. \n**Note:** This outline includes spoilers.\n\n### 1. Opening: A City in Motion (5 minutes)\n- Ask students: **What makes a city feel like a character in a movie?**\n- Show or describe the opening freeway sequence, “Another Day of Sun.”\n- Invite students to notice how the scene uses traffic, movement, color, and ensemble choreography to introduce Los Angeles as a place of possibility and frustration.\n\n### 2. Film and Story Background (5 minutes)\n- Introduce *La La Land* (2016), written and directed by Damien Chazelle.\n- The central characters are Mia, an aspiring actor, and Sebastian, a jazz pianist who dreams of opening his own club.\n- Explain that the film draws on classic Hollywood musicals while telling a contemporary story about artistic ambition and relationships.\n\n### 3. The Characters’ Dreams (8 minutes)\n- Discuss Mia’s auditions and Sebastian’s commitment to jazz.\n- Ask: **Are their dreams purely personal, or do they also reflect ideas about success and identity?**\n- Consider how each character’s ambitions change—and how their choices affect their relationship.\n\n### 4. Music and Musical Storytelling (8 minutes)\n- Explore how songs express feelings that ordinary dialogue cannot.\n- Compare the exuberance of “Another Day of Sun” with the intimacy of “City of Stars.”\n- Discuss Sebastian’s defense of jazz: What does the film suggest about preserving an art form while allowing it to evolve?\n- **Quick activity:** Have students choose a song and describe what it reveals about a character.\n\n### 5. Visual Style: Color, Light, and Movement (8 minutes)\n- Examine the film’s vivid colors, carefully composed frames, and expressive camera movement.\n- Discuss how costumes and lighting help establish mood and distinguish fantasy from everyday life.\n- Look at the planetarium sequence: How do its movement, setting, and music make the moment feel dreamlike?\n\n### 6. The Ending and the Road Not Taken (8 minutes)\n- Discuss the final imagined sequence and the reunion between Mia and Sebastian.\n- Ask: **Does the ending feel happy, sad, or both?**\n- Consider how the film presents success and love as meaningful, even when they do not lead to a shared future.\n\n### 7. Discussion and Wrap-Up (8 minutes)\nChoose one or two questions:\n- Does *La La Land* celebrate Hollywood dreams, question them, or do both?\n- How does the film balance nostalgia for classic musicals with a modern setting?\n- Which scene best communicates the film’s central ideas, and why?\n- What does the film suggest people may have to give up—or change—in order to pursue a dream?\n\n**Closing takeaway:** *La La Land* uses the visual and musical language of classic Hollywood to explore a modern tension: pursuing a dream can bring fulfillment, but it may also reshape relationships and the lives people imagine for themselves.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.03219357289787566, "classifierCostIndex": 0, "promptTokens": 74, "completionTokens": 920, "reasoningTokens": 238, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5995, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "74", "completionTokens": "920", "reasoningTokens": "238", "cachedTokens": "0" }, "timing": { "headersMs": 627.9098750000121, "firstEventMs": 1029.767125000013, "firstReasoningMs": null, "firstContentMs": 3940.683500000043, "lastContentMs": 6609.257500000007, "generationMs": 2685.194790999987, "totalMs": 6625.87829100003, "visibleTokensPerSecond": 253.61288584445313, "contentChunkCount": 125, "averageContentChunkCharacters": 25.536, "maxContentStallMs": 307.1959999999963, "finalContentBurstRatio": 0.18358395989974938, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1686", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:01:41.115Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Hello. I need to give a lecture to my students about the movie La La Land. Please help me write a lecture outline that is engaging and informative.\n\n## Lecture Outline: *La La Land*—Dreams, Love, and the Movie Musical\n\n**Suggested length:** 60 minutes \n**Spoiler notice:** This lecture discusses the film’s ending.\n\n### Learning Objectives\nBy the end of the lecture, students should be able to:\n- Explain how *La La Land* draws on and reworks the Hollywood musical.\n- Analyze how music, color, movement, and setting communicate emotion.\n- Discuss the film’s treatment of ambition, romance, nostalgia, and success.\n- Support an interpretation of the ending with specific cinematic evidence.\n\n### 1. Opening Hook: What Does Success Cost? — 5 minutes\nAsk students:\n> “Can achieving your dream require giving up another kind of happiness?”\n\nInvite a few responses, then introduce the central tension: *La La Land* presents love and ambition as mutually inspiring but not always compatible.\n\n**Optional opening clip:** “Another Day of Sun.” \nAsk students to notice the contrast between the exuberant performance and the stalled freeway traffic.\n\n### 2. Film Background and Story — 7 minutes\n- **Release:** 2016\n- **Writer and director:** Damien Chazelle\n- **Lead performers:** Emma Stone as Mia and Ryan Gosling as Sebastian\n- **Music:** Score by Justin Hurwitz; lyrics primarily by Benj Pasek and Justin Paul\n- **Premise:** An aspiring actress and a jazz pianist fall in love while pursuing uncertain careers in Los Angeles.\n- **Recognition:** The film won six Academy Awards, including Best Director and Best Actress.\n\n**Discussion prompt:** \nHow does Los Angeles function as both a place of opportunity and a source of frustration?\n\n### 3. The Movie Musical: Tradition and Reinvention — 10 minutes\n**Key idea:** The film is both a tribute to earlier musicals and a story that complicates their promises.\n\nExplore:\n- **Song and dance as emotional expression:** Characters perform feelings that ordinary dialogue cannot fully convey.\n- **Hollywood influences:** Connections to *Singin’ in the Rain* and the dream ballet of *An American in Paris*.\n- **French musical influences:** Connections to Jacques Demy’s *The Umbrellas of Cherbourg* and *The Young Girls of Rochefort*.\n- **Fantasy versus realism:** Spectacular musical sequences coexist with failed auditions, financial pressures, and relationship conflict.\n\n**Clip suggestion:** “A Lovely Night.” \nAsk: “What does the choreography reveal that the characters’ words try to deny?”\n\n### 4. Visual Storytelling: Color, Camera, and Space — 10 minutes\nFocus on three techniques:\n\n**Color and costume**\n- Saturated colors help establish the film’s heightened emotional world.\n- Invite students to interpret individual choices in context rather than assume every color has a fixed meaning.\n\n**Camera movement and choreography**\n- Flowing camera movements and extended takes connect the viewer to the performers’ bodies and shared space.\n- Contrast energetic ensemble scenes with quieter, more isolated compositions.\n\n**Setting and fantasy**\n- Locations such as Griffith Observatory turn Los Angeles into a romantic dreamscape.\n- The planetarium sequence makes emotional exhilaration visible by departing from physical realism.\n\n**Mini-activity:** \nShow a still or brief excerpt. Ask students to identify one visual choice and explain its emotional effect.\n\n### 5. Music, Jazz, and the Question of Authenticity — 10 minutes\n**Key songs and musical ideas:**\n- **“Another Day of Sun”:** Collective ambition and persistence.\n- **“City of Stars”:** Hope, longing, and uncertainty.\n- **“Audition (The Fools Who Dream)”:** Artistic vulnerability and the value of taking risks.\n- **“Mia & Sebastian’s Theme”:** A recurring melody that accumulates associations with love, memory, and loss.\n\n**Critical discussion:**\n- Sebastian wants to preserve jazz, while Keith argues that innovation is essential to its survival.\n- Does the film endorse Sebastian’s nostalgia, challenge it, or do both?\n- How does centering a white protagonist as a defender of jazz shape the film’s portrayal of a Black American art form?\n\n**Teaching point:** \nDistinguish a character’s beliefs from the film’s overall perspective.\n\n### 6. Love, Ambition, and the Ending — 13 minutes\nTrace the relationship’s development:\n1. Mia and Sebastian recognize and encourage each other’s ambitions.\n2. Work, compromise, and conflicting expectations strain their relationship.\n3. Each contributes to the other’s growth without becoming part of the other’s final everyday life.\n\n**Examine the epilogue:**\n- The imagined alternative life revisits earlier moments and changes their outcomes.\n- Music and montage invite viewers to experience a possibility that the actual story does not deliver.\n- Their final exchange of looks can support multiple readings: regret, gratitude, acceptance, or a mixture.\n\n**Small-group question:** \n> “Is the ending happy, sad, or deliberately both? Support your answer with two details from the film.”\n\n### 7. Conclusion and Exit Ticket — 5 minutes\n**Closing synthesis:** \n*La La Land* uses the pleasures of the musical—song, dance, romance, and spectacle—to explore the gap between imagined lives and lived choices. Its ending does not simply dismiss dreams; it asks what their fulfillment can include and exclude.\n\n**Exit ticket:** \nIn two or three sentences, explain how one song, visual technique, or scene develops the film’s ideas about ambition or love.\n\n### Optional Follow-Up Assignment\nWrite a 500–750-word analysis of one musical sequence. Explain how at least two formal elements—such as cinematography, editing, choreography, costume, or music—develop a central theme. Avoid plot summary; build your argument from specific details.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 4.1142535024066715, "classifierCostIndex": 0, "promptTokens": 74, "completionTokens": 1205, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 23382, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "74", "completionTokens": "1205", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 7118.414083999989, "firstEventMs": 7541.53341699997, "firstReasoningMs": null, "firstContentMs": 8384.01549999998, "lastContentMs": 30463.74887499999, "generationMs": 22127.837500000023, "totalMs": 30511.853000000003, "visibleTokensPerSecond": 54.41110094920025, "contentChunkCount": 248, "averageContentChunkCharacters": 23.31048387096774, "maxContentStallMs": 1357.830083000008, "finalContentBurstRatio": 0.15827711468604047, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1686", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:02:11.627Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "Hello. I need to give a lecture to my students about the movie La La Land. Please help me write a lecture outline that is engaging and informative.\n\nHere's a lecture outline for La La Land:\n\n**I. Introduction (5-10 minutes)**\n- Hook: Open with the \"Another Day of Sun\" opening sequence—ask students what they noticed about the single-take style\n- Brief overview: Director Damien Chazelle, release year (2016), genre (musical romance)\n- Why this film matters: Revival of the movie musical, critical/commercial success, Oscar history\n\n**II. Plot & Character Overview (10 minutes)**\n- Quick synopsis of Mia and Sebastian's relationship arc\n- Character motivations: her acting dreams, his jazz club ambitions\n- The central tension: love vs. ambition\n\n**III. Thematic Analysis (15 minutes)**\n- Dreams vs. reality\n- Compromise and sacrifice in relationships\n- Nostalgia (especially for classic Hollywood musicals and jazz)\n- The \"epilogue\" sequence—what if things had gone differently?\n\n**IV. Technical & Artistic Elements (15 minutes)**\n- Cinematography: color palette (the primary colors, especially blue/yellow), long takes, the Griffith Observatory scene\n- Music: original songs by Justin Hurwitz, use of jazz as a motif\n- Homages to classic films (Singin' in the Rain, Rebel Without a Cause, French New Wave)\n- Editing choices, especially in the finale montage\n\n**V. Historical & Cultural Context (10 minutes)**\n- The decline and revival of movie musicals\n- Los Angeles as a character itself\n- Awards season controversy (Best Picture mix-up at the Oscars)\n\n**VI. Discussion Questions / Class Activity (10-15 minutes)**\n- Was the ending realistic or overly romanticized?\n- Did the film succeed in blending old Hollywood style with modern storytelling?\n- Compare a scene to a classic musical clip (e.g., Singin' in the Rain)\n\n**VII. Conclusion (5 minutes)**\n- Recap key takeaways\n- Assign follow-up reading/viewing (interviews, related films) or a short reflective essay\n\nWould you like me to expand on any section, add specific film clips/timestamps to reference, or adjust the length for your class period?", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5510303572092532, "classifierCostIndex": 0.004540174593244215, "promptTokens": 102, "completionTokens": 789, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 10009, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "102", "completionTokens": "789", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2190.8053330000257, "firstEventMs": 3110.7032079999917, "firstReasoningMs": null, "firstContentMs": 3110.729082999984, "lastContentMs": 12225.618000000017, "generationMs": 9640.97875000001, "totalMs": 12751.707832999993, "visibleTokensPerSecond": 81.7344400847268, "contentChunkCount": 195, "averageContentChunkCharacters": 10.794871794871796, "maxContentStallMs": 904.8206670000218, "finalContentBurstRatio": 0.056532066508313536, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 204, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2752", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:02:24.618Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "*The opposite of youth* is not age, but *a lack of enthusiasm.*", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008220037425719792, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 231, "reasoningTokens": 208, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3838, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "231", "reasoningTokens": "208", "cachedTokens": "0" }, "timing": { "headersMs": 550.6438330000383, "firstEventMs": 874.0817500000121, "firstReasoningMs": 3060.449083000014, "firstContentMs": 4361.441458000045, "lastContentMs": 4363.165458000032, "generationMs": 53.71229199995287, "totalMs": 4415.153749999998, "visibleTokensPerSecond": 409.58967083399284, "contentChunkCount": 17, "averageContentChunkCharacters": 3.7058823529411766, "maxContentStallMs": 1.6424169999663718, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2752", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:02:29.033Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "The opposite of *youth* is not *age*, but **cynicism**.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2581825539066824, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 375, "reasoningTokens": 350, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5758, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "375", "reasoningTokens": "350", "cachedTokens": "0" }, "timing": { "headersMs": 452.87649999995483, "firstEventMs": 642.3911249999655, "firstReasoningMs": 3319.4945420000004, "firstContentMs": 6131.588374999992, "lastContentMs": 6134.255000000005, "generationMs": 450.2912500000093, "totalMs": 6581.879625000001, "visibleTokensPerSecond": 53.29883714151564, "contentChunkCount": 19, "averageContentChunkCharacters": 2.8947368421052633, "maxContentStallMs": 2.3446250000270084, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2752", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:02:35.616Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "The opposite of youth is not age, but *apathy*.\n\nYouth is curiosity, wonder, and the willingness to begin again. Its opposite is not growing older—it is *losing the desire to discover*.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5005522593162015, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 141, "reasoningTokens": 92, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4050, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "141", "reasoningTokens": "92", "cachedTokens": "0" }, "timing": { "headersMs": 1036.826875000028, "firstEventMs": 1749.3131250000442, "firstReasoningMs": 4175.318499999994, "firstContentMs": 4896.612792, "lastContentMs": 5062.191334000032, "generationMs": 2181.198625000019, "totalMs": 7077.811417000019, "visibleTokensPerSecond": 22.006248972396808, "contentChunkCount": 38, "averageContentChunkCharacters": 4.868421052631579, "maxContentStallMs": 162.76741700002458, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2752", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:02:42.694Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "The opposite of youth is not age, but *the loss of curiosity*.\n\nYou can grow older and remain *open to wonder, change, and possibility*.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0075433074000414825, "classifierCostIndex": 0.00441391999806086, "promptTokens": 37, "completionTokens": 83, "reasoningTokens": 45, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1881, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "83", "reasoningTokens": "45", "cachedTokens": "0" }, "timing": { "headersMs": 872.9338339999667, "firstEventMs": 1171.7202089999919, "firstReasoningMs": null, "firstContentMs": 2688.63712499995, "lastContentMs": 2737.3120839999756, "generationMs": 792.38079200004, "totalMs": 3481.01791699999, "visibleTokensPerSecond": 46.69472098965031, "contentChunkCount": 32, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 30.491125000000466, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 188, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-5", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T10:02:46.688Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "76", "evaluation": { "passed": true, "answer": "76", "expected": "76" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028341189096127102, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1985, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 322.2004580000066, "firstEventMs": 613.5165419999976, "firstReasoningMs": null, "firstContentMs": 2303.39954199997, "lastContentMs": 2303.39954199997, "generationMs": 47.83779100002721, "totalMs": 2351.2373329999973, "visibleTokensPerSecond": 83.61590107699004, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-5", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T10:02:49.040Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "76", "evaluation": { "passed": true, "answer": "76", "expected": "76" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0056801079093708635, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1225, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 271.0813339999877, "firstEventMs": 737.201166999992, "firstReasoningMs": null, "firstContentMs": 1539.8850840000086, "lastContentMs": 1539.8850840000086, "generationMs": 0.6479159999871626, "totalMs": 1540.5329999999958, "visibleTokensPerSecond": 6173.639792934969, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-5", "category": "easy", "arm": "smart", "at": "2026-09-26T10:02:50.581Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "76", "evaluation": { "passed": true, "answer": "76", "expected": "76" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.00463837261172016, "classifierCostIndex": 0.0043402714842039015, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1822, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2551.586040999973, "firstEventMs": 2897.6330829999642, "firstReasoningMs": null, "firstContentMs": 3685.049874999968, "lastContentMs": 3685.049874999968, "generationMs": 711.1430830000318, "totalMs": 4396.192958, "visibleTokensPerSecond": 5.624747108733139, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 166, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-5", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T10:02:54.977Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "76", "evaluation": { "passed": true, "answer": "76", "expected": "76" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008140453866790112, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 20, "reasoningTokens": 13, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1757, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "20", "reasoningTokens": "13", "cachedTokens": "0" }, "timing": { "headersMs": 562.4503339999937, "firstEventMs": 928.9270419999957, "firstReasoningMs": null, "firstContentMs": 2361.0204169999924, "lastContentMs": 2361.0204169999924, "generationMs": 0.15904200001386926, "totalMs": 2361.1794590000063, "visibleTokensPerSecond": 37725.88372553646, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "constrained_strings", "category": "combinatorics", "arm": "gpt-6-astra", "at": "2026-09-26T10:03:09.218Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Let \\(k\\) be the number of A characters. Since no two A’s can be adjacent, \\(0\\le k\\le 7\\).\n\nThe number of ways to choose \\(k\\) nonadjacent positions among 14 is\n\\[\n\\binom{14-k+1}{k}=\\binom{15-k}{k}.\n\\]\nFrom the remaining \\(14-k\\) positions, choose four for C; all others are B. Thus the total is\n\\[\n\\sum_{k=0}^{7}\\binom{15-k}{k}\\binom{14-k}{4}\n=1001+10010+38610+72600+69300+31752+5880+280.\n\\]\n\nFINAL: 229433", "evaluation": { "passed": true, "answer": "229433", "expected": "229433", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.7815771088710706, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 516, "reasoningTokens": 352, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 10074, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "516", "reasoningTokens": "352", "cachedTokens": "0" }, "timing": { "headersMs": 63384.224583, "firstEventMs": 67684.881292, "firstReasoningMs": null, "firstContentMs": 73422.55937500001, "lastContentMs": 73447.02929199999, "generationMs": 9577.501374999993, "totalMs": 83000.06075, "visibleTokensPerSecond": 17.019052633652077, "contentChunkCount": 75, "averageContentChunkCharacters": 5.44, "maxContentStallMs": 18.188790999993216, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "constrained_strings", "category": "combinatorics", "arm": "smart", "at": "2026-09-26T10:04:32.219Z", "model": "anthropic/claude-fable-5-1", "loggedModel": "anthropic/claude-fable-5-1", "content": "**Setup.** Choose positions for the four C's; they split the remaining 10 positions into 5 segments (possibly empty) of lengths summing to 10. Each segment of length L must be filled with A/B with no AA, which can be done in f(L) = F(L+2) ways (Fibonacci): 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144 for L = 0..10.\n\nThe answer is the coefficient of x¹⁰ in g(x)⁵ where g(x) = (1+x)/(1−x−x²).\n\n**Computing.** Let h(x) = (1−x−x²)⁻⁵ with coefficients\nh₀..h₁₀ = 1, 5, 20, 65, 190, 511, 1295, 3130, 7285, 16435, 36122.\n\nThen [x¹⁰](1+x)⁵h(x) = h₁₀ + 5h₉ + 10h₈ + 10h₇ + 5h₆ + h₅\n= 36122 + 82175 + 72850 + 31300 + 6475 + 511 = 229433.\n\nFINAL: 229433", "evaluation": { "passed": true, "answer": "229433", "expected": "229433", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 6.7131467473413755, "classifierCostIndex": 0.00448406143982939, "promptTokens": 85, "completionTokens": 1972, "reasoningTokens": 1596, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "medium", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 22776, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "85", "completionTokens": "1972", "reasoningTokens": "1596", "cachedTokens": "0" }, "timing": { "headersMs": 1774.9720830000006, "firstEventMs": 3723.971332999994, "firstReasoningMs": 6930.063416999998, "firstContentMs": 20833.518125000002, "lastContentMs": 24448.485832999984, "generationMs": 5016.015458000009, "totalMs": 25849.53358300001, "visibleTokensPerSecond": 74.76053515782434, "contentChunkCount": 57, "averageContentChunkCharacters": 11.175438596491228, "maxContentStallMs": 1507.1709580000024, "finalContentBurstRatio": 0.14913657770800628, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "high", "band": "high", "selectedModel": "claude-fable-5-1", "classifierLatencyMs": 208, "classifierFailed": false, "classifierReused": false } }, { "caseId": "constrained_strings", "category": "combinatorics", "arm": "gpt-6-sol", "at": "2026-09-26T10:04:58.069Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "If there are \\(k\\) A’s, the remaining \\(14-k\\) positions contain four C’s in \\(\\binom{14-k}{4}\\) ways. To avoid AA, place the A’s in \\(k\\) distinct gaps among the \\(15-k\\) gaps around those positions. Thus the count is\n\\[\n\\sum_{k=0}^{7}\\binom{14-k}{4}\\binom{15-k}{k}=229433.\n\\]\n\nFINAL: 229433", "evaluation": { "passed": true, "answer": "229433", "expected": "229433", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.39713342448708283, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 576, "reasoningTokens": 465, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 9323, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "576", "reasoningTokens": "465", "cachedTokens": "0" }, "timing": { "headersMs": 13954.452625000034, "firstEventMs": 14448.477249999996, "firstReasoningMs": 19501.98108400003, "firstContentMs": 22873.11508399999, "lastContentMs": 22969.34395900002, "generationMs": 159.96525000000838, "totalMs": 23033.080334, "visibleTokensPerSecond": 687.6493488429157, "contentChunkCount": 105, "averageContentChunkCharacters": 2.780952380952381, "maxContentStallMs": 66.40133299998706, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "constrained_strings", "category": "combinatorics", "arm": "gpt-6-luna", "at": "2026-09-26T10:05:21.102Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Choose \\(k\\) positions for A, with no two adjacent. There are \\(\\binom{14-k}{k}\\) ways to do so. From the remaining positions, choose 4 for C; the others are B. Thus the total is\n\\[\n\\sum_{k=0}^{7}\\binom{14-k}{k}\\binom{14-k}{4}\n=159387.\n\\]\nFINAL: 159387", "evaluation": { "passed": false, "answer": "159387", "expected": "229433", "detail": "159387 != 229433" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.024357964528002624, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 695, "reasoningTokens": 598, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6356, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "695", "reasoningTokens": "598", "cachedTokens": "0" }, "timing": { "headersMs": 5743.5315829999745, "firstEventMs": 6087.778790999961, "firstReasoningMs": 8360.512915999978, "firstContentMs": 12095.335832999961, "lastContentMs": 12095.769040999992, "generationMs": 20.106167000019923, "totalMs": 12115.44199999998, "visibleTokensPerSecond": 4774.654462976701, "contentChunkCount": 59, "averageContentChunkCharacters": 4.271186440677966, "maxContentStallMs": 0.09962500003166497, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2273", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:05:44.355Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Let the results be \\(x_1,x_2,\\ldots,x_{11}\\). The arithmetic goblin jingles its sum-bells:\n\n\\[\n\\sum_{i=1}^{11}x_i=11(51)=561,\n\\qquad\n\\sum_{i=1}^{5}x_i=5(49)=245,\n\\qquad\n\\sum_{i=3}^{11}x_i=9(52)=468.\n\\]\n\nThe first five and last nine overlap at \\(x_3,x_4,x_5\\). Thus, by the double-counting wobble-spell,\n\n\\[\nx_3+x_4+x_5=245+468-561=152.\n\\]\n\nBut no equation pins down \\(x_6\\). Indeed, the sneaky transformation\n\\[\nx_6\\mapsto x_6+t,\\qquad x_7\\mapsto x_7-t\n\\]\nleaves all three given averages unchanged.\n\n**Therefore, the sixth result cannot be uniquely determined.**\n\nP.P.S. The number-gremlins demand another independent clue!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.5144488233911406, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 436, "reasoningTokens": 199, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 9233, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "436", "reasoningTokens": "199", "cachedTokens": "0" }, "timing": { "headersMs": 301.52504100004444, "firstEventMs": 612.9420000000391, "firstReasoningMs": null, "firstContentMs": 6199.2871249999735, "lastContentMs": 9529.174500000023, "generationMs": 3338.841916000005, "totalMs": 9538.129040999978, "visibleTokensPerSecond": 70.68319074019905, "contentChunkCount": 91, "averageContentChunkCharacters": 6.846153846153846, "maxContentStallMs": 789.6681249999674, "finalContentBurstRatio": 0.3996789727126806, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2273", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:05:53.894Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# The Curious Case of the Sixth Result 🎩\n\nBehold, ye seekers of numerical truth! Let us summon the arcane symbols to vanquish this puzzle.\n\n**The Grand Total Incantation:**\n\n$$\\sum_{i=1}^{11} x_i = 11 \\times 51 = 561$$\n\n**The First Coven of Five:**\n\n$$\\sum_{i=1}^{5} x_i = 5 \\times 49 = 245$$\n\n**The Latter Assembly of Nine:**\n\n$$\\sum_{i=3}^{11} x_i = 9 \\times 52 = 468$$\n\nNow, prithee note — the sixth result, $x_6$, doth lurk within *both* summonings above (since the \"last nine\" spans results 3 through 11). This means we may combine the two group-sums thusly:\n\n$$\\sum_{i=1}^{5} x_i + \\sum_{i=3}^{11} x_i = 245 + 468 = 713$$\n\nBut wait! In this combined incantation, results 3, 4, and 5 have been counted **twice** — the mischievous duplicands! Let us define:\n\n$$S = \\sum_{i=1}^{11} x_i + (x_3 + x_4 + x_5)$$\n\nHmm, this path grows thorny. Let us instead invoke the *cleaner ritual*:\n\n$$x_6 = \\Big(\\sum_{i=1}^{5} x_i + \\sum_{i=6}^{11} x_i\\Big) - \\sum_{i=1}^{5} x_i - \\sum_{i=6}^{11} x_i + x_6$$\n\nNay, let us abandon such recursive madness and simply decree:\n\n$$x_6 = \\left(\\sum_{i=1}^{5} x_i\\right) + \\left(\\sum_{i=6}^{11} x_i\\right) - \\sum_{i=1}^{11} x_i + x_6 \\cdot 0$$\n\n**The True Simple Path:**\n\nSince $\\sum_{i=1}^{5} x_i + \\sum_{i=6}^{11} x_i = \\sum_{i=1}^{11} x_i$, we get:\n\n$$245 + \\sum_{i=6}^{11} x_i = 561 \\implies \\sum_{i=6}^{11} x_i = 316$$\n\nThe \"last nine\" (positions 3–11) sum to 468, so positions 3, 4, 5 sum to:\n\n$$468 - \\sum_{i=6}^{11} x_i = 468 - 316 = 152$$\n\nBut positions 1–5 sum to 245, so positions 1, 2 sum to $245 - 152 = 93$... \n\nActually — the tidiest incantation is simply:\n\n$$x_6 = \\left(\\sum_{i=1}^{5}x_i\\right) + \\left(\\sum_{i=6}^{11}x_i\\right) - \\left(\\sum_{i=1}^{11}x_i\\right)$$\n\nis wrong since 6-11 isn't \"last nine.\" The clean way:\n\n$$x_6 = \\text{(Total)} - \\text{(First 5)} - \\text{(Results 7 to 11)}$$\n\nSince results 7–11 (five terms) plus $x_6$ equal the \"last nine\" (results 3–11, nine terms)... \n\n**FORGET THE LABYRINTH — direct sorcery:**\n\n$$x_6 = (\\text{Sum of first 6}) - (\\text{Sum of first 5})$$\n\nWe need Sum of first 6. Note Total = Sum(1–5) + Sum(6–11):\n\n$$561 = 245 + \\text{Sum}(6\\text{–}11) \\implies \\text{Sum}(6\\text{–}11) = 316$$\n\nAlso Total = Sum(1–2) + Sum(3–11):\n\n$$561 = \\text{Sum}(1\\text{–}2) + 468 \\implies \\text{Sum}(1\\text{–}2) = 93$$\n\nThen Sum(3–5) = Sum(1–5) − Sum(1–2) = 245 − 93 = **152**\n\nAnd $x_6$ = Sum(6–11) − Sum(7–11)... we lack Sum(7–11) directly, BUT:\n\nSum(3–11) = Sum(3–5) + $x_6$ + Sum(7–11) = 468\nSum(6–11) = $x_6$ + Sum(7–11) = 316\n\nSubtracting: Sum(3–5) = 468 − 316 = 152 ✓ (consistent, no new info)\n\n**The Actual Resolution:**\n\n$$x_6 = \\text{Sum}(6\\text{-}11) - \\text{Sum}(7\\text{-}11)$$\n\nAlas, we require one more clue... but by convention, this classic puzzle assumes **overlap only at position 6** (first 5 + last 9 = 14, minus 11 total = 3 overlap... wait, that means 3 results overlap, not 1)!\n\n**Recomputing the overlap properly:**\n\n$$5 + 9 - 11 = 3 \\text{ overlapping results (positions 3, 4, 5)}$$\n\nSo: $$245 + 468 - 561 = 152 = x_3 + x_4 + x_5$$\n\nThe puzzle, as classically posed, intends the \"sixth result\" loosely as *the value shared in the overlap* when overlap is exactly one term — meaning the intended reading is **first six** & **last six**, not five/nine. Under the *traditional textbook fram", "evaluation": { "passed": false, "answer": "0", "expected": "all instructions followed", "detail": "Failed: detectable_content:postscript", "score": 0, "metrics": { "instructionsPassed": 0, "instructionsTotal": 1 } }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 1.5493597027206065, "classifierCostIndex": 0.0045261463048905095, "promptTokens": 81, "completionTokens": 1, "reasoningTokens": null, "cachedInputTokens": 0, "finishReason": null, "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 103050, "loggedFinishReason": "canceled", "billedUsage": { "promptTokens": "81", "completionTokens": "2272", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 77603.80987499992, "firstEventMs": 80880.66579200001, "firstReasoningMs": null, "firstContentMs": 80880.69112500001, "lastContentMs": 179800.52000000002, "generationMs": 99122.36774999998, "totalMs": 180003.058875, "visibleTokensPerSecond": 0, "contentChunkCount": 362, "averageContentChunkCharacters": 9.08011049723757, "maxContentStallMs": 6610.52679100004, "finalContentBurstRatio": 0.3547307575296623, "buffered": false }, "error": { "code": "stream_read_error" }, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 4316, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2273", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:10:48.919Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "The sums do a little overlap goblin-dance:\n\\[\nS_{1\\ldots11}=11(51)=561,\\quad\nS_{1\\ldots5}=5(49)=245,\\quad\nS_{3\\ldots11}=9(52)=468.\n\\]\nSo the three results counted twice must total\n\\[\nS_{3\\ldots5}=245+468-561=152.\n\\]\n\nBut the sixth result is **not** one of those overlap goblins. We know only that results 6 through 11 total \\(561-245=316\\), so the sixth result **cannot be determined**.\n\nP.P.S. The sixth result could be \\(51\\) or \\(52\\), with the other five results adjusting to keep their total at \\(316\\).", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3463672071332282, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 500, "reasoningTokens": 327, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7047, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "500", "reasoningTokens": "327", "cachedTokens": "0" }, "timing": { "headersMs": 2433.347292, "firstEventMs": 2696.9671249999997, "firstReasoningMs": 6937.165333999999, "firstContentMs": 8341.714958999999, "lastContentMs": 9374.882416999999, "generationMs": 1136.904458000001, "totalMs": 9478.619417, "visibleTokensPerSecond": 151.28799855581167, "contentChunkCount": 167, "averageContentChunkCharacters": 3.0419161676646707, "maxContentStallMs": 539.7414170000011, "finalContentBurstRatio": 0.6082677165354331, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2273", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:10:58.399Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "The totals are\n\\[\nS_{1:11}=11(51)=561,\\qquad S_{1:5}=5(49)=245,\\qquad S_{3:11}=9(52)=468.\n\\]\nThus the overlapping trio, results \\(3\\) through \\(5\\), sums to\n\\[\nS_{3:5}=245+468-561=152.\n\\]\nBut the sixth result is merely one pebble in the last-nine pile; its individual value is not pinned down.\n\nFor example, both lists satisfy the given averages:\n\\[\n(46,47,50,51,51,\\boxed{52},52,52,53,53,53)\n\\]\nand\n\\[\n(46,47,50,51,51,\\boxed{53},51,53,53,53,53).\n\\]\nSo the sixth result could be \\(52\\), \\(53\\), or other values—there isn’t enough information to determine it uniquely.\n\nP.P.S. The averages have revealed the herd’s total weight, but not the sixth goat’s personal wobble.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.02631383165424052, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 751, "reasoningTokens": 516, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5097, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "751", "reasoningTokens": "516", "cachedTokens": "0" }, "timing": { "headersMs": 11200.743541999998, "firstEventMs": 11589.077457999998, "firstReasoningMs": null, "firstContentMs": 15891.652375, "lastContentMs": 16261.748417, "generationMs": 411.7243329999983, "totalMs": 16303.376707999998, "visibleTokensPerSecond": 568.3414392707292, "contentChunkCount": 86, "averageContentChunkCharacters": 7.77906976744186, "maxContentStallMs": 141.4169580000016, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "assignment", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T10:12:43.200Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "FINAL: 21", "evaluation": { "passed": true, "answer": "21", "expected": "21", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5579886580074674, "classifierCostIndex": 0, "promptTokens": 142, "completionTokens": 798, "reasoningTokens": 788, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 11187, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "142", "completionTokens": "798", "reasoningTokens": "788", "cachedTokens": "0" }, "timing": { "headersMs": 31205.971583, "firstEventMs": 34525.168458, "firstReasoningMs": 35834.775042, "firstContentMs": 42266.496625, "lastContentMs": 42309.458792, "generationMs": 3361.822042, "totalMs": 45628.318667, "visibleTokensPerSecond": 2.6771196950823017, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 22.669083000000683, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "assignment", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T10:13:28.829Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 21", "evaluation": { "passed": true, "answer": "21", "expected": "21", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04783241666449779, "classifierCostIndex": 0, "promptTokens": 142, "completionTokens": 1360, "reasoningTokens": 1350, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7961, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "142", "completionTokens": "1360", "reasoningTokens": "1350", "cachedTokens": "0" }, "timing": { "headersMs": 4520.914500000006, "firstEventMs": 5137.556542000006, "firstReasoningMs": null, "firstContentMs": 12203.172750000005, "lastContentMs": 12238.200625000005, "generationMs": 253.0839169999963, "totalMs": 12456.256667000001, "visibleTokensPerSecond": 35.56132727311998, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 27.288042000000132, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "assignment", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T10:13:41.287Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "An optimal worker-to-job assignment is \\(1\\to2,\\ 2\\to1,\\ 3\\to3,\\ 4\\to5,\\ 5\\to4,\\ 6\\to6\\), costing \\(5+2+3+1+3+7=21\\).\n\nFINAL: 21", "evaluation": { "passed": true, "answer": "21", "expected": "21", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 2.035259819513526, "classifierCostIndex": 0, "promptTokens": 142, "completionTokens": 575, "reasoningTokens": 504, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 10652, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "142", "completionTokens": "575", "reasoningTokens": "504", "cachedTokens": "0" }, "timing": { "headersMs": 4965.933124999996, "firstEventMs": 5272.901749999997, "firstReasoningMs": 14695.05225, "firstContentMs": 15414.211374999992, "lastContentMs": 15546.136250000003, "generationMs": 4483.167207999999, "totalMs": 19897.37858299999, "visibleTokensPerSecond": 15.613961459007891, "contentChunkCount": 48, "averageContentChunkCharacters": 2.6666666666666665, "maxContentStallMs": 86.40958300000057, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "assignment", "category": "algorithms", "arm": "smart", "at": "2026-09-26T10:14:01.185Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "Looking at the cost matrix, I need to find an optimal one-to-one assignment.\n\n**Testing an assignment:**\n- Worker 4 → Job 5 (cost 1)\n- Worker 2 → Job 1 (cost 2)\n- Worker 1 → Job 2 (cost 5)\n- Worker 3 → Job 3 (cost 3)\n- Worker 5 → Job 4 (cost 3)\n- Worker 6 → Job 6 (cost 7)\n\nTotal = 1+2+5+3+3+7 = **21**\n\n**Verification via Hungarian Algorithm:**\n\nRow reduction (subtract row minima: 5,2,3,1,3,4):\n```\n9 0 3 2 10 4\n0 10 4 3 1 9\n4 5 0 6 4 3\n1 3 5 9 0 7\n6 4 2 0 5 1\n2 6 0 4 1 2\n```\n\nColumn reduction (col6 min=1, others already 0):\n```\n9 0 3 2 10 3\n0 10 4 3 1 8\n4 5 0 6 4 2\n1 3 5 9 0 6\n6 4 2 0 5 0\n2 6 0 4 1 2\n```\n\nMinimum line cover of zeros uses 5 lines (cols 1,2,3,5 and row 5), less than 6, so further adjustment needed. The minimum uncovered value is 2. Subtracting 2 from uncovered elements and adding 2 to doubly-covered elements gives:\n\n```\n9 0 3 0 10 1\n0 10 4 1 1 6\n4 5 0 4 4 0\n1 3 5 7 0 4\n8 6 4 0 7 0\n2 6 0 2 1 0\n```\n\nNow a perfect zero-cost matching exists:\n- W1→Job2, W2→Job1, W3→Job3, W4→Job5, W5→Job4, W6→Job6\n\nThis matches the assignment found earlier, confirming optimality.\n\nTotal reduction sum: (5+2+3+1+3+4) + 1 + 2 = 21, consistent with the computed cost.\n\n**Minimum total cost = 21**\n\nFINAL: 21", "evaluation": { "passed": true, "answer": "21", "expected": "21", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 2.5442513082609737, "classifierCostIndex": 0.0047891767115225015, "promptTokens": 182, "completionTokens": 3725, "reasoningTokens": 3010, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 32066, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "182", "completionTokens": "3725", "reasoningTokens": "3010", "cachedTokens": "0" }, "timing": { "headersMs": 839.0989580000023, "firstEventMs": 1861.6332910000056, "firstReasoningMs": 4138.396540999995, "firstContentMs": 28999.285040999996, "lastContentMs": 32879.362582999995, "generationMs": 3909.451375000004, "totalMs": 32908.736416, "visibleTokensPerSecond": 182.63432167640127, "contentChunkCount": 112, "averageContentChunkCharacters": 11.571428571428571, "maxContentStallMs": 425.06595799999195, "finalContentBurstRatio": 0.6550925925925926, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 281, "classifierFailed": false, "classifierReused": false } }, { "caseId": "number_theory_crt", "category": "math", "arm": "gpt-6-luna", "at": "2026-09-26T10:14:34.353Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Write \\(x=11+37a\\). The second congruence gives \\(a\\equiv19\\pmod{41}\\), so \\(x=714+1517b\\) for some integer \\(b\\). The third congruence then gives \\(12b\\equiv3\\pmod{43}\\), hence \\(b\\equiv11\\pmod{43}\\). Taking \\(b=11\\) yields \\(x=17401\\), which lies between \\(0\\) and \\(37\\cdot41\\cdot43=65231\\), so it is the smallest nonnegative solution.\n\nFINAL: 17401", "evaluation": { "passed": true, "answer": "17401", "expected": "17401", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.021191483094317492, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 601, "reasoningTokens": 461, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6420, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "601", "reasoningTokens": "461", "cachedTokens": "0" }, "timing": { "headersMs": 6888.949165999991, "firstEventMs": 7195.837082999991, "firstReasoningMs": 13342.804457999999, "firstContentMs": 13374.343666, "lastContentMs": 13389.512915999992, "generationMs": 41.05524999999034, "totalMs": 13415.398915999991, "visibleTokensPerSecond": 3385.681490187801, "contentChunkCount": 69, "averageContentChunkCharacters": 5.101449275362318, "maxContentStallMs": 2.585333000009996, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "number_theory_crt", "category": "math", "arm": "smart", "at": "2026-09-26T10:14:47.769Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 17401", "evaluation": { "passed": true, "answer": "17401", "expected": "17401", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2832733616137781, "classifierCostIndex": 0.004536667521155789, "promptTokens": 94, "completionTokens": 394, "reasoningTokens": 384, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6632, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "94", "completionTokens": "394", "reasoningTokens": "384", "cachedTokens": "0" }, "timing": { "headersMs": 1052.473708000005, "firstEventMs": 1869.624542000005, "firstReasoningMs": 3875.363083000004, "firstContentMs": 7607.195500000002, "lastContentMs": 7607.19991700002, "generationMs": 16.000250000011874, "totalMs": 7623.1957500000135, "visibleTokensPerSecond": 562.4912110744095, "contentChunkCount": 2, "averageContentChunkCharacters": 6, "maxContentStallMs": 0.004417000018293038, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 271, "classifierFailed": false, "classifierReused": false } }, { "caseId": "number_theory_crt", "category": "math", "arm": "gpt-6-astra", "at": "2026-09-26T10:14:55.393Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Write \\(x=11+37a\\). Modulo \\(41\\),\n\\[\n-4a\\equiv6\\pmod{41}\\quad\\Rightarrow\\quad a\\equiv19\\pmod{41}.\n\\]\nThus \\(x=714+1517b\\). Modulo \\(43\\),\n\\[\n26+12b\\equiv29\\pmod{43}\\quad\\Rightarrow\\quad b\\equiv11\\pmod{43}.\n\\]\nHence all solutions are\n\\[\nx=17401+65231k,\\qquad k\\in\\mathbb Z,\n\\]\nso the smallest nonnegative solution is:\n\nFINAL: 17401", "evaluation": { "passed": true, "answer": "17401", "expected": "17401", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.177165607403877, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 335, "reasoningTokens": 186, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5646, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "335", "reasoningTokens": "186", "cachedTokens": "0" }, "timing": { "headersMs": 495.12162499999977, "firstEventMs": 802.5560839999816, "firstReasoningMs": null, "firstContentMs": 5002.491791999986, "lastContentMs": 6077.666874999995, "generationMs": 1090.3621670000139, "totalMs": 6092.853959, "visibleTokensPerSecond": 135.73471684844154, "contentChunkCount": 72, "averageContentChunkCharacters": 4.597222222222222, "maxContentStallMs": 187.9161670000176, "finalContentBurstRatio": 0.540785498489426, "buffered": false }, "error": null, "routing": null }, { "caseId": "number_theory_crt", "category": "math", "arm": "gpt-6-sol", "at": "2026-09-26T10:15:01.486Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "FINAL: 17401", "evaluation": { "passed": true, "answer": "17401", "expected": "17401", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.17691694924843818, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 248, "reasoningTokens": 237, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4530, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "248", "reasoningTokens": "237", "cachedTokens": "0" }, "timing": { "headersMs": 311.17687499997555, "firstEventMs": 645.6427089999779, "firstReasoningMs": null, "firstContentMs": 4641.944374999992, "lastContentMs": 4642.0717920000025, "generationMs": 208.1229170000006, "totalMs": 4850.067291999992, "visibleTokensPerSecond": 48.04852893734894, "contentChunkCount": 5, "averageContentChunkCharacters": 2.4, "maxContentStallMs": 0.036124999984167516, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-13", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T10:15:06.564Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-108-ready", "evaluation": { "passed": true, "answer": "gateway-108-ready", "expected": "gateway-108-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0004458028173942223, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2615, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 215.67129200001364, "firstEventMs": 1814.3127500000119, "firstReasoningMs": null, "firstContentMs": 2656.545207999996, "lastContentMs": 2662.6019169999927, "generationMs": 178.16541700001108, "totalMs": 2834.710625000007, "visibleTokensPerSecond": 39.28933076838119, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 4.436167000007117, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-13", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T10:15:09.400Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "gateway-108-ready.", "evaluation": { "passed": false, "answer": "gateway-108-ready.", "expected": "gateway-108-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04588329390766073, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3267, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1131.1423329999961, "firstEventMs": 4611.135416999983, "firstReasoningMs": null, "firstContentMs": 4611.294041999994, "lastContentMs": 4611.972416999983, "generationMs": 501.13000000000466, "totalMs": 5112.424041999999, "visibleTokensPerSecond": 15.963921537325497, "contentChunkCount": 5, "averageContentChunkCharacters": 3.6, "maxContentStallMs": 0.6378329999861307, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-13", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T10:15:14.513Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "gateway-108-ready", "evaluation": { "passed": true, "answer": "gateway-108-ready", "expected": "gateway-108-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008518812990176131, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1233, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 331.86779200000456, "firstEventMs": 652.3789169999945, "firstReasoningMs": null, "firstContentMs": 1082.4772499999963, "lastContentMs": 1751.8368750000081, "generationMs": 669.6649170000164, "totalMs": 1752.1421670000127, "visibleTokensPerSecond": 10.452988983443833, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 574.9971249999944, "finalContentBurstRatio": 0.35294117647058826, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-13", "category": "easy", "arm": "smart", "at": "2026-09-26T10:15:16.265Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-108-ready", "evaluation": { "passed": true, "answer": "gateway-108-ready", "expected": "gateway-108-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004814130878305537, "classifierCostIndex": 0.004368328060911314, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1176, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 855.1153340000019, "firstEventMs": 1330.6161670000001, "firstReasoningMs": null, "firstContentMs": 1946.592416999978, "lastContentMs": 1946.733916999976, "generationMs": 91.31879200000549, "totalMs": 2037.9112089999835, "visibleTokensPerSecond": 76.65454006443251, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 0.08116699999663979, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 194, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2691", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:15:18.463Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "\"Dear Darius,\n\nI heard you're the one reading these cover letters, which is great news, because I wrote this one specifically to make you laugh instead of putting you into the kind of coma usually induced by phrases like \"results-driven synergy expert.\"\n\nLet me put it plainly: I want to work in Ventura. I want it so badly that I've already imagined myself eating a burrito on the beach during my lunch break, pretending to think deep thoughts about the ocean while actually just thinking about the burrito. Ventura seems like the kind of place where work-life balance isn't just a buzzword—it's a lifestyle involving surfboards, sunsets, and a suspiciously high number of avocado-based meals.\n\nAs for my qualifications, I promise they're real, even though this letter is mostly jokes. I'm hardworking, dependable, and possess a rare ability to stay calm under pressure—unless someone puts pineapple on pizza in front of me, at which point all bets are off. I show up on time, I meet deadlines, and I can make even the most tedious meeting slightly more bearable with a well-timed joke (see: this entire letter).\n\nI also work well in teams, mostly because I've learned that bringing donuts to the office solves roughly 90% of interpersonal conflicts. The other 10% usually requires pizza.\n\nDarius, I know you're busy, probably fending off cover letters that open with \"To Whom It May Concern\" like it's still 1987. So thank you for reading this far. If you decide to bring me in for an interview, I promise to bring actual donuts, not just metaphorical ones.\n\nThank you for your consideration, and for laughing (hopefully) at least once while reading this.\n\nWarm regards,\n[Your Name]\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3887105164297863, "classifierCostIndex": 0.004406905853884006, "promptTokens": 56, "completionTokens": 558, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8522, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "56", "completionTokens": "558", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 769.3582919999899, "firstEventMs": 1384.6449169999978, "firstReasoningMs": null, "firstContentMs": 1384.6989999999932, "lastContentMs": 9165.982292, "generationMs": 7841.850459000008, "totalMs": 9226.549459000002, "visibleTokensPerSecond": 71.02915350301497, "contentChunkCount": 171, "averageContentChunkCharacters": 9.853801169590643, "maxContentStallMs": 628.8402089999872, "finalContentBurstRatio": 0.13293768545994064, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 202, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2691", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:15:27.691Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "\"Dear Darius,\n\nI’m excited to apply for the [Job Title] position at [Company] in Ventura. The opportunity caught my attention for three reasons: the work sounds meaningful, the team sounds like one I’d enjoy contributing to, and Ventura has a strong case for being the best place to take a lunch break.\n\nI’d bring a thoughtful approach, dependable follow-through, and a willingness to tackle the unglamorous tasks as well as the exciting ones. I’m eager to learn what matters most to your team and show you how I can help.\n\nI’d welcome the chance to talk. Thank you for your time and consideration—and I promise not to spend the entire interview discussing the beach.\n\nBest,\n[Your Name]\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1845954138112721, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 266, "reasoningTokens": 112, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5254, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "266", "reasoningTokens": "112", "cachedTokens": "0" }, "timing": { "headersMs": 356.6777079999738, "firstEventMs": 677.288332999975, "firstReasoningMs": null, "firstContentMs": 4134.895166999981, "lastContentMs": 5513.3737919999985, "generationMs": 1498.1408750000119, "totalMs": 5633.036041999992, "visibleTokensPerSecond": 102.12657738211621, "contentChunkCount": 148, "averageContentChunkCharacters": 4.641891891891892, "maxContentStallMs": 293.9901249999821, "finalContentBurstRatio": 0.2052401746724891, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2691", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:15:33.325Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"Dear Hiring Manager,\n\nI’m excited to apply for the [Job Title] position at [Company] in Ventura. I bring a strong work ethic, a knack for solving problems, and the kind of reliability that makes people say, ‘Thank goodness—we don’t have to figure this out twice.’\n\nI’m drawn to this opportunity because it’s a chance to contribute to a team doing meaningful work in a place where even the commute can come with an ocean view. I’m organized, adaptable, and happy to roll up my sleeves—whether the task is a major project or tracking down the mysterious meeting invite everyone swears they never received.\n\nI’d love to bring my skills, good humor, and commitment to doing excellent work to your team. Thank you for considering my application. I’d welcome the chance to talk about how I can help [Company] succeed—and, if Darius is involved in the hiring process, earn at least one approving nod.\n\nSincerely, \n[Your Name]\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.013104309745793859, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 373, "reasoningTokens": 168, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3069, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "373", "reasoningTokens": "168", "cachedTokens": "0" }, "timing": { "headersMs": 273.90474999998696, "firstEventMs": 603.4191249999858, "firstReasoningMs": null, "firstContentMs": 2952.278540999978, "lastContentMs": 3334.4887909999816, "generationMs": 394.48083400001633, "totalMs": 3346.759374999994, "visibleTokensPerSecond": 517.135390156855, "contentChunkCount": 82, "averageContentChunkCharacters": 11.231707317073171, "maxContentStallMs": 117.91233299998567, "finalContentBurstRatio": 0.8859934853420195, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2691", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:15:36.672Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "\"Dear Darius,\n\nI’m excited to apply for the [Job Title] position at [Company Name] in Ventura. The opportunity to contribute to your team, grow professionally, and work somewhere with an ocean breeze feels almost suspiciously good—but I’ve decided not to question it.\n\nMy experience in [relevant field or skill] has prepared me to tackle challenges, communicate clearly, and keep projects moving when priorities change. At [Previous Company or Organization], I [briefly describe a relevant achievement]. I’d welcome the chance to bring that same initiative to your team, along with the rare workplace ability to ask whether a meeting could, in fact, be an email.\n\nWhat interests me most about [Company Name] is [specific detail about the company or its work]. I’m looking for a role where I can make a meaningful contribution, learn from good people, and become someone colleagues can count on—not just someone who knows where the good snacks are. Though I intend to learn that too.\n\nThank you for considering my application. I’d love to discuss how my skills could support your team’s goals. I’m happy to work around your schedule and will plan around the 101’s occasional commitment to testing everyone’s character.\n\nBest regards,\n[Your Name]\n[Phone Number]\n[Email Address]\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.0806840309404422, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 313, "reasoningTokens": 46, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7850, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "313", "reasoningTokens": "46", "cachedTokens": "0" }, "timing": { "headersMs": 729.1762919999892, "firstEventMs": 1001.2889999999898, "firstReasoningMs": null, "firstContentMs": 4316.801749999984, "lastContentMs": 8309.043375000008, "generationMs": 4051.162083000003, "totalMs": 8367.963832999987, "visibleTokensPerSecond": 65.66017220496379, "contentChunkCount": 99, "averageContentChunkCharacters": 12.88888888888889, "maxContentStallMs": 519.1933330000029, "finalContentBurstRatio": 0.14106583072100312, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1658", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:15:45.298Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"JORDAN [LAST NAME]\n[City, State] | [Phone] | [Email] | [LinkedIn or Portfolio]\n\nCOLLEGE STUDENT\n\nSUMMARY\nMotivated college student seeking an opportunity to build professional experience and contribute strong organization, communication, and problem-solving skills. Interested in developing technical skills and learning from a collaborative team.\n\nEDUCATION\n[College or University], [City, State]\nBachelor of [Degree or Intended Major] | Expected Graduation: [Month Year]\nGPA: [GPA, if you wish to include it]\nRelevant coursework: [Course Name], [Course Name], [Course Name]\n\nSKILLS\n• Programming: Python, Java\n• [Microsoft Office / Google Workspace]\n• Written and verbal communication\n• Organization and time management\n• Teamwork and problem-solving\n\nACADEMIC PROJECTS\n[Project Name] | [Course or Personal Project] | [Month Year]\n• Describe a class or personal project, your contribution, and the tools you used.\n• Include a specific result or skill demonstrated, if applicable.\n\n[Project Name] | [Course or Personal Project] | [Month Year]\n• Describe another relevant project or assignment.\n• Highlight research, collaboration, presentation, or technical skills.\n\nEXPERIENCE\nNo formal work experience yet. Eager to learn and contribute through an entry-level opportunity.\n\nACTIVITIES & INTERESTS\n[Student club, volunteer activity, sport, or personal interest]\n• [Describe your participation or responsibilities, if applicable.]\"\n", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.019553410654246258, "classifierCostIndex": 0.00442444121432614, "promptTokens": 41, "completionTokens": 431, "reasoningTokens": 115, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4080, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "431", "reasoningTokens": "115", "cachedTokens": "0" }, "timing": { "headersMs": 562.1878340000112, "firstEventMs": 866.2897090000042, "firstReasoningMs": 3018.0362920000043, "firstContentMs": 3750.424167000019, "lastContentMs": 4638.891709000018, "generationMs": 916.5667499999981, "totalMs": 4666.990917000017, "visibleTokensPerSecond": 343.6738240831894, "contentChunkCount": 97, "averageContentChunkCharacters": 14.783505154639176, "maxContentStallMs": 521.2912500000093, "finalContentBurstRatio": 0.07601115760111576, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 215, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1658", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:15:49.967Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "\"[Your Name]\n[City, State] | [Phone] | [Email] | [LinkedIn or GitHub]\n\nSUMMARY\nCollege student seeking an internship or entry-level opportunity. Interested in applying Python and Java skills while gaining hands-on experience.\n\nEDUCATION\n[College Name] — [Degree and Major]\nExpected graduation: [Month Year]\nRelevant coursework: [List applicable courses]\n\nTECHNICAL SKILLS\nProgramming: Python, Java\nTools: [List tools you have used]\n\nACADEMIC PROJECTS\n[Project Name] | [Course or Date]\n• [Describe what you built, the skills you used, and the result.]\n\n[Project Name] | [Course or Date]\n• [Describe your contribution and what you learned.]\n\nACTIVITIES\n[Club, volunteer role, or campus activity]\n• [Describe a contribution or responsibility.]\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.24859813055117663, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 360, "reasoningTokens": 179, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4967, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "360", "reasoningTokens": "179", "cachedTokens": "0" }, "timing": { "headersMs": 297.4480829999957, "firstEventMs": 686.9983749999956, "firstReasoningMs": null, "firstContentMs": 3573.034874999983, "lastContentMs": 5314.6374999999825, "generationMs": 1741.993416000012, "totalMs": 5315.028290999995, "visibleTokensPerSecond": 103.32989685650956, "contentChunkCount": 175, "averageContentChunkCharacters": 4.234285714285714, "maxContentStallMs": 479.1126660000009, "finalContentBurstRatio": 0.07827260458839407, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1658", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:15:55.283Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "\"# [Your Name]\n[City, State] | [Phone Number] | [Email Address] | [LinkedIn or GitHub URL]\n\n## PROFESSIONAL SUMMARY\nMotivated college student seeking an internship or entry-level opportunity to develop technical and professional skills. Interested in programming with Python and Java and eager to contribute through collaboration, problem-solving, and a willingness to learn.\n\n## EDUCATION\n**[College or University Name]** — [City, State] \n[Degree and Major] | Expected Graduation: [Month, Year]\n- Relevant coursework: [List completed or current courses]\n- GPA: [Include if desired]\n- Honors: [Include any academic awards]\n\n## SKILLS\n- **Programming:** Python, Java — [Describe your current proficiency]\n- **Tools:** [List software or tools you have used]\n- **Professional skills:** [Include strengths you can demonstrate, such as teamwork, organization, or communication]\n\n## ACADEMIC AND PERSONAL PROJECTS\n**[Project Name]** | [Course or Personal Project]\n- Created [describe what you made] using [Python, Java, or another tool].\n- Applied [specific concept or skill] to solve [problem].\n- Achieved [result or learning outcome].\n\n**[Class Assignment or Group Project]** | [Course Name]\n- Contributed to [describe the assignment and your role].\n- Collaborated with [number] classmates to complete [deliverable].\n- Presented [findings or results] through [report, demonstration, or presentation].\n\n## CAMPUS INVOLVEMENT AND VOLUNTEERING\n**[Club, Student Organization, or Volunteer Activity]** | [Dates]\n- Participated in [activity or responsibility].\n- Supported [event, initiative, or community need] by [specific contribution].\n\n*Replace bracketed text with accurate details and remove any sections or skills that do not apply. Formal work experience and age do not need to be listed.*\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.3700775031233008, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 398, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7120, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "398", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 508.5672499999928, "firstEventMs": 917.0309159999888, "firstReasoningMs": null, "firstContentMs": 1531.2713750000112, "lastContentMs": 7549.859790999995, "generationMs": 6040.9534579999745, "totalMs": 7572.224832999986, "visibleTokensPerSecond": 65.71810273993368, "contentChunkCount": 122, "averageContentChunkCharacters": 14.663934426229508, "maxContentStallMs": 776.1568750000151, "finalContentBurstRatio": 0.1218557853549469, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1658", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:16:02.856Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"JORDAN TAYLOR\n[City, State] • [Email Address] • [Phone Number] • [LinkedIn or GitHub URL]\n\nCOLLEGE STUDENT\nMotivated college student seeking an internship or entry-level opportunity to apply classroom learning, strengthen technical skills, and contribute to a collaborative team. Interested in software development and eager to learn.\n\nEDUCATION\n[College or University], [City, State]\n[Degree or Major], Expected [Month Year]\nCurrently in second year\nRelevant coursework: [Course Name], [Course Name], [Course Name]\n\nPROJECTS\n[Course or Personal Project Name] | [Month Year]\n• Built [brief description of project] using Python.\n• Applied problem-solving skills to [specific task or feature].\n• Tested and revised the project based on [requirements or feedback].\n\n[Course or Personal Project Name] | [Month Year]\n• Created [brief description of project] using Java.\n• Used [relevant concept or tool] to [specific result].\n• Collaborated with [team members, if applicable] to complete the project.\n\nSKILLS\nProgramming: Python, Java\nTools: [Git, Excel, or other tools you use]\nWorkplace: Communication, teamwork, organization, time management\n\nCAMPUS & COMMUNITY INVOLVEMENT\n[Club, Volunteer Group, or Campus Activity] | [Month Year–Present]\n• [Describe a contribution, responsibility, or achievement.]\n• [Add another relevant detail, if applicable.]\n\nADDITIONAL\nAvailability: [Part-time, summer, or internship availability]\nInterests: [Relevant interests or activities]\"\n", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.023315285018635806, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 669, "reasoningTokens": 333, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6393, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "669", "reasoningTokens": "333", "cachedTokens": "0" }, "timing": { "headersMs": 415.4897920000076, "firstEventMs": 1881.2246670000022, "firstReasoningMs": null, "firstContentMs": 6350.575249999994, "lastContentMs": 6799.845207999984, "generationMs": 467.70054200000595, "totalMs": 6818.275792, "visibleTokensPerSecond": 716.2702839031471, "contentChunkCount": 99, "averageContentChunkCharacters": 14.848484848484848, "maxContentStallMs": 149.82324999998673, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1746", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:16:09.916Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Benjamin Franklin’s life embodied the possibilities and contradictions of eighteenth-century America. A printer, writer, scientist, inventor, diplomat, and political leader, he helped shape both the practical institutions and the founding ideals of the United States. His achievements grew from curiosity, disciplined work, and a conviction that knowledge should serve the public.\n\nFranklin was born in Boston on January 17, 1706, into a large family of modest means. His father, Josiah Franklin, made candles and soap. Although Benjamin received only a brief formal education, he became an enthusiastic reader and continued learning throughout his life. At twelve, he began an apprenticeship with his older brother James, a printer. Working in the print shop introduced him to public debate and the power of the written word. In 1722, he secretly contributed witty essays to his brother’s newspaper under the name “Silence Dogood,” creating the voice of a fictional widow to comment on society.\n\nAt seventeen, Franklin left Boston and eventually settled in Philadelphia. There he built a successful printing business and became an influential figure in colonial life. He acquired the *Pennsylvania Gazette* in 1729 and began publishing *Poor Richard’s Almanack* in 1732. Its mixture of practical information, humor, and memorable sayings made it widely popular. Franklin’s advice praised industry, thrift, and thoughtful conduct, reflecting habits he cultivated in his own pursuit of self-improvement.\n\nYet Franklin’s ambitions extended beyond personal success. He believed that people could improve their communities through cooperation. In 1727, he organized the Junto, a discussion group devoted to learning and civic improvement. He helped establish the Library Company of Philadelphia, a subscription library, in 1731, and organized a volunteer fire company in 1736. He also supported the founding of the Pennsylvania Hospital and an academy that developed into the University of Pennsylvania. These projects showed his talent for turning useful ideas into lasting institutions.\n\nFranklin brought the same practical spirit to science and invention. His investigations of electricity won international recognition. His famous kite experiment in 1752 helped demonstrate the electrical nature of lightning, while his development of the lightning rod offered a way to protect buildings from its destructive force. His other inventions included bifocal glasses and the Franklin stove. He generally declined to patent his inventions, believing that useful discoveries should benefit others.\n\nAs tensions grew between Britain and its American colonies, Franklin became increasingly involved in imperial politics. For years, he worked in London as a colonial representative and hoped that disputes could be resolved within the British Empire. Over time, however, British policies and the failure of reconciliation changed his position. Returning to Philadelphia in 1775, he joined the Continental Congress and supported independence. In 1776, he served on the committee that prepared the Declaration of Independence, helping revise the document principally drafted by Thomas Jefferson.\n\nFranklin’s diplomatic work in France was especially important to the American Revolution. His scientific fame, wit, and carefully cultivated simplicity made him a celebrated figure in French society. More importantly, he helped secure the French alliance of 1778, bringing military and financial support essential to the American cause. He later helped negotiate the Treaty of Paris in 1783, which recognized American independence.\n\nIn his final years, Franklin continued to serve the new nation. As a delegate to the Constitutional Convention in 1787, he encouraged compromise among representatives with competing interests. His life also revealed moral inconsistencies. He had enslaved people and benefited from a society that tolerated slavery, but he later became president of the Pennsylvania Abolition Society. In 1790, he signed a petition urging Congress to act against slavery and the slave trade. This change did not erase his earlier conduct, but it demonstrated his capacity to reconsider established beliefs.\n\nFranklin died in Philadelphia on April 17, 1790, at the age of eighty-four. His legacy rests not on a single accomplishment but on the extraordinary range of his contributions. He used printing to inform, science to explain, invention to protect, and diplomacy to build a nation. Neither flawless nor simple, Franklin remains a powerful example of how curiosity and public service can transform a life—and help transform a society.\n\n******\nA candle-maker’s son with books in hand, \nHe sought a wider world to understand. \nFrom Boston’s presses, restless, young, and bold, \nHe went where new beginnings could unfold.\n\nIn printed wit, Poor Richard’s counsel grew; \nHe built a place where neighbors shared and knew. \nWith books and schools, with care for those in need, \nHe made the public good a living creed.\n\nHe traced the lightning through the storm-dark sky \nAnd asked what hidden laws might answer why. \nThen turned discovery toward a useful end: \nA rod against the bolt, a home’s defense.\n\nWhen reconciliation failed at last, \nHe helped a nation leave its bonds behind. \nIn France, his patient diplomacy held fast, \nSecuring aid through reputation, mind.\n\nHis freedom’s vision bore its shadows too; \nIn age, he challenged wrongs he once had known. \nHis final public labors helped renew \nThe promise liberty had not yet shown.\n\nPrinter and envoy, curious to the end, \nHe left a world his labors helped to mend.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 3.6352994116596564, "classifierCostIndex": 0, "promptTokens": 59, "completionTokens": 1066, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 24940, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "59", "completionTokens": "1066", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 313.0987920000043, "firstEventMs": 1234.4972499999858, "firstReasoningMs": null, "firstContentMs": 1646.283374999999, "lastContentMs": 25198.081291999988, "generationMs": 23615.64183400001, "totalMs": 25261.925209000008, "visibleTokensPerSecond": 45.097228670985935, "contentChunkCount": 249, "averageContentChunkCharacters": 22.63855421686747, "maxContentStallMs": 1041.2249590000138, "finalContentBurstRatio": 0.053397197090651057, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1746", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:16:35.179Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# The Life of Benjamin Franklin\n\nBenjamin Franklin stands as one of the most remarkable figures in American history, a man whose talents spanned so many fields that he seems almost impossible to categorize. Born on January 17, 1706, in Boston, Massachusetts, Franklin was the fifteenth of seventeen children born to a soap and candle maker. Despite this humble beginning, he would go on to become a printer, author, scientist, inventor, diplomat, and statesman whose influence helped shape the founding of the United States.\n\nFranklin's formal education ended at age ten, but his intellectual curiosity never waned. He apprenticed as a printer under his brother James, where he learned the trade that would eventually make him financially independent. At seventeen, seeking greater opportunity, he ran away to Philadelphia, arriving with little money but abundant ambition. There he established himself as a successful printer and publisher, most notably of \"Poor Richard's Almanack,\" a collection of witty aphorisms and practical wisdom that made him famous throughout the colonies.\n\nBeyond his business success, Franklin's scientific curiosity led to groundbreaking discoveries. His famous kite experiment demonstrated the electrical nature of lightning, and he invented numerous practical devices including the lightning rod, bifocal glasses, and the Franklin stove. He never patented his inventions, believing they should benefit humanity freely.\n\nFranklin's civic contributions were equally significant. He founded America's first public lending library, organized the first volunteer fire department, and helped establish the University of Pennsylvania. His organizational genius extended to founding the American Philosophical Society, fostering intellectual exchange among colonial thinkers.\n\nPerhaps Franklin's most enduring legacy lies in his political and diplomatic achievements. He served as a delegate to the Continental Congress and was one of the five men who drafted the Declaration of Independence. During the Revolutionary War, he served as America's ambassador to France, using his charm and wit to secure crucial military and financial support that proved decisive in the colonies' fight for independence. Later, he participated in negotiating the Treaty of Paris, which ended the war, and was a signatory to the U.S. Constitution.\n\nFranklin died on April 17, 1790, at the age of 84, having lived a life of extraordinary achievement and influence. His legacy endures not only in his inventions and writings but in the very fabric of American democratic institutions he helped create.\n\n******\n\nA printer's son from Boston town,\nWho rose from humble trade,\nThrough wit and work earned his renown,\nA legend that he made.\n\nHe caught the lightning in the sky,\nGave glasses double sight,\nHis stove kept homes both warm and dry,\nHis words brought common light.\n\nAmbassador to France he served,\nHis charm secured the aid,\nFor independence, hard-earned, nerved\nThe nation newly made.\n\nDeclaration's hand he lent,\nConstitution too,\nA founder's life, on wisdom bent,\nFranklin's spirit true.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6826163764039578, "classifierCostIndex": 0.004487568511917817, "promptTokens": 87, "completionTokens": 987, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 12771, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "87", "completionTokens": "987", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 854.9400830000232, "firstEventMs": 1571.8830830000225, "firstReasoningMs": null, "firstContentMs": 1571.9072500000184, "lastContentMs": 13414.10033300001, "generationMs": 11851.133915999992, "totalMs": 13423.04116600001, "visibleTokensPerSecond": 83.19878983637338, "contentChunkCount": 259, "averageContentChunkCharacters": 11.96911196911197, "maxContentStallMs": 768.5795419999922, "finalContentBurstRatio": 0.06806451612903226, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 235, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1746", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:16:48.603Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "Benjamin Franklin was born in Boston in 1706, the fifteenth of seventeen children. His formal schooling ended early, and he became an apprentice in his brother’s print shop. At seventeen, he left Boston for Philadelphia, where he built a successful printing business. He published *The Pennsylvania Gazette* and *Poor Richard’s Almanack*, whose wit and practical advice made him widely known.\n\nFranklin believed people could improve their communities through shared effort. He helped establish a lending library, a volunteer fire company, and an academy that later became the University of Pennsylvania. Curious about the natural world, he investigated electricity and showed that lightning was electrical. His inventions included the lightning rod and a more efficient stove.\n\nAs the American colonies moved toward independence, Franklin became a leading statesman. He helped draft the Declaration of Independence and served as a diplomat in France, securing crucial support for the Revolution. He later helped negotiate the treaty that ended the war and took part in the Constitutional Convention. In his final years, he spoke against slavery. Franklin died in Philadelphia in 1790, leaving a legacy of invention, public service, and faith in the power of learning.\n\n******\n\nA printer’s apprentice left Boston behind,\nAnd made a new life with an inquiring mind.\nHe filled pages with wisdom and helped neighbors unite,\nThen studied the storm and drew lessons from light.\n\nHe won France’s support when his country sought birth,\nAnd helped shape its peace and its laws on the earth.\nFrom books shared with strangers to lightning made known,\nHis life showed how much can be built—not alone.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3063973763162067, "classifierCostIndex": 0, "promptTokens": 59, "completionTokens": 442, "reasoningTokens": 119, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7203, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "59", "completionTokens": "442", "reasoningTokens": "119", "cachedTokens": "0" }, "timing": { "headersMs": 4425.199250000005, "firstEventMs": 4673.234083000018, "firstReasoningMs": 6875.873416000017, "firstContentMs": 7428.887958000007, "lastContentMs": 11622.469708000019, "generationMs": 4784.848792000004, "totalMs": 12213.736750000011, "visibleTokensPerSecond": 67.29575248822194, "contentChunkCount": 317, "averageContentChunkCharacters": 5.3249211356466875, "maxContentStallMs": 378.0742920000048, "finalContentBurstRatio": 0.06990521327014218, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1746", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:17:00.817Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Benjamin Franklin was born in Boston in 1706, the fifteenth child in a large family. His father hoped he would become a clergyman, but the cost of education was too high. Instead, Benjamin learned the printing trade as an apprentice to his older brother James. He loved reading and taught himself many subjects, developing a skill with words that would serve him throughout his life.\n\nIn 1723, Franklin moved to Philadelphia, where he established himself as a printer and publisher. His newspaper, the *Pennsylvania Gazette*, and his annual *Poor Richard’s Almanack* made him widely known. The almanac offered practical advice and memorable sayings about work, thrift, and learning. Franklin also helped build Philadelphia’s civic life, supporting a lending library, a fire company, a hospital, and an academy that later became the University of Pennsylvania.\n\nFranklin was also a curious scientist and inventor. His investigations into electricity helped show that lightning was electrical, and he developed the lightning rod to protect buildings. Among his other inventions were bifocal glasses and a more efficient stove. He chose not to patent many of his creations, believing that useful ideas should benefit the public.\n\nAs tensions between Britain and its American colonies grew, Franklin became an important political leader. He helped draft the Declaration of Independence in 1776 and traveled to France to win support for the American Revolution. His diplomacy helped secure a French alliance, which proved vital to the American cause. Later, he helped negotiate the peace treaty with Britain and took part in the 1787 Constitutional Convention.\n\nFranklin’s life included contradictions. He had enslaved people earlier in his life, but in his later years he became an outspoken opponent of slavery and served as president of an abolitionist society. He died in Philadelphia in 1790, at the age of 84. Remembered as a printer, scientist, writer, diplomat, and statesman, Franklin devoted his long life to learning and public service.\n\n******\nFrom Boston’s streets, a curious mind \nSet forth to learn, to print, to write; \nIn Philadelphia, he helped to build \nA city’s promise, bright with light.\n\nHe studied sparks and storming skies, \nAnd gave the lightning rod its name; \nWith books and civic ventures, too, \nHe sought to serve, not chase for fame.\n\nHe helped a nation claim its voice, \nWon friends abroad, made peace endure; \nHis life held flaws and changing views, \nYet learning’s light remained his lure.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.02193538703922797, "classifierCostIndex": 0, "promptTokens": 59, "completionTokens": 625, "reasoningTokens": 113, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5703, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "59", "completionTokens": "625", "reasoningTokens": "113", "cachedTokens": "0" }, "timing": { "headersMs": 558.7101659999753, "firstEventMs": 1124.789999999979, "firstReasoningMs": 5016.864999999962, "firstContentMs": 5854.950749999989, "lastContentMs": 6251.73195799996, "generationMs": 425.4906249999767, "totalMs": 6280.441374999966, "visibleTokensPerSecond": 1200.9665312838044, "contentChunkCount": 115, "averageContentChunkCharacters": 21.973913043478262, "maxContentStallMs": 117.22729100001743, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1546", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:17:07.332Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "Write an acoustic song about the Korean peninsula without using any commas.\n\n**Where the Mountains Meet the Sea**\n\n*Verse 1* \nA quiet guitar by the eastern shore \nWaves roll in like they have before \nThe Taebaek mountains catch the dawn \nAnd old familiar songs carry on \n\n*Chorus* \nFrom Seoul to Pyongyang the same stars shine \nOver two roads and one long line \nLet the wind sing soft through the cedar trees \nOf a hope held close on a divided peninsula \n\n*Verse 2* \nA grandmother hums by a window light \nA child asks why the road ends at night \nShe says some doors take time to mend \nThen hums the tune for him again \n\n*Bridge* \nWe cannot hurry the turning tide \nOr wish away the years between \nSo we listen for each other's songs \nAcross the hills and through the green \n\n*Final chorus* \nFrom Seoul to Pyongyang the same stars shine \nOver two roads and one long line \nLet the wind sing soft through the cedar trees \nOf a hope held close on a divided peninsula", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2114697025627208, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 304, "reasoningTokens": 74, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4981, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "304", "reasoningTokens": "74", "cachedTokens": "0" }, "timing": { "headersMs": 345.3299170000246, "firstEventMs": 518.4583749999874, "firstReasoningMs": null, "firstContentMs": 2188.4623330000322, "lastContentMs": 5134.999125000031, "generationMs": 3058.1817089999677, "totalMs": 5246.644042, "visibleTokensPerSecond": 74.88109660916241, "contentChunkCount": 224, "averageContentChunkCharacters": 4.397321428571429, "maxContentStallMs": 333.5101249999716, "finalContentBurstRatio": 0.23959390862944163, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1546", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:17:12.579Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Write an acoustic song about the Korean peninsula without using any commas.\n\n**The Mountain Keeps the Morning**\n\n*Verse 1* \nAlong the ridges where the cold winds roam \nA river carries stories home \nThe old pines lean above the stone \nAnd every path remembers more \n\n*Chorus* \nOh peninsula beneath one sky \nWhere distant lights and wild geese fly \nMay every guarded field grow green \nMay every voice be heard between \n\n*Verse 2* \nA mother hums beside the door \nA child draws boats along the shore \nThe moon lays silver on the sea \nAnd dreams cross where the eyes can’t see \n\n*Chorus* \nOh peninsula beneath one sky \nWhere distant lights and wild geese fly \nMay every guarded field grow green \nMay every voice be heard between \n\n*Bridge* \nNo wall can turn the seasons back \nNo border stops the roots from finding cracks \nThe mountain holds the rain and snow \nAnd waits for gentler winds to blow \n\n*Final Chorus* \nOh peninsula beneath one sky \nLet open roads replace goodbye \nMay every guarded field grow green \nAnd dawn fall soft on all between", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.013377456706527083, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 379, "reasoningTokens": 139, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3237, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "379", "reasoningTokens": "139", "cachedTokens": "0" }, "timing": { "headersMs": 268.2011250000214, "firstEventMs": 626.4461660000379, "firstReasoningMs": null, "firstContentMs": 2267.743666000024, "lastContentMs": 3501.064000000013, "generationMs": 1241.851583999989, "totalMs": 3509.595250000013, "visibleTokensPerSecond": 192.4545598518173, "contentChunkCount": 87, "averageContentChunkCharacters": 12.298850574712644, "maxContentStallMs": 137.6571249999688, "finalContentBurstRatio": 0.2738317757009346, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1546", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:17:16.089Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Write an acoustic song about the Korean peninsula without using any commas.\n\n**Under One Moon**\n\n*[Soft fingerpicked guitar]*\n\n**Verse 1** \nMorning climbs the eastern shore \nFishing boats drift out once more \nMountains wear their coats of pine \nAnd sunlight warms the washing line \n\n**Verse 2** \nThe Han runs silver through the town \nAs market stalls are closing down \nA radio behind a door \nPlays a song worth waiting for \n\n**Chorus** \nOh peninsula of rain and stone \nHow many roads will lead us home \nUnder one moon the night winds blow \nThrough fields where spring has yet to show \n\n**Verse 3** \nA grandmother unfolds a page \nThe ink has softened with its age \nShe reads a name I never knew \nThen sets another cup to brew \n\n**Bridge** \nMay there come an ordinary day \nWhen no one has to turn away \nWhen letters need no years to roam \nAnd every voice can find its home \n\n**Final Chorus** \nOh peninsula of rain and stone \nHow many roads will lead us home \nUnder one moon the night winds blow \nAnd somewhere seeds begin to grow", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.056404301097489, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 304, "reasoningTokens": 63, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 9695, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "304", "reasoningTokens": "63", "cachedTokens": "0" }, "timing": { "headersMs": 323.00458300003083, "firstEventMs": 792.6575000000303, "firstReasoningMs": 3993.8229170000413, "firstContentMs": 4786.420291999995, "lastContentMs": 9988.562917000032, "generationMs": 5239.473416000023, "totalMs": 10025.893708000018, "visibleTokensPerSecond": 45.8061299189153, "contentChunkCount": 98, "averageContentChunkCharacters": 10.775510204081632, "maxContentStallMs": 418.8526670000283, "finalContentBurstRatio": 0.26420454545454547, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1546", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:17:26.115Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "Write an acoustic song about the Korean peninsula without using any commas.\n\n**Verse 1**\nMountains rise where rivers bend\nTwo hearts beating without an end\nOne moon shines above the sea\nWhispering of what used to be\n\n**Chorus**\nOh Korea land of morning light\nDivided fields under starry night\nOne people singing the same old song\nWaiting for the day we're whole and strong\n\n**Verse 2**\nGrandmothers tell of a single home\nChildren draw maps of where they roam\nBarbed wire cuts through ancient soil\nYet hope still blooms through all this toil\n\n**Chorus**\nOh Korea land of morning light\nDivided fields under starry night\nOne people singing the same old song\nWaiting for the day we're whole and strong\n\n**Bridge**\nFrom Halla's peak to Baekdu's crown\nThe spirit of the people won't back down\nThrough wars and tears and borders drawn\nThe heart of Korea carries on\n\n**Final Chorus**\nOh Korea land of morning light\nSomeday soon we'll end this fight\nOne people singing the same old song\nStanding together whole and strong", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2703353680174085, "classifierCostIndex": 0.004441976574768272, "promptTokens": 64, "completionTokens": 381, "reasoningTokens": 19, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5626, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "64", "completionTokens": "381", "reasoningTokens": "19", "cachedTokens": "0" }, "timing": { "headersMs": 607.2125419999938, "firstEventMs": 1323.820166999998, "firstReasoningMs": 2963.8355830000364, "firstContentMs": 2963.8959580000374, "lastContentMs": 6175.696417000028, "generationMs": 3236.597124999971, "totalMs": 6200.4930830000085, "visibleTokensPerSecond": 111.5368969500655, "contentChunkCount": 107, "averageContentChunkCharacters": 9.457943925233645, "maxContentStallMs": 472.2481249999837, "finalContentBurstRatio": 0.1600790513833992, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 198, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-17", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T10:17:32.537Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "-17,0,60,136", "evaluation": { "passed": true, "answer": "-17,0,60,136", "expected": "-17,0,60,136" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0600525395818441, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1319, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 456.70041699998546, "firstEventMs": 770.9026670000167, "firstReasoningMs": null, "firstContentMs": 1559.106334000011, "lastContentMs": 1560.0936249999795, "generationMs": 307.3647500000079, "totalMs": 1866.471084000019, "visibleTokensPerSecond": 35.788098667787104, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.9349999999976717, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-17", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T10:17:34.404Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-17,0,60,136", "evaluation": { "passed": true, "answer": "-17,0,60,136", "expected": "-17,0,60,136" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.001315826470100042, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 32, "reasoningTokens": 18, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3846, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "32", "reasoningTokens": "18", "cachedTokens": "0" }, "timing": { "headersMs": 371.3015000000014, "firstEventMs": 692.465166000009, "firstReasoningMs": 3154.0136659999844, "firstContentMs": 4208.895916000009, "lastContentMs": 4209.575249999994, "generationMs": 7.500708999985363, "totalMs": 4216.396624999994, "visibleTokensPerSecond": 1733.1694910474953, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.6627089999965392, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-17", "category": "easy", "arm": "smart", "at": "2026-09-26T10:17:38.621Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-17,0,60,136", "evaluation": { "passed": true, "answer": "-17,0,60,136", "expected": "-17,0,60,136" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005708704035630342, "classifierCostIndex": 0.0043928775655303, "promptTokens": 29, "completionTokens": 32, "reasoningTokens": 18, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2132, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "32", "reasoningTokens": "18", "cachedTokens": "0" }, "timing": { "headersMs": 908.7385000000359, "firstEventMs": 1160.6399160000146, "firstReasoningMs": 2243.0650000000023, "firstContentMs": 2983.556125000003, "lastContentMs": 3037.0344580000383, "generationMs": 67.54587500001071, "totalMs": 3051.1020000000135, "visibleTokensPerSecond": 192.4617898576033, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 52.77500000002328, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 217, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-17", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T10:17:41.672Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "-17,0,60,136", "evaluation": { "passed": true, "answer": "-17,0,60,136", "expected": "-17,0,60,136" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012032629448003512, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1028, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 201.18674999999348, "firstEventMs": 521.6747920000344, "firstReasoningMs": null, "firstContentMs": 1224.0632920000353, "lastContentMs": 1227.7136670000036, "generationMs": 27.386499999964144, "totalMs": 1251.4497919999994, "visibleTokensPerSecond": 401.65775108226325, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 2.49633300001733, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2798", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:17:43.111Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "1. The United Kingdom is made up of England Scotland Wales and Northern Ireland.\n2. London is the capital of the UK.\n3. Great Britain is the island containing England Scotland and Wales.\n4. The UK is a constitutional monarchy.\n5. The UK Parliament meets at the Palace of Westminster in London.\n6. The official currency is the pound sterling.\n7. The UK has coastlines on the Atlantic Ocean the North Sea the English Channel and the Irish Sea.\n8. English is the most widely spoken language in the UK.\n9. The UK’s national flag is called the Union Jack.\n10. The UK was a founding member of NATO.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0092782289847085, "classifierCostIndex": 0, "promptTokens": 22, "completionTokens": 265, "reasoningTokens": 128, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3402, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "22", "completionTokens": "265", "reasoningTokens": "128", "cachedTokens": "0" }, "timing": { "headersMs": 260.42566700000316, "firstEventMs": 646.2540420000441, "firstReasoningMs": 2414.8649590000277, "firstContentMs": 3387.058834000025, "lastContentMs": 3657.9245420000516, "generationMs": 292.32641600002535, "totalMs": 3679.3852500000503, "visibleTokensPerSecond": 465.233357494412, "contentChunkCount": 69, "averageContentChunkCharacters": 8.579710144927537, "maxContentStallMs": 173.10262499999953, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2798", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:17:46.790Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "1. The UK is made up of England Scotland Wales and Northern Ireland.\n2. London is the UK’s capital and largest city.\n3. The UK is a constitutional monarchy.\n4. The UK’s Parliament meets at the Palace of Westminster in London.\n5. The pound sterling is the UK’s currency.\n6. English is the UK’s most widely spoken language.\n7. Welsh is an official language in Wales.\n8. The UK has coastlines along the Atlantic Ocean the North Sea the English Channel and the Irish Sea.\n9. The UK is home to Stonehenge one of the world’s best-known prehistoric monuments.\n10. The UK helped lead the Industrial Revolution.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.011709843928480252, "classifierCostIndex": 0.004357806844646035, "promptTokens": 22, "completionTokens": 209, "reasoningTokens": 67, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2449, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "22", "completionTokens": "209", "reasoningTokens": "67", "cachedTokens": "0" }, "timing": { "headersMs": 1436.5499589999672, "firstEventMs": 1616.9108750000014, "firstReasoningMs": null, "firstContentMs": 3216.4495419999585, "lastContentMs": 3777.6774999999907, "generationMs": 629.6934170000022, "totalMs": 3846.1429589999607, "visibleTokensPerSecond": 223.91849143310878, "contentChunkCount": 71, "averageContentChunkCharacters": 8.47887323943662, "maxContentStallMs": 520.1140840000007, "finalContentBurstRatio": 0.8089700996677741, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 150, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2798", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:17:50.637Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "1. **Four countries make up the UK:** England and Scotland along with Wales and Northern Ireland.\n2. **London is the capital** and the largest city in the UK.\n3. **The UK is a constitutional monarchy** with a parliamentary democracy.\n4. **Its currency is the pound sterling** which uses the symbol £.\n5. **The UK Parliament has two houses:** the House of Commons and the House of Lords.\n6. **Great Britain is not the same as the UK.** Great Britain is the island containing England and Scotland along with Wales.\n7. **The National Health Service began in 1948** and provides most healthcare free at the point of use.\n8. **The UK was the birthplace of the Industrial Revolution** which began in the 18th century.\n9. **Ben Nevis is the UK's highest mountain** at 1345 metres above sea level.\n10. **People drive on the left side of the road** throughout the UK.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.2729289085261248, "classifierCostIndex": 0, "promptTokens": 22, "completionTokens": 373, "reasoningTokens": 169, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 9048, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "22", "completionTokens": "373", "reasoningTokens": "169", "cachedTokens": "0" }, "timing": { "headersMs": 753.0339999999851, "firstEventMs": 1054.6049580000108, "firstReasoningMs": 7360.12820799998, "firstContentMs": 7922.710833000019, "lastContentMs": 9777.318665999977, "generationMs": 1890.0427079999936, "totalMs": 9812.753541000013, "visibleTokensPerSecond": 107.40498039581902, "contentChunkCount": 84, "averageContentChunkCharacters": 10.214285714285714, "maxContentStallMs": 497.03724999999395, "finalContentBurstRatio": 0.25874125874125875, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2798", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:18:00.450Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "1. The UK is made up of England Scotland Wales and Northern Ireland.\n2. Its capital is London.\n3. Its currency is the pound sterling.\n4. The UK is a constitutional monarchy.\n5. The UK Parliament meets at the Palace of Westminster.\n6. English is the most widely spoken language.\n7. People drive on the left side of the road.\n8. Ben Nevis in Scotland is the UK's highest mountain.\n9. The Prime Meridian passes through Greenwich in London.\n10. The UK is separated from mainland Europe by the English Channel.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.16298375650328348, "classifierCostIndex": 0, "promptTokens": 22, "completionTokens": 237, "reasoningTokens": 119, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4505, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "22", "completionTokens": "237", "reasoningTokens": "119", "cachedTokens": "0" }, "timing": { "headersMs": 372.4285000000382, "firstEventMs": 679.4408340000082, "firstReasoningMs": 3138.3247090000077, "firstContentMs": 4150.295709000027, "lastContentMs": 4811.228542000055, "generationMs": 703.8283749999828, "totalMs": 4854.12408400001, "visibleTokensPerSecond": 166.23370718749848, "contentChunkCount": 112, "averageContentChunkCharacters": 4.508928571428571, "maxContentStallMs": 611.0703329999815, "finalContentBurstRatio": 0.7683168316831683, "buffered": false }, "error": null, "routing": null }, { "caseId": "instruction_cipher", "category": "instruction", "arm": "gpt-6-astra", "at": "2026-09-26T10:18:05.530Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: TZGLQDOMYZWQ", "evaluation": { "passed": true, "answer": "tzglqdomyzwq", "expected": "tzglqdomyzwq", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.497876093537956, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 132, "reasoningTokens": 117, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3737, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "132", "reasoningTokens": "117", "cachedTokens": "0" }, "timing": { "headersMs": 309.603208000015, "firstEventMs": 823.2228749999776, "firstReasoningMs": null, "firstContentMs": 3854.8059580000117, "lastContentMs": 3901.700790999981, "generationMs": 155.2365829999908, "totalMs": 4010.0425410000025, "visibleTokensPerSecond": 90.18492760820966, "contentChunkCount": 9, "averageContentChunkCharacters": 2.111111111111111, "maxContentStallMs": 21.210208000033163, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "instruction_cipher", "category": "instruction", "arm": "smart", "at": "2026-09-26T10:18:09.540Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: TZGLQDOMYZWQ", "evaluation": { "passed": true, "answer": "tzglqdomyzwq", "expected": "tzglqdomyzwq", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.08601687801373413, "classifierCostIndex": 0.004540174593244215, "promptTokens": 108, "completionTokens": 99, "reasoningTokens": 79, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4538, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "108", "completionTokens": "99", "reasoningTokens": "79", "cachedTokens": "0" }, "timing": { "headersMs": 600.4252919999999, "firstEventMs": 1724.2246250000317, "firstReasoningMs": 4652.791499999992, "firstContentMs": 5107.18770900002, "lastContentMs": 5107.18770900002, "generationMs": 0.13491600000998005, "totalMs": 5107.32262500003, "visibleTokensPerSecond": 140828.36726996445, "contentChunkCount": 1, "averageContentChunkCharacters": 19, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 137, "classifierFailed": false, "classifierReused": false } }, { "caseId": "instruction_cipher", "category": "instruction", "arm": "gpt-6-luna", "at": "2026-09-26T10:18:14.648Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: TZGLQDOMYZWQ", "evaluation": { "passed": true, "answer": "tzglqdomyzwq", "expected": "tzglqdomyzwq", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005910090905938837, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 155, "reasoningTokens": 140, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2125, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "155", "reasoningTokens": "140", "cachedTokens": "0" }, "timing": { "headersMs": 271.0881250000093, "firstEventMs": 704.1600420000032, "firstReasoningMs": null, "firstContentMs": 2356.402708000038, "lastContentMs": 2356.472000000009, "generationMs": 43.50516699999571, "totalMs": 2399.9078750000335, "visibleTokensPerSecond": 321.8008564362339, "contentChunkCount": 9, "averageContentChunkCharacters": 2.111111111111111, "maxContentStallMs": 0.012541999982204288, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "instruction_cipher", "category": "instruction", "arm": "gpt-6-sol", "at": "2026-09-26T10:18:17.048Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "FINAL: TZGLQDOMYZWQ", "evaluation": { "passed": true, "answer": "tzglqdomyzwq", "expected": "tzglqdomyzwq", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.12196719955525472, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 165, "reasoningTokens": 150, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2837, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "165", "reasoningTokens": "150", "cachedTokens": "0" }, "timing": { "headersMs": 209.5013339999714, "firstEventMs": 669.7280419999734, "firstReasoningMs": null, "firstContentMs": 2904.6756249999744, "lastContentMs": 2951.8080840000184, "generationMs": 152.52041699999245, "totalMs": 3057.196041999967, "visibleTokensPerSecond": 91.79098953027838, "contentChunkCount": 9, "averageContentChunkCharacters": 2.111111111111111, "maxContentStallMs": 16.258667000045534, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3294", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:18:20.434Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "\"Q & A # 1\nQ: What is the largest planet in our solar system?\nA: Jupiter.\n***\nQ & A # 2\nQ: Who wrote Pride and Prejudice?\nA: Jane Austen.\n***\nQ & A # 3\nQ: What is the chemical symbol for gold?\nA: Au.\n***\nQ & A # 4\nQ: How many sides does a hexagon have?\nA: Six.\n***\nQ & A # 5\nQ: What is the capital of Japan?\nA: Tokyo.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5491386964797109, "classifierCostIndex": 0, "promptTokens": 69, "completionTokens": 149, "reasoningTokens": 31, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3303, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "69", "completionTokens": "149", "reasoningTokens": "31", "cachedTokens": "0" }, "timing": { "headersMs": 214.58445899997605, "firstEventMs": 599.1075420000125, "firstReasoningMs": 2404.610166999977, "firstContentMs": 3294.3539170000004, "lastContentMs": 3517.675916999986, "generationMs": 228.76949999999488, "totalMs": 3523.1234169999952, "visibleTokensPerSecond": 511.43181237010447, "contentChunkCount": 64, "averageContentChunkCharacters": 4.96875, "maxContentStallMs": 216.0769169999985, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3294", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:18:23.957Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"Q & A # 1 \nQ: What is the capital of France? \nA: Paris. \n***\nQ & A # 2 \nQ: How many days are in a leap year? \nA: 366. \n***\nQ & A # 3 \nQ: Which planet is known as the Red Planet? \nA: Mars. \n***\nQ & A # 4 \nQ: What do bees make from flower nectar? \nA: Honey. \n***\nQ & A # 5 \nQ: What is the largest ocean on Earth? \nA: The Pacific Ocean.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.007459946994247344, "classifierCostIndex": 0, "promptTokens": 69, "completionTokens": 202, "reasoningTokens": 73, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2852, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "69", "completionTokens": "202", "reasoningTokens": "73", "cachedTokens": "0" }, "timing": { "headersMs": 224.78441600000951, "firstEventMs": 542.984999999986, "firstReasoningMs": 2092.7445409999928, "firstContentMs": 2911.1332910000347, "lastContentMs": 3072.5175409999792, "generationMs": 167.74245899997186, "totalMs": 3078.8757500000065, "visibleTokensPerSecond": 763.074541550756, "contentChunkCount": 66, "averageContentChunkCharacters": 5.287878787878788, "maxContentStallMs": 155.5319169999566, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3294", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:18:27.036Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "\"Q & A # 1\nQ: What is the capital of France?\nA: Paris.\n***\nQ & A # 2\nQ: How many days are in a leap year?\nA: 366.\n***\nQ & A # 3\nQ: What planet is known as the Red Planet?\nA: Mars.\n***\nQ & A # 4\nQ: What do bees make?\nA: Honey.\n***\nQ & A # 5\nQ: What is the largest ocean on Earth?\nA: The Pacific Ocean.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.12412270001575687, "classifierCostIndex": 0, "promptTokens": 69, "completionTokens": 170, "reasoningTokens": 53, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2327, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "69", "completionTokens": "170", "reasoningTokens": "53", "cachedTokens": "0" }, "timing": { "headersMs": 215.6618749999907, "firstEventMs": 631.1957079999847, "firstReasoningMs": null, "firstContentMs": 2255.4793749999953, "lastContentMs": 2505.7452909999993, "generationMs": 315.4506249999977, "totalMs": 2570.929999999993, "visibleTokensPerSecond": 367.7279130450316, "contentChunkCount": 111, "averageContentChunkCharacters": 2.7117117117117115, "maxContentStallMs": 83.96387499995762, "finalContentBurstRatio": 0.6445182724252492, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3294", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:18:29.608Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"Q & A # 1 \nQ: What is the largest planet in our solar system? \nA: Jupiter. \n*** \nQ & A # 2 \nQ: What is the capital of Japan? \nA: Tokyo. \n*** \nQ & A # 3 \nQ: How many sides does a hexagon have? \nA: Six. \n*** \nQ & A # 4 \nQ: What gas do plants absorb from the atmosphere? \nA: Carbon dioxide. \n*** \nQ & A # 5 \nQ: Who wrote *Pride and Prejudice*? \nA: Jane Austen.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.011986093299137853, "classifierCostIndex": 0.0045261463048905095, "promptTokens": 69, "completionTokens": 202, "reasoningTokens": 66, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3092, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "69", "completionTokens": "202", "reasoningTokens": "66", "cachedTokens": "0" }, "timing": { "headersMs": 808.3757079999777, "firstEventMs": 1048.833249999967, "firstReasoningMs": 2544.320415999973, "firstContentMs": 3733.338457999984, "lastContentMs": 3846.537624999997, "generationMs": 133.49520800000755, "totalMs": 3866.8336659999914, "visibleTokensPerSecond": 1011.2722548062726, "contentChunkCount": 68, "averageContentChunkCharacters": 5.544117647058823, "maxContentStallMs": 106.57829199999105, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 216, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1591", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:18:34.034Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "A mom cried, “These chores must be done!”\nHer kids fled and hid from the sun.\n“Get up! Scrub that floor!\nI’ve asked you before!”\nNow she’s furious—this isn’t fun.\n\n******\n\nA mom yelled, “Put toys in the bin!”\nHer kids just sat there with a grin.\n“Get scrubbing! Don’t stall!\nPick up down the hall!”\nShe’s furious clear to her chin.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0258302603682017, "classifierCostIndex": 0.004438469502679845, "promptTokens": 46, "completionTokens": 612, "reasoningTokens": 516, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 10820, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "612", "reasoningTokens": "516", "cachedTokens": "0" }, "timing": { "headersMs": 753.4732499999809, "firstEventMs": 1083.0414170000004, "firstReasoningMs": 3698.673542000004, "firstContentMs": 11403.327875000017, "lastContentMs": 11570.768708999967, "generationMs": 188.18362500000512, "totalMs": 11591.511500000022, "visibleTokensPerSecond": 504.8260708124706, "contentChunkCount": 57, "averageContentChunkCharacters": 5.807017543859649, "maxContentStallMs": 161.64545900002122, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 234, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1591", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:18:45.626Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "The dishes were stacked to the sky,\nWhile my kids let the hours slip by.\nI roared, “Scrub that plate!”\nThey said, “Mom, can it wait?”\nNow the sink and my temper run high.\n\n******\n\nThe laundry had conquered the floor,\nWhile my kids let it creep past the door.\nI yelled, “Fold your clothes!”\nThey replied, “We oppose!”\nSo I banned all their screens with a roar.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.541599165926534, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 793, "reasoningTokens": 697, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 11134, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "793", "reasoningTokens": "697", "cachedTokens": "0" }, "timing": { "headersMs": 274.3522080000257, "firstEventMs": 645.3124160000007, "firstReasoningMs": 5240.020625000005, "firstContentMs": 10707.404666000046, "lastContentMs": 11131.670375000045, "generationMs": 704.7458340000012, "totalMs": 11412.150500000047, "visibleTokensPerSecond": 134.80037116473375, "contentChunkCount": 90, "averageContentChunkCharacters": 3.988888888888889, "maxContentStallMs": 36.51474999997299, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1591", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:18:57.038Z", "model": "openai/gpt-6-luna", "loggedModel": "openai/gpt-6-luna", "content": "A furious mom saw bright red, \nAt clothes strewn all over the bed. \n“Go sweep! No delay!” \n“Sure, maybe someday!” \nShe fumed as she cleaned up instead.\n\n******\n\nA mom made a chore chart one day, \nHer kids shoved the whole thing away. \n“Now wash every dish!” \nThey ignored her fierce wish— \nShe roared, “You’ll be grounded till May!”", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.05558169710604033, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 1606, "reasoningTokens": 1511, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 15703, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "1606", "reasoningTokens": "1511", "cachedTokens": "0" }, "timing": { "headersMs": 969.7470409999951, "firstEventMs": 1260.0047080000513, "firstReasoningMs": 10999.064165999996, "firstContentMs": 16332.542208000028, "lastContentMs": 16618.193874999997, "generationMs": 433.2911249999888, "totalMs": 16765.833333000017, "visibleTokensPerSecond": 216.9442081233545, "contentChunkCount": 89, "averageContentChunkCharacters": 3.8202247191011236, "maxContentStallMs": 96.52995799999917, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1591", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:19:13.805Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "There once was a mom who was sore \nFrom scrubbing the damn kitchen floor. \nHer kids said, “Not now!” \nShe bellowed, “Oh, wow— \nThen your Wi-Fi’s not on anymore!”\n\n******\n\nA mom heard her kids whine and pout \nWhen asked to take one trash bag out. \n“Your thumbs work just fine \nWhen you’re gaming online— \nSo lift it, you brats!” came her shout.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 3.0834926426449814, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 905, "reasoningTokens": 804, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 27561, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "905", "reasoningTokens": "804", "cachedTokens": "0" }, "timing": { "headersMs": 290.0415840000496, "firstEventMs": 722.0754590000142, "firstReasoningMs": 8329.940042000031, "firstContentMs": 27673.61525000003, "lastContentMs": 27847.75, "generationMs": 182.94658399996115, "totalMs": 27856.561833999993, "visibleTokensPerSecond": 546.6076371233105, "contentChunkCount": 59, "averageContentChunkCharacters": 5.9491525423728815, "maxContentStallMs": 167.2108340000268, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-3", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T10:19:42.224Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "gateway-38-ready.", "evaluation": { "passed": false, "answer": "gateway-38-ready.", "expected": "gateway-38-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04588329390766073, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1533, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 226.6662499999511, "firstEventMs": 531.4326249999576, "firstReasoningMs": null, "firstContentMs": 1586.265791999991, "lastContentMs": 1647.9970420000027, "generationMs": 177.16358300001593, "totalMs": 1763.429375000007, "visibleTokensPerSecond": 45.156007033337545, "contentChunkCount": 5, "averageContentChunkCharacters": 3.4, "maxContentStallMs": 56.835750000027474, "finalContentBurstRatio": 0.5294117647058824, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-3", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T10:19:43.987Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "gateway-38-ready", "evaluation": { "passed": true, "answer": "gateway-38-ready", "expected": "gateway-38-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008518812990176131, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 864, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 332.93104199995287, "firstEventMs": 617.1154999999562, "firstReasoningMs": null, "firstContentMs": 1083.054999999993, "lastContentMs": 1130.9548749999958, "generationMs": 198.5282920000027, "totalMs": 1281.5832919999957, "visibleTokensPerSecond": 35.2594581330499, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 40.59941700001946, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-3", "category": "easy", "arm": "smart", "at": "2026-09-26T10:19:45.269Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-38-ready", "evaluation": { "passed": true, "answer": "gateway-38-ready", "expected": "gateway-38-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.00481062380621711, "classifierCostIndex": 0.0043648209888228874, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1136, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 562.3190419999883, "firstEventMs": 818.2659579999745, "firstReasoningMs": null, "firstContentMs": 1642.0989999999874, "lastContentMs": 1642.135249999992, "generationMs": 59.36362499999814, "totalMs": 1701.4626249999856, "visibleTokensPerSecond": 117.91732731955334, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.013417000009212643, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 186, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-3", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T10:19:46.971Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "gateway-38-ready", "evaluation": { "passed": true, "answer": "gateway-38-ready", "expected": "gateway-38-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0004458028173942223, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2428, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 349.7406669999473, "firstEventMs": 1137.1528339999495, "firstReasoningMs": null, "firstContentMs": 2343.1067919999477, "lastContentMs": 2359.0790419999976, "generationMs": 426.1257920000353, "totalMs": 2769.232583999983, "visibleTokensPerSecond": 16.427074191274063, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 14.200333999993745, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2070", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:19:50.598Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "| Potential benefit | Potential drawback |\n|---|---|\n| Can protect others when a young person poses an immediate, serious safety risk. | Confinement can expose young people to violence, stress, and trauma. |\n| Can ensure a young person appears in court while a case is pending. | It can disrupt school, family relationships, and access to community support. |\n| May provide structured supervision and access to services. | The quality of education and treatment varies widely; detention may not address the causes of the behavior. |\n| Can create a pause for assessment and planning. | It is costly, and its use can be uneven across communities. |\n\nP.S. Detention is generally most defensible when a less restrictive option cannot adequately address a specific safety or court-appearance concern.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.18216339420533628, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 263, "reasoningTokens": 98, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4090, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "263", "reasoningTokens": "98", "cachedTokens": "0" }, "timing": { "headersMs": 260.3257080000476, "firstEventMs": 550.4358329999959, "firstReasoningMs": 2404.2700420000474, "firstContentMs": 3013.775708000001, "lastContentMs": 4199.49566700001, "generationMs": 1347.0580840000184, "totalMs": 4360.8337920000195, "visibleTokensPerSecond": 121.74679172928505, "contentChunkCount": 159, "averageContentChunkCharacters": 5, "maxContentStallMs": 199.36887499998556, "finalContentBurstRatio": 0.14465408805031446, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2070", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:19:54.960Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Juvenile detention involves holding young people accused or found responsible for offenses in secure facilities. Its effects depend on the conditions, length of confinement, available services, and alternatives.\n\n| Potential pros | Cons and risks |\n|---|---|\n| **Immediate public safety:** Temporarily prevents a young person who poses a serious risk from harming others in the community. | **Potential for harm:** Confinement can expose young people to violence, isolation, abuse, or worsening mental health. |\n| **Court attendance:** Can ensure attendance at hearings when there is a substantial risk of failing to appear. | **Loss of liberty before adjudication:** Some young people are detained before a court determines whether they committed an offense. |\n| **Access to services:** Well-resourced facilities may provide education, counseling, substance-use treatment, and health care. | **Uneven service quality:** Services may be inadequate or disrupted upon release; detention is not necessary to provide most of these supports. |\n| **Structured environment:** Predictable routines and supervision may offer short-term stability. | **Disrupted development:** Separation from family, school, and community can undermine relationships, learning, and healthy development. |\n| **Enforcement of court orders:** Secure custody can enforce restrictions when less restrictive measures cannot adequately manage a serious risk. | **Limited deterrent value:** Detention does not reliably prevent future offending and can increase that risk, particularly for lower-risk youth. |\n| **Short-term assessment:** Staff may identify urgent health, safety, or treatment needs. | **High costs and unequal impacts:** Detention is expensive, and disadvantaged communities and some racial or ethnic groups are disproportionately affected. |\n\n**Bottom line:** Detention may be necessary in some serious-risk cases, but community-based supervision, family support, restorative justice, and treatment often offer less disruptive options.\n\nP.S. Detention before a court decision and longer-term confinement after adjudication serve different purposes, so their benefits and drawbacks should be evaluated separately.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.3788431600335467, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 402, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 9549, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "402", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 723.2028329999885, "firstEventMs": 1028.9179579999764, "firstReasoningMs": null, "firstContentMs": 1834.0634169999976, "lastContentMs": 10282.835832999961, "generationMs": 8453.205915999948, "totalMs": 10287.269332999946, "visibleTokensPerSecond": 47.43762354599696, "contentChunkCount": 124, "averageContentChunkCharacters": 17.70967741935484, "maxContentStallMs": 466.75070799997775, "finalContentBurstRatio": 0.1830601092896175, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2070", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:20:05.248Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "| Potential pros | Potential cons |\n|---|---|\n| Can temporarily protect the public when a young person poses an immediate, serious safety risk. | Confinement can disrupt school, family relationships, and healthy development. |\n| May provide structure and access to services such as education, counseling, or substance-use treatment. | Services can be limited or inconsistent, and detention itself is not a substitute for effective treatment. |\n| Can ensure a young person appears in court and comply with legal orders when less restrictive options have failed. | Detention can expose young people to violence, isolation, or harmful peer influences. |\n| May give families and communities short-term relief during a crisis. | Research has linked detention—especially longer stays or detention for lower-level offenses—to worse outcomes for some youth, including higher rates of later justice-system involvement. |\n| In some cases, a brief stay may create time to assess needs and arrange a safer plan. | It can disproportionately affect youth from marginalized communities and impose significant costs on families and public systems. |\n\nP.S. Detention is generally best treated as a last resort, with the decision based on an individual assessment and less restrictive alternatives considered first.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.014179901777836682, "classifierCostIndex": 0.004399891709707153, "promptTokens": 34, "completionTokens": 277, "reasoningTokens": 33, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3114, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "277", "reasoningTokens": "33", "cachedTokens": "0" }, "timing": { "headersMs": 1218.0976249999949, "firstEventMs": 1861.9865839999984, "firstReasoningMs": 3075.2804590000305, "firstContentMs": 3904.602292000025, "lastContentMs": 4327.184875000035, "generationMs": 441.08399999997346, "totalMs": 4345.6862919999985, "visibleTokensPerSecond": 550.9154718829399, "contentChunkCount": 87, "averageContentChunkCharacters": 14.908045977011493, "maxContentStallMs": 109.93016699998407, "finalContentBurstRatio": 0.9722436391673092, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 535, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2070", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:20:09.594Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "| Potential pros | Potential cons |\n|---|---|\n| Can temporarily protect the public when a young person poses an immediate, serious safety risk. | Can disrupt education, family relationships, and healthy social development. |\n| May provide access to structure, schooling, counseling, or health services—if those services are available and effective. | Confinement can expose young people to violence, isolation, or other traumatic experiences. |\n| Can create time for assessment and planning when a young person needs urgent support. | Detention may increase stress and make it harder to return to school or community life. |\n| May ensure a young person appears for court proceedings in some cases. | It can disproportionately affect youth from marginalized communities, and detention may be used when less restrictive options would suffice. |\n| In limited circumstances, separation from an unsafe home or environment may offer short-term protection. | A detention placement may not address the reasons behind the behavior, and can lead to further justice-system involvement. |\n\nThe effects depend greatly on the young person’s circumstances, the length and conditions of detention, and the services provided. Community-based options—such as supervised release, restorative programs, or intensive family support—may be appropriate alternatives in many cases.\n\nP.S. Detention is generally best treated as a last resort, especially for young people who do not pose an immediate safety risk.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01198137224055728, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 341, "reasoningTokens": 61, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3706, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "341", "reasoningTokens": "61", "cachedTokens": "0" }, "timing": { "headersMs": 324.40950000000885, "firstEventMs": 753.4508749999804, "firstReasoningMs": 2588.663292000012, "firstContentMs": 3588.0182499999646, "lastContentMs": 4024.807709000015, "generationMs": 450.93283400003565, "totalMs": 4038.9510840000003, "visibleTokensPerSecond": 618.7174207855043, "contentChunkCount": 92, "averageContentChunkCharacters": 16.16304347826087, "maxContentStallMs": 193.05924999999115, "finalContentBurstRatio": 0.9926025554808339, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-11", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T10:20:13.876Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-94-42", "evaluation": { "passed": true, "answer": "ORD-94-42", "expected": "ORD-94-42" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0005618059710883318, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1466, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 282.33950000000186, "firstEventMs": 624.9209580000024, "firstReasoningMs": null, "firstContentMs": 1534.8429170000018, "lastContentMs": 1536.241708000016, "generationMs": 243.06266599998344, "totalMs": 1777.9055829999852, "visibleTokensPerSecond": 32.913322854775835, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 1.3591250000172295, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-11", "category": "easy", "arm": "smart", "at": "2026-09-26T10:20:15.655Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-94-42", "evaluation": { "passed": true, "answer": "ORD-94-42", "expected": "ORD-94-42" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004966553626764076, "classifierCostIndex": 0.004404747655675743, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1137, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 839.976708000002, "firstEventMs": 1114.8745409999974, "firstReasoningMs": null, "firstContentMs": 1866.4516660000081, "lastContentMs": 1874.4678330000024, "generationMs": 220.68620900000678, "totalMs": 2087.137875000015, "visibleTokensPerSecond": 36.250566069580515, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 5.892124999954831, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 189, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-11", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T10:20:17.742Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "ORD-94-42", "evaluation": { "passed": true, "answer": "ORD-94-42", "expected": "ORD-94-42" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.05330951905490397, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 998, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 265.02416600001743, "firstEventMs": 535.6375409999746, "firstReasoningMs": null, "firstContentMs": 1161.315082999994, "lastContentMs": 1165.4218329999712, "generationMs": 113.1341249999823, "totalMs": 1274.4492079999764, "visibleTokensPerSecond": 70.71252816072295, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 2.551000000035856, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-11", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T10:20:19.017Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "ORD-94-42", "evaluation": { "passed": true, "answer": "ORD-94-42", "expected": "ORD-94-42" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010685104441719615, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 680, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 210.51299999997718, "firstEventMs": 572.1595000000088, "firstReasoningMs": null, "firstContentMs": 716.8141659999965, "lastContentMs": 890.5914159999811, "generationMs": 230.91749999998137, "totalMs": 947.7316659999778, "visibleTokensPerSecond": 34.64440763476413, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 147.30158299999312, "finalContentBurstRatio": 0.2222222222222222, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-19", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T10:20:20.135Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04386605301987537, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1349, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 196.03445800003828, "firstEventMs": 493.75887499999953, "firstReasoningMs": null, "firstContentMs": 1550.0750000000116, "lastContentMs": 1550.111583000049, "generationMs": 203.93362500000512, "totalMs": 1754.0086250000168, "visibleTokensPerSecond": 24.51778121435283, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.036583000037353486, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-19", "category": "easy", "arm": "smart", "at": "2026-09-26T10:20:21.889Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004883462995745969, "classifierCostIndex": 0.0044174270701492855, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1403, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 844.7877499999595, "firstEventMs": 1316.9057499999763, "firstReasoningMs": null, "firstContentMs": 2063.5016249999753, "lastContentMs": 2065.9626249999856, "generationMs": 195.54812499997206, "totalMs": 2259.0497499999474, "visibleTokensPerSecond": 25.569153373374018, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 2.4610000000102445, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 199, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-19", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T10:20:24.148Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008795332135609764, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 778, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 239.60183400003007, "firstEventMs": 493.2467090000282, "firstReasoningMs": null, "firstContentMs": 958.2829170000041, "lastContentMs": 958.2955840000068, "generationMs": 64.7862080000341, "totalMs": 1023.0691250000382, "visibleTokensPerSecond": 77.17692012468717, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.012667000002693385, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-19", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T10:20:25.172Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008443950489827026, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3171, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 1083.231958999997, "firstEventMs": 1507.4655419999617, "firstReasoningMs": null, "firstContentMs": 4188.721958999988, "lastContentMs": 4198.77774999995, "generationMs": 135.62825000000885, "totalMs": 4324.3502089999965, "visibleTokensPerSecond": 51.611666448542564, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 10.055790999962483, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-9", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T10:20:29.721Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008443950489827026, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2444, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 300.4612920000218, "firstEventMs": 1152.0224589999998, "firstReasoningMs": null, "firstContentMs": 2396.5549170000013, "lastContentMs": 2396.57058400003, "generationMs": 390.86095800000476, "totalMs": 2787.415875000006, "visibleTokensPerSecond": 17.909181914249707, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.015667000028770417, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-9", "category": "easy", "arm": "smart", "at": "2026-09-26T10:20:32.509Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005292711330987745, "classifierCostIndex": 0.00441391999806086, "promptTokens": 35, "completionTokens": 18, "reasoningTokens": 10, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1468, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "18", "reasoningTokens": "10", "cachedTokens": "0" }, "timing": { "headersMs": 475.3143329999875, "firstEventMs": 799.2461250000051, "firstReasoningMs": null, "firstContentMs": 1836.3389580000076, "lastContentMs": 1859.3154579999973, "generationMs": 197.92474999994738, "totalMs": 2034.263707999955, "visibleTokensPerSecond": 35.36697659086022, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 22.976499999989755, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 157, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-9", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T10:20:34.544Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008795332135609764, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 750, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 259.5352079999866, "firstEventMs": 773.2114999999758, "firstReasoningMs": null, "firstContentMs": 925.18170799996, "lastContentMs": 941.4562919999589, "generationMs": 163.22120900003938, "totalMs": 1088.4029169999994, "visibleTokensPerSecond": 30.633273890274843, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 16.274583999998868, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-9", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T10:20:35.632Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04386605301987537, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1354, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 542.2204170000041, "firstEventMs": 848.5394169999636, "firstReasoningMs": null, "firstContentMs": 1769.7176249999902, "lastContentMs": 1769.7316669999855, "generationMs": 125.02020799997263, "totalMs": 1894.7378329999628, "visibleTokensPerSecond": 39.99353448524973, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.014041999995242804, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2605", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:20:37.699Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"Major mega trends in the tech industry:\n\n- Artificial intelligence, generative models, and autonomous agents\n- Cloud computing, edge computing, and distributed infrastructure\n- Robotics, automation, and intelligent manufacturing\n- Cybersecurity, digital identity, and privacy protection\n- Quantum computing and advanced semiconductor technologies\n- Internet of Things, connected devices, and smart homes\n- Clean technology, renewable energy, and efficient data centers\n- Spatial computing, augmented reality, and virtual reality\n- Biotechnology, digital health, and personalized medicine\n- Blockchain, tokenization, and decentralized platforms\n- Data governance, responsible technology, and trustworthy AI\n- Global connectivity through 5G, satellite networks, and next-generation communications\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.00951765409843762, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 267, "reasoningTokens": 119, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2629, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "267", "reasoningTokens": "119", "cachedTokens": "0" }, "timing": { "headersMs": 280.0933339999756, "firstEventMs": 736.2951250000042, "firstReasoningMs": null, "firstContentMs": 2345.6062089999905, "lastContentMs": 2897.0548340000096, "generationMs": 573.0682909999741, "totalMs": 2918.6744999999646, "visibleTokensPerSecond": 256.51393090253293, "contentChunkCount": 71, "averageContentChunkCharacters": 11.211267605633802, "maxContentStallMs": 133.24599999998463, "finalContentBurstRatio": 0.8329145728643216, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2605", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:20:40.618Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "\"Here are 12 megatrends reshaping the technology industry:\n\n1. Artificial intelligence and automation — Generative AI, autonomous agents, and robotics are transforming software development, operations, and knowledge work.\n\n2. Cloud and edge computing — Organizations are combining cloud platforms with local processing to support connected products, real-time decisions, and operational resilience.\n\n3. Cybersecurity and digital trust — Growing online threats are driving adoption of zero-trust security, stronger authentication, and continuous monitoring.\n\n4. Semiconductor innovation — Demand for computing power is accelerating investment in specialized processors, advanced chip packaging, and more resilient production networks.\n\n5. Data infrastructure and governance — Organizations are modernizing data platforms while strengthening quality controls, privacy protections, and responsible information use.\n\n6. Robotics and autonomous systems — Improvements in perception, motion control, and machine learning are expanding automation across factories, logistics, agriculture, and transportation.\n\n7. Connected devices and industrial IoT — Sensors and connected equipment are enabling remote monitoring, predictive maintenance, and more efficient industrial operations.\n\n8. Sustainable technology — Energy-efficient computing, improved batteries, carbon monitoring, and circular production models are becoming strategic priorities.\n\n9. Spatial computing and digital twins — Augmented reality, immersive interfaces, and virtual models of physical systems are opening new possibilities for training, simulation, and collaboration.\n\n10. Quantum technologies — Quantum computing, sensing, and communication are advancing, though broad commercial adoption remains uncertain and application-dependent.\n\n11. Biotechnology and computational medicine — AI-supported drug discovery, genomic analysis, and personalized treatments are connecting technology more closely with healthcare.\n\n12. Technology sovereignty and regulation — Governments and organizations are prioritizing domestic production, data localization, AI governance, and control over critical technology infrastructure.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.1973892734891767, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 346, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8627, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "346", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 280.6730840000091, "firstEventMs": 603.4749590000138, "firstReasoningMs": null, "firstContentMs": 1315.6682089999667, "lastContentMs": 8832.776583999977, "generationMs": 7975.9152080000495, "totalMs": 9291.583417000016, "visibleTokensPerSecond": 43.25522413452391, "contentChunkCount": 122, "averageContentChunkCharacters": 17.868852459016395, "maxContentStallMs": 474.49829199997475, "finalContentBurstRatio": 0.05779816513761468, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2605", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:20:49.910Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "\"Here is a list of mega trends shaping the world of technology today, going forward into tomorrow:\n\n1. Artificial Intelligence and automation growing across almost every workflow.\n2. Cloud computing solutions supporting global organizations for storage and processing power.\n3. Robotics and autonomous tools transforming manufacturing floors.\n4. Blockchain protocols empowering more transparent and open financial ecosystems.\n5. Internet of Things connecting more objects, tools, and homes to networks.\n6. Quantum computing offering more powerful options for solving complex problems.\n7. Cybersecurity growing more crucial as more organizations move online.\n8. Augmented and virtual reality opening new dimensions for consumer connections.\n9. Green technology promoting more sustainable outcomes for corporations and consumers.\n10. 5G and future networks boosting connection speeds worldwide.\n\nOverall, these trends show how technology continues to evolve, offering more opportunities for growth, innovation, and progress across numerous sectors of our modern world.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2423811708375005, "classifierCostIndex": 0.004438469502679845, "promptTokens": 62, "completionTokens": 340, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5880, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "62", "completionTokens": "340", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 760.1915410000365, "firstEventMs": 1988.7885000000242, "firstReasoningMs": null, "firstContentMs": 1988.8101250000182, "lastContentMs": 5927.61370799999, "generationMs": 4682.045999999973, "totalMs": 6670.856124999991, "visibleTokensPerSecond": 72.40424378572999, "contentChunkCount": 88, "averageContentChunkCharacters": 12.125, "maxContentStallMs": 477.3660840000375, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 310, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2605", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:20:56.582Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "\"1. Generative AI and autonomous agents reshaping software, work, and customer support.\n2. Cloud computing evolving toward hybrid, multicloud, and edge architectures.\n3. Semiconductor innovation powering AI, robotics, and more efficient devices.\n4. Cybersecurity shifting toward zero-trust protection and automated response.\n5. Robotics and automation expanding from factories into homes and services.\n6. Connected devices and the Internet of Things producing real-time operational data.\n7. Digital health combining remote monitoring, diagnostics, and personalized care.\n8. Climate technology focusing on cleaner energy, smarter grids, and lower emissions.\n9. Spatial computing bringing augmented and virtual experiences into work and entertainment.\n10. Data governance and privacy becoming core requirements for responsible technology.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.16880212398537117, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 241, "reasoningTokens": 88, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3769, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "241", "reasoningTokens": "88", "cachedTokens": "0" }, "timing": { "headersMs": 985.1475840000203, "firstEventMs": 1332.5123340000282, "firstReasoningMs": null, "firstContentMs": 3206.5869589999784, "lastContentMs": 4728.536124999984, "generationMs": 1671.165083000029, "totalMs": 4877.752042000007, "visibleTokensPerSecond": 90.95450924999813, "contentChunkCount": 147, "averageContentChunkCharacters": 5.6938775510204085, "maxContentStallMs": 352.897042000026, "finalContentBurstRatio": 0.09438470728793309, "buffered": false }, "error": null, "routing": null }, { "caseId": "hypergeometric", "category": "probability", "arm": "gpt-6-luna", "at": "2026-09-26T10:21:01.706Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "The probability is\n\\[\n\\frac{\\binom{8}{2}\\binom{7}{3}}{\\binom{15}{5}}\n=\\frac{980}{3003}\n=\\frac{140}{429}.\n\\]\n\nFINAL: 140/429", "evaluation": { "passed": true, "answer": "140/429", "expected": "140/429", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.006610156449743985, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 176, "reasoningTokens": 116, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2163, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "176", "reasoningTokens": "116", "cachedTokens": "0" }, "timing": { "headersMs": 1643.4990419999813, "firstEventMs": 1941.3074589999742, "firstReasoningMs": null, "firstContentMs": 3637.836249999993, "lastContentMs": 3795.835583999986, "generationMs": 174.10162500001024, "totalMs": 3811.9378750000033, "visibleTokensPerSecond": 338.88253484134066, "contentChunkCount": 43, "averageContentChunkCharacters": 2.86046511627907, "maxContentStallMs": 116.32900000002701, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "hypergeometric", "category": "probability", "arm": "gpt-6-sol", "at": "2026-09-26T10:21:05.518Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "FINAL: 140/429", "evaluation": { "passed": true, "answer": "140/429", "expected": "140/429", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.08712983385225748, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 114, "reasoningTokens": 102, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2597, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "114", "reasoningTokens": "102", "cachedTokens": "0" }, "timing": { "headersMs": 235.55483300000196, "firstEventMs": 480.4576249999809, "firstReasoningMs": 2047.5638749999925, "firstContentMs": 2707.450375000015, "lastContentMs": 2735.303332999989, "generationMs": 128.41904199996497, "totalMs": 2835.86941699998, "visibleTokensPerSecond": 85.65707879991037, "contentChunkCount": 6, "averageContentChunkCharacters": 2.3333333333333335, "maxContentStallMs": 15.123041999991983, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "hypergeometric", "category": "probability", "arm": "gpt-6-astra", "at": "2026-09-26T10:21:08.354Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "There are \\(\\binom{15}{5}\\) equally likely selections. Exactly 2 red balls means choosing 2 of the 8 red balls and 3 of the 7 blue balls:\n\n\\[\nP=\\frac{\\binom{8}{2}\\binom{7}{3}}{\\binom{15}{5}}\n=\\frac{28\\cdot35}{3003}\n=\\frac{140}{429}.\n\\]\n\nFINAL: 140/429", "evaluation": { "passed": true, "answer": "140/429", "expected": "140/429", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5767993787032953, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 156, "reasoningTokens": 54, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4629, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "156", "reasoningTokens": "54", "cachedTokens": "0" }, "timing": { "headersMs": 236.27133399999002, "firstEventMs": 535.7259590000031, "firstReasoningMs": 2963.3350419999915, "firstContentMs": 4371.846834000025, "lastContentMs": 4865.391125000024, "generationMs": 541.414832999988, "totalMs": 4913.261667000013, "visibleTokensPerSecond": 186.5482691716395, "contentChunkCount": 59, "averageContentChunkCharacters": 4.254237288135593, "maxContentStallMs": 491.9117500000284, "finalContentBurstRatio": 0.9641434262948207, "buffered": true }, "error": null, "routing": null }, { "caseId": "hypergeometric", "category": "probability", "arm": "smart", "at": "2026-09-26T10:21:13.269Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 140/429", "evaluation": { "passed": true, "answer": "140/429", "expected": "140/429", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.08195838628309648, "classifierCostIndex": 0.004529653376978937, "promptTokens": 113, "completionTokens": 92, "reasoningTokens": 81, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3167, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "113", "completionTokens": "92", "reasoningTokens": "81", "cachedTokens": "0" }, "timing": { "headersMs": 798.4360830000369, "firstEventMs": 1579.7022920000018, "firstReasoningMs": 3959.867083000019, "firstContentMs": 3959.94879200001, "lastContentMs": 3959.9509580000304, "generationMs": 18.103875000029802, "totalMs": 3978.05266700004, "visibleTokensPerSecond": 552.3679322787823, "contentChunkCount": 2, "averageContentChunkCharacters": 7, "maxContentStallMs": 0.002166000020224601, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 192, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2622", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:21:17.406Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "How about **The Melbourne Buzz**? It sounds lively and could cover the stories, events and issues teenagers care about.\n\nP.S. Its tagline could be: *Your city. Your stories.*", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.10547721637024907, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 147, "reasoningTokens": 102, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4091, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "147", "reasoningTokens": "102", "cachedTokens": "0" }, "timing": { "headersMs": 286.4125420000055, "firstEventMs": 525.7427499999758, "firstReasoningMs": 2574.293791999982, "firstContentMs": 3865.8898339999723, "lastContentMs": 4372.372042000003, "generationMs": 557.0079160000314, "totalMs": 4422.897750000004, "visibleTokensPerSecond": 78.99349135999984, "contentChunkCount": 39, "averageContentChunkCharacters": 4.461538461538462, "maxContentStallMs": 458.8790830000071, "finalContentBurstRatio": 0.5517241379310345, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2622", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:21:21.830Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "**The Melbourne Pulse** \n*Your city. Your stories. Your voice.*\n\nA fresh name for a newspaper covering what matters to Melbourne teens—from music and sport to local news and issues shaping their future.\n\nP.S. Let teen readers pitch stories and help choose the front page—it should feel like their newspaper.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3447310231165892, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 93, "reasoningTokens": 25, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3964, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "93", "reasoningTokens": "25", "cachedTokens": "0" }, "timing": { "headersMs": 267.7363749999786, "firstEventMs": 1324.9930000000168, "firstReasoningMs": 3203.6531250000116, "firstContentMs": 3986.2273750000168, "lastContentMs": 4226.417041999986, "generationMs": 249.7034589999821, "totalMs": 4235.930833999999, "visibleTokensPerSecond": 268.31826947180895, "contentChunkCount": 47, "averageContentChunkCharacters": 6.553191489361702, "maxContentStallMs": 140.99662499997066, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2622", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:21:26.066Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "**The Melbourne Buzz** — a lively name for a newspaper made by and for Melbourne teens.\n\nP.S. It could cover local news, music, sport, school life and teen perspectives.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.007049889334677469, "classifierCostIndex": 0.004438469502679845, "promptTokens": 46, "completionTokens": 66, "reasoningTokens": 22, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2574, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "66", "reasoningTokens": "22", "cachedTokens": "0" }, "timing": { "headersMs": 842.8291670000181, "firstEventMs": 1190.2694170000032, "firstReasoningMs": 2463.1238750000484, "firstContentMs": 3394.6556669999845, "lastContentMs": 3397.531042000046, "generationMs": 27.121291000046767, "totalMs": 3421.7769580000313, "visibleTokensPerSecond": 1585.4702491826754, "contentChunkCount": 35, "averageContentChunkCharacters": 4.828571428571428, "maxContentStallMs": 0.774208000046201, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 210, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2622", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:21:29.488Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "How about **The Melbourne Mix**—a lively name for a newspaper covering teen life, local news, culture and events.\n\nP.S. It could also feature a regular section called “The Teen Scene.”", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005672689103029962, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 155, "reasoningTokens": 108, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3225, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "155", "reasoningTokens": "108", "cachedTokens": "0" }, "timing": { "headersMs": 476.4167080000043, "firstEventMs": 834.5554170000833, "firstReasoningMs": 2560.5917920001084, "firstContentMs": 3644.872250000015, "lastContentMs": 3698.964542000089, "generationMs": 61.21500000008382, "totalMs": 3706.0872500000987, "visibleTokensPerSecond": 751.4498080525527, "contentChunkCount": 37, "averageContentChunkCharacters": 4.972972972972973, "maxContentStallMs": 51.51858400006313, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3631", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:21:33.364Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "**The PB&J Song**\n\nWash your hands and clear a space \nSet the bread out in its place \nGrab the peanut butter jar \nAnd the jelly from afar \n\nSpread the peanut butter smooth and wide \nOn one slice of bread on its side \nSpread the jelly on the other \nNow bring the slices close together \n\n**Chorus** \nStack it up and press it tight \nPB&J tastes just right \nCut it once or take a bite \nSandwich time is pure delight \n\nPut the jars away when you’re done \nClean the knife and have some fun \nTake your sandwich on a plate \nYou made a snack that tastes so great!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.006502246539330859, "classifierCostIndex": 0, "promptTokens": 28, "completionTokens": 183, "reasoningTokens": 43, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4838, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "28", "completionTokens": "183", "reasoningTokens": "43", "cachedTokens": "0" }, "timing": { "headersMs": 280.73474999994505, "firstEventMs": 627.1913329999661, "firstReasoningMs": 2059.802415999933, "firstContentMs": 2761.319790999987, "lastContentMs": 5139.949707999942, "generationMs": 2378.7579589999514, "totalMs": 5140.0777499999385, "visibleTokensPerSecond": 58.433855985262454, "contentChunkCount": 69, "averageContentChunkCharacters": 8.26086956521739, "maxContentStallMs": 2195.126166000031, "finalContentBurstRatio": 0.7719298245614035, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3631", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:21:38.506Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "**Peanut Butter Jelly Jam**\n\n[Verse 1]\nGrab two slices of your favorite bread\nSet them on a plate and get ready to spread\nOpen up the peanut butter smooth or crunchy style\nScoop a little out and stack up a smile\n\n[Chorus]\nSpread it to the left\nSpread it to the right\nPeanut butter jelly\nWhat a tasty little bite\nPut the sticky sides together\nGive a gentle press\nPeanut butter jelly\nYou're a sandwich-making success\n\n[Verse 2]\nGrab a clean spoon for the jelly jar\nGrape or strawberry can be your star\nSpread it on the other slice from edge to edge\nThen flip it on the peanut butter like a little bread bridge\n\n[Bridge]\nCut it into triangles\nOr leave it in a square\nPut away the jars\nAnd wipe the counter with care\n\n[Final Chorus]\nSpread it to the left\nSpread it to the right\nPeanut butter jelly\nNow your lunch is looking bright\nTwo slices full of happiness\nMade by you today\nTake a bite and sing along\nThe PB and J way", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8553721846194777, "classifierCostIndex": 0, "promptTokens": 28, "completionTokens": 248, "reasoningTokens": 16, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 7141, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "28", "completionTokens": "248", "reasoningTokens": "16", "cachedTokens": "0" }, "timing": { "headersMs": 573.3746660000179, "firstEventMs": 904.2300000000978, "firstReasoningMs": 2440.035416000057, "firstContentMs": 3144.0891660000198, "lastContentMs": 7690.116833000095, "generationMs": 4569.2813340000575, "totalMs": 7713.370500000077, "visibleTokensPerSecond": 50.554996095584485, "contentChunkCount": 99, "averageContentChunkCharacters": 9.262626262626263, "maxContentStallMs": 314.19645899999887, "finalContentBurstRatio": 0.12540894220283533, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3631", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:21:46.220Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "**The PB and J Song**\n\nTake two slices of bread\nLay them side by side\nGrab the peanut butter\nSpread it far and wide\n\nScoop some jelly from the jar\nSpread it on the other slice\nPut the two together\nNow your sandwich looks so nice\n\nPeanut butter jelly time\nA little sweet and a little nutty\nCut it into triangles\nAnd share one with a buddy!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.08615931909547944, "classifierCostIndex": 0, "promptTokens": 28, "completionTokens": 122, "reasoningTokens": 32, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2633, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "28", "completionTokens": "122", "reasoningTokens": "32", "cachedTokens": "0" }, "timing": { "headersMs": 421.2739999999758, "firstEventMs": 693.1548750000075, "firstReasoningMs": 1720.8578330000164, "firstContentMs": 2297.5426669999724, "lastContentMs": 2965.451875000028, "generationMs": 773.2480000000214, "totalMs": 3070.790666999994, "visibleTokensPerSecond": 115.09890746564818, "contentChunkCount": 84, "averageContentChunkCharacters": 4.023809523809524, "maxContentStallMs": 134.63879200001247, "finalContentBurstRatio": 0.14497041420118342, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3631", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:21:49.291Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "**“The PB&J Song”**\n\nGrab two slices of bread \nSet them on a plate \nGet the peanut butter \nAnd the jelly you love to taste \n\nSpread the peanut butter \nFrom corner unto corner \nSpread the jelly on the other \nNow your sandwich is a warmer \n\nPut the slices together \nJelly side meets the PB \nPress them gently in the middle \nThat’s a tasty recipe \n\nCut it down the center \nOr leave it whole and wide \nTake a happy little bite \nAnd enjoy the PB&J ride!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009226567115098215, "classifierCostIndex": 0.004375342205088168, "promptTokens": 28, "completionTokens": 135, "reasoningTokens": 19, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2349, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "28", "completionTokens": "135", "reasoningTokens": "19", "cachedTokens": "0" }, "timing": { "headersMs": 1795.0025000000605, "firstEventMs": 2017.8493340000277, "firstReasoningMs": null, "firstContentMs": 3969.8956250000047, "lastContentMs": 4052.43345900008, "generationMs": 103.50808399997186, "totalMs": 4073.4037089999765, "visibleTokensPerSecond": 1111.024333133548, "contentChunkCount": 63, "averageContentChunkCharacters": 7.349206349206349, "maxContentStallMs": 72.21424999996088, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 856, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2432", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:21:53.588Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "I’m so sorry about your best friend. Losing them yesterday is so recent; you don’t have to know how to carry this yet. I’m here to listen, whether you want to tell me about them, put a memory into words, or just talk through the next few minutes.\n\nHere’s a small fictional story that might feel familiar: After Maya lost her closest friend in an accident at the lake, she kept reaching for her phone to send him jokes. One night, she wrote one in a notebook instead, along with what she imagined he’d say back. It didn’t take away her grief, but it gave her a place to put some of the love she still had for him.\n\nIf you’d like, what was your friend like?", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.30463777033953277, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 441, "reasoningTokens": 284, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5714, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "441", "reasoningTokens": "284", "cachedTokens": "0" }, "timing": { "headersMs": 201.82929200003855, "firstEventMs": 469.3217500000028, "firstReasoningMs": null, "firstContentMs": 4172.45541699999, "lastContentMs": 5804.972209000029, "generationMs": 1758.7310000000289, "totalMs": 5931.186417000019, "visibleTokensPerSecond": 88.70031858197612, "contentChunkCount": 151, "averageContentChunkCharacters": 4.337748344370861, "maxContentStallMs": 51.40025000006426, "finalContentBurstRatio": 0.2641221374045801, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2432", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:21:59.519Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "I’m so, so sorry about your best friend. A loss this sudden can make the world feel unreal, and you don’t have to know what to say or do right now. I’m here with you.\n\nI can’t honestly share a personal memory, but I can offer a small imagined story: Someone lost their closest friend in a water accident and found that the hardest moments came unexpectedly—a song, a familiar place, a message they almost sent. A friend sat beside them without trying to fix anything. They shared one funny memory, then sat quietly. It didn’t make the loss smaller, but it helped them feel less alone.\n\nIf you can, reach out to someone you trust and ask them to stay with you today. I can also listen while you tell me about your friend, help you write a message to someone, or just keep you company.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01781727508308709, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 507, "reasoningTokens": 328, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 4810, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "507", "reasoningTokens": "328", "cachedTokens": "0" }, "timing": { "headersMs": 292.9753750000382, "firstEventMs": 1109.5990830000956, "firstReasoningMs": null, "firstContentMs": 4282.018958000001, "lastContentMs": 5097.823291000095, "generationMs": 824.6849580000853, "totalMs": 5106.703916000086, "visibleTokensPerSecond": 215.8399983815172, "contentChunkCount": 77, "averageContentChunkCharacters": 10.168831168831169, "maxContentStallMs": 123.46816699998453, "finalContentBurstRatio": 0.4444444444444444, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2432", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:22:04.626Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "I’m so sorry. Losing your best friend so suddenly is heartbreaking, and you don’t have to find the right words or make sense of it right now.\n\nI can stay with you here, listen to stories about them, or help you write a message to someone you trust. If it helps, here’s a small imagined scene: someone grieving sits quietly with a friend, sharing one favorite memory at a time. They don’t try to fix the pain; they just make room for it, together.\n\nI can’t offer a personal story of my own, but I can listen to yours. What was something about your friend that always made you smile?", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.014785411262642332, "classifierCostIndex": 0.004466526079387257, "promptTokens": 51, "completionTokens": 289, "reasoningTokens": 152, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3607, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "289", "reasoningTokens": "152", "cachedTokens": "0" }, "timing": { "headersMs": 591.3634580000071, "firstEventMs": 1531.4967079999624, "firstReasoningMs": null, "firstContentMs": 3691.341207999969, "lastContentMs": 4192.248458000016, "generationMs": 511.1359170000069, "totalMs": 4202.477124999976, "visibleTokensPerSecond": 266.0740430807921, "contentChunkCount": 69, "averageContentChunkCharacters": 8.420289855072463, "maxContentStallMs": 116.57983399997465, "finalContentBurstRatio": 0.8605851979345955, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 201, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2432", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:22:08.829Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "I’m so sorry you lost your best friend. With this happening only yesterday, you don’t have to make sense of it or know how to cope right now. Whatever you’re feeling—sadness, numbness, anger, or all of them—is welcome here.\n\nI don’t have personal memories to share, but here’s a small fictional story about a similar loss:\n\nSomeone lost their closest friend suddenly. The next morning, they picked up their phone to send that friend something funny, then remembered. They sat on the kitchen floor and cried. Later, another friend came over with food and sat beside them without trying to make anything better. Eventually, they shared one funny memory. The laugh didn’t erase the sadness, and it wasn’t a betrayal. For a moment, there was room for both.\n\nFor now, a sip of water and someone nearby may be enough. If reaching out feels hard, you could text: “I’m having a really hard time. Can you stay with me or call?”\n\nI can listen, help you write a tribute, or help you find words to ask for support. If you’d like, what’s one thing you wish I knew about your best friend?", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.2284228148501113, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 354, "reasoningTokens": 107, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 10998, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "354", "reasoningTokens": "107", "cachedTokens": "0" }, "timing": { "headersMs": 521.0202089999802, "firstEventMs": 976.9187920000404, "firstReasoningMs": null, "firstContentMs": 5914.481875000056, "lastContentMs": 11496.420584000065, "generationMs": 5611.653416999965, "totalMs": 11526.13529200002, "visibleTokensPerSecond": 43.83734734129635, "contentChunkCount": 100, "averageContentChunkCharacters": 10.74, "maxContentStallMs": 1001.546374999918, "finalContentBurstRatio": 0.17970204841713222, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1393", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:22:20.595Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "### Pros\n- **More clarity for different audiences:** Different synonyms can match the terminology familiar to particular groups.\n- **More flexibility:** Different names or synonyms can suit different contexts, tones, or levels of formality.\n- **Better discoverability:** Using multiple synonyms can help people find information even if they search for a different name.\n\n### Cons\n- **Possible confusion:** People may wonder whether the names refer to the same thing or to different things.\n- **Inconsistent communication:** Teams may use different synonyms and misunderstand one another.\n- **Harder organization:** Multiple names can complicate documentation, search, and record-keeping.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010416273877402918, "classifierCostIndex": 0.0043928775655303, "promptTokens": 33, "completionTokens": 168, "reasoningTokens": 35, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2543, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "168", "reasoningTokens": "35", "cachedTokens": "0" }, "timing": { "headersMs": 496.1936670000432, "firstEventMs": 794.348333000089, "firstReasoningMs": 2092.5991670000367, "firstContentMs": 2881.188000000082, "lastContentMs": 3034.8902080000844, "generationMs": 181.31529199995566, "totalMs": 3062.5032920000376, "visibleTokensPerSecond": 728.013608471768, "contentChunkCount": 67, "averageContentChunkCharacters": 10.253731343283581, "maxContentStallMs": 148.69262499990873, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 168, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1393", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:22:23.658Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Using two different names for the same thing—often called **synonyms**—can be helpful, but it can also cause confusion.\n\n### Pros\n- **Adds variety:** Synonyms reduce repetition and make writing or speech more engaging.\n- **Fits different audiences:** A technical name may suit specialists, while a familiar name helps general readers.\n- **Adjusts tone:** Different names can sound formal, casual, friendly, or professional.\n- **Improves discoverability:** Including synonyms can help people find information using different search terms.\n- **Connects communities:** Alternative names can bridge regional, cultural, or professional vocabulary.\n\n### Cons\n- **Creates ambiguity:** People may assume two names refer to two different things.\n- **Increases learning effort:** Readers or users must learn and remember both names.\n- **Weakens consistency:** Switching labels can make instructions, interfaces, and documentation harder to follow.\n- **Introduces subtle differences:** Synonyms are not always interchangeable; their connotations or typical uses may differ.\n- **Complicates organization:** Multiple names can lead to duplicate records, inconsistent tags, or missed search results.\n\n**Rule of thumb:** Use synonyms for variety and accessibility, but choose one primary name when precision and consistency matter.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8756120371913395, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 253, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5527, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "253", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 520.7979169999016, "firstEventMs": 787.9337499999674, "firstReasoningMs": null, "firstContentMs": 1498.8992499999003, "lastContentMs": 6044.513624999905, "generationMs": 4614.009542000014, "totalMs": 6112.908791999915, "visibleTokensPerSecond": 54.616271966088455, "contentChunkCount": 96, "averageContentChunkCharacters": 13.708333333333334, "maxContentStallMs": 1213.2160409999778, "finalContentBurstRatio": 0.22112462006079028, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1393", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:22:29.771Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "Using two names for the same thing can be useful, but it can also cause confusion.\n\n**Pros**\n- Synonyms can help different audiences recognize the same thing.\n- Synonyms give writers more variety and help avoid repetition.\n- Familiar synonyms can make a technical term easier to explain.\n\n**Cons**\n- People may assume the two names refer to different things.\n- Inconsistent naming can make searching and record-keeping harder.\n- If the synonyms carry slightly different connotations, they may create misunderstandings.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0976389102526157, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 138, "reasoningTokens": 31, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2492, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "138", "reasoningTokens": "31", "cachedTokens": "0" }, "timing": { "headersMs": 273.9139590000268, "firstEventMs": 577.3290419999976, "firstReasoningMs": 1664.3454999999376, "firstContentMs": 2362.112749999971, "lastContentMs": 2690.439333999995, "generationMs": 409.28295899997465, "totalMs": 2771.395708999946, "visibleTokensPerSecond": 258.9895270963543, "contentChunkCount": 101, "averageContentChunkCharacters": 5.128712871287129, "maxContentStallMs": 41.36604100000113, "finalContentBurstRatio": 0.6158301158301158, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1393", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:22:32.543Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "### Pros\n- **More choice:** Synonyms let people pick the word that best fits their tone, audience, or context.\n- **Better communication across groups:** Different communities may use different names for the same thing, and recognizing both synonyms can help people understand one another.\n- **More expressive language:** Synonyms can add variety or emphasize slightly different associations.\n\n### Cons\n- **Potential confusion:** People may not realize two names refer to the same thing, especially if they encounter unfamiliar synonyms.\n- **Inconsistent communication:** Using different synonyms across documents or teams can make instructions and information harder to follow.\n- **Search and organization challenges:** Information may be harder to find if it is filed under one name but searched for using another.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.007433643953584144, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 209, "reasoningTokens": 56, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2778, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "209", "reasoningTokens": "56", "cachedTokens": "0" }, "timing": { "headersMs": 272.4769170000218, "firstEventMs": 535.4626250000438, "firstReasoningMs": 1687.2270420000423, "firstContentMs": 2805.7509590000845, "lastContentMs": 3059.831625000108, "generationMs": 257.7764999999199, "totalMs": 3063.5274590000045, "visibleTokensPerSecond": 589.6580952881556, "contentChunkCount": 72, "averageContentChunkCharacters": 11.319444444444445, "maxContentStallMs": 216.69866700004786, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-2", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T10:22:36.076Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "-2,0,15,31", "evaluation": { "passed": true, "answer": "-2,0,15,31", "expected": "-2,0,15,31" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012032629448003512, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 965, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 263.5854169999948, "firstEventMs": 557.1802919999463, "firstReasoningMs": null, "firstContentMs": 1223.6832500000019, "lastContentMs": 1225.0395419999259, "generationMs": 29.975582999992184, "totalMs": 1253.658832999994, "visibleTokensPerSecond": 366.96533975679034, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 0.6870000000344589, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-2", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T10:22:37.330Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "-2,0,15,31", "evaluation": { "passed": true, "answer": "-2,0,15,31", "expected": "-2,0,15,31" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0600525395818441, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1796, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 259.3534170000348, "firstEventMs": 662.8710420000134, "firstReasoningMs": null, "firstContentMs": 1328.9399589999812, "lastContentMs": 1390.2453749999404, "generationMs": 761.4747910000151, "totalMs": 2090.4147499999963, "visibleTokensPerSecond": 14.445652213324264, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 50.713417000020854, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-2", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T10:22:39.420Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-2,0,15,31", "evaluation": { "passed": true, "answer": "-2,0,15,31", "expected": "-2,0,15,31" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0013502227540442258, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 33, "reasoningTokens": 19, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2516, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "33", "reasoningTokens": "19", "cachedTokens": "0" }, "timing": { "headersMs": 628.9274169999408, "firstEventMs": 918.5582089999225, "firstReasoningMs": 2090.331208999967, "firstContentMs": 3120.307334000012, "lastContentMs": 3123.436624999973, "generationMs": 45.367874999996275, "totalMs": 3165.675209000008, "visibleTokensPerSecond": 286.5463722953977, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 3.100082999910228, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-2", "category": "easy", "arm": "smart", "at": "2026-09-26T10:22:42.586Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "-2,0,15,31", "evaluation": { "passed": true, "answer": "-2,0,15,31", "expected": "-2,0,15,31" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005013764212569817, "classifierCostIndex": 0.004385863421353446, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1352, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 846.0763329999754, "firstEventMs": 1186.705249999999, "firstReasoningMs": null, "firstContentMs": 1940.4583329999587, "lastContentMs": 1978.3627499999711, "generationMs": 267.11308399995323, "totalMs": 2207.571416999912, "visibleTokensPerSecond": 41.18106022841594, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 9.037332999985665, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 257, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-6", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T10:22:44.972Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-59-27", "evaluation": { "passed": true, "answer": "ORD-59-27", "expected": "ORD-59-27" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0005618059710883318, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1982, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 320.7690409999341, "firstEventMs": 745.7785409999778, "firstReasoningMs": null, "firstContentMs": 1962.6459579999791, "lastContentMs": 2011.984582999954, "generationMs": 303.74887500004843, "totalMs": 2266.3948330000276, "visibleTokensPerSecond": 26.33754610613364, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 19.337915999931283, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-6", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T10:22:47.238Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "ORD-59-27", "evaluation": { "passed": true, "answer": "ORD-59-27", "expected": "ORD-59-27" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010685104441719615, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 711, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 250.55387499998324, "firstEventMs": 511.2828750000335, "firstReasoningMs": null, "firstContentMs": 852.1160000000382, "lastContentMs": 880.1772920000367, "generationMs": 125.13437499990687, "totalMs": 977.250374999945, "visibleTokensPerSecond": 63.93127388062596, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 9.104083000100218, "finalContentBurstRatio": 0.2222222222222222, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-6", "category": "easy", "arm": "smart", "at": "2026-09-26T10:22:48.216Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "ORD-59-27", "evaluation": { "passed": true, "answer": "ORD-59-27", "expected": "ORD-59-27" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004966553626764076, "classifierCostIndex": 0.004404747655675743, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1085, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 643.3401669999585, "firstEventMs": 890.56012499996, "firstReasoningMs": null, "firstContentMs": 1629.1311670000432, "lastContentMs": 1648.9095840000082, "generationMs": 116.89066699997056, "totalMs": 1746.0218340000138, "visibleTokensPerSecond": 68.44002353072392, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 9.151832999894395, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 147, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-6", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T10:22:49.962Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "ORD-59-27", "evaluation": { "passed": true, "answer": "ORD-59-27", "expected": "ORD-59-27" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.05330951905490397, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 1061, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 781.3283330000704, "firstEventMs": 1078.0061670000432, "firstReasoningMs": null, "firstContentMs": 1715.1607080000686, "lastContentMs": 1715.201708000037, "generationMs": 221.8511249999283, "totalMs": 1937.0118329999968, "visibleTokensPerSecond": 36.060218310827075, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.030458999914117157, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1107", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:22:52.228Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Why did the rocket break up with the moon?\nIt needed some space.\n\n******\n\nWhat is a rocket’s favorite meal?\nLaunch.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.4303946310611084, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 121, "reasoningTokens": 88, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3379, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "121", "reasoningTokens": "88", "cachedTokens": "0" }, "timing": { "headersMs": 322.20162499998696, "firstEventMs": 918.8859579999698, "firstReasoningMs": null, "firstContentMs": 3539.336291000014, "lastContentMs": 3697.9322910000337, "generationMs": 189.41474999999627, "totalMs": 3728.7510410000104, "visibleTokensPerSecond": 168.94143671493708, "contentChunkCount": 27, "averageContentChunkCharacters": 4.2592592592592595, "maxContentStallMs": 92.78370799997356, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1107", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:22:55.957Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "Why did the rocket break up with the moon? It needed space.\n******\nWhy did the rocket become a comedian? Its jokes always took off.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.07265978930279751, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 101, "reasoningTokens": 66, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2579, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "101", "reasoningTokens": "66", "cachedTokens": "0" }, "timing": { "headersMs": 506.25325000006706, "firstEventMs": 858.940333000035, "firstReasoningMs": null, "firstContentMs": 3078.468292000005, "lastContentMs": 3084.1181250000373, "generationMs": 44.15758300002199, "totalMs": 3122.625875000027, "visibleTokensPerSecond": 769.9696788201263, "contentChunkCount": 29, "averageContentChunkCharacters": 4.517241379310345, "maxContentStallMs": 2.77820800000336, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1107", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:22:59.080Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Why did the rocket bring a pencil? It wanted to draw a launch plan.\n******\nWhat do rockets eat for breakfast? Launch cereal.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005707490049138194, "classifierCostIndex": 0.004396384637618726, "promptTokens": 33, "completionTokens": 31, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2309, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "31", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1931.1081249999115, "firstEventMs": 2978.572124999948, "firstReasoningMs": null, "firstContentMs": 3830.807374999975, "lastContentMs": 4241.446582999895, "generationMs": 524.3161250000121, "totalMs": 4355.123499999987, "visibleTokensPerSecond": 57.21738960440957, "contentChunkCount": 27, "averageContentChunkCharacters": 4.592592592592593, "maxContentStallMs": 390.67524999997113, "finalContentBurstRatio": 0.8064516129032258, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 163, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1107", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:23:03.435Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Why did the rocket bring a ladder? It wanted to reach new heights.******Why did the rocket break up with the satellite? It needed more space.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.003030919608728647, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 81, "reasoningTokens": 44, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 2269, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "81", "reasoningTokens": "44", "cachedTokens": "0" }, "timing": { "headersMs": 296.09841699991375, "firstEventMs": 613.4736669999547, "firstReasoningMs": null, "firstContentMs": 2429.283083999995, "lastContentMs": 2621.3091669999994, "generationMs": 192.1537079999689, "totalMs": 2621.436791999964, "visibleTokensPerSecond": 187.35001460396396, "contentChunkCount": 31, "averageContentChunkCharacters": 4.548387096774194, "maxContentStallMs": 160.38254199991934, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2471", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:23:06.252Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "# Executive Demands and Presidential Well-Being\n\n**[Student Name]** \n**[Department]** \n**[Course Number and Title]** \n**[Instructor Name]** \n**[Institution]** \n**[Submission Date]**\n\n## Abstract\n\nThe presidency combines extensive decision-making, public visibility, and responsibility for national affairs. These features make the office a useful setting for studying how demanding work affects a leader’s well-being and performance. This paper examines the sources of presidential demands, their possible effects on judgment, and the practices that may support effective leadership. Drawing on scholarship in political science, psychology, and organizational studies, it argues that structured routines, trusted advisers, adequate rest, and clear communication can help presidents sustain sound decision-making. Because access to presidential health information varies, conclusions about individual presidents should be made with care.\n\n## Introduction\n\nThe president of the United States leads the executive branch, represents the country in domestic and international affairs, and makes decisions with far-reaching consequences. The office also involves a continuous flow of briefings, meetings, public appearances, and urgent requests. These responsibilities can place substantial demands on a president’s time, attention, and emotional resources.\n\nStudying these demands is relevant to both leadership and public administration. Presidential decisions may shape national policy, so the conditions under which those decisions are made matter. At the same time, the presidency is occupied by an individual with ordinary human needs for rest, reflection, and social connection. This paper considers how the demands of presidential service relate to well-being and decision-making, and what institutional practices can support effective leadership.\n\n## Sources of Presidential Demands\n\nPresidential demands arise from several features of the office. First, the president receives information from many channels, including agency reports, intelligence briefings, legislative updates, and communications with foreign leaders. Making sense of this material requires sustained attention and the ability to distinguish urgent matters from longer-term priorities [Scholar One, Year].\n\nSecond, presidential work is highly visible. Public remarks, policy choices, and interactions with other leaders receive extensive attention from citizens, news organizations, and political institutions. This visibility can encourage careful preparation, while also making private reflection and personal time harder to protect [Researcher Two, Year].\n\nThird, the president’s schedule is shaped by events beyond any one person’s control. National emergencies, legislative negotiations, and international developments may require rapid attention. Organizational research suggests that roles with broad responsibility and frequent interruptions call for reliable systems of delegation and communication [Author Three, Year; Author Four, Year].\n\n## Well-Being and Decision-Making\n\nA president’s well-being is relevant because decision-making depends on attention, memory, judgment, and the ability to weigh different perspectives. Research on sleep and cognition, for example, indicates that regular rest supports concentration and information processing [Researcher Five, Year]. Findings from leadership studies also suggest that reflection and consultation can improve the quality of complex decisions [Scholar Six, Year].\n\nThese findings do not mean that every demanding period produces the same effects. People respond differently to workload, and the surrounding environment matters. A president who has access to candid advisers, dependable staff, and clear procedures may be better positioned to review information carefully. In contrast, a schedule with few opportunities for reflection may make it harder to compare options and consider longer-term consequences [Author Seven, Year].\n\nIt is also important to distinguish general observations from claims about a particular president. Public schedules and biographies provide some information about the work of the office, but they cannot establish an individual’s private experience or health status. Responsible analysis should rely on verified sources and avoid drawing conclusions from appearance or rumor [Historian Eight, Year].\n\n## Practices That Support Effective Leadership\n\nSeveral institutional practices can help presidents manage the demands of the office. A well-organized briefing process can present essential information clearly and identify areas of uncertainty [Policy Analyst Nine, Year]. Delegation allows senior officials to address matters within their expertise, while preserving presidential attention for decisions that require direct involvement [Scholar Ten, Year].\n\nProtected time for reading, reflection, and discussion can also support careful judgment. Such time need not be separate from official duties; it can be built into the daily schedule through focused briefings and structured decision meetings [Author Eleven, Year]. Regular opportunities for physical activity and rest may further support sustained attention, according to research on health and cognitive performance [Researcher Twelve, Year].\n\nFinally, trusted advisers can provide perspective and offer direct feedback. A strong advisory environment is not simply a source of agreement; it gives the president access to relevant evidence, differing viewpoints, and clear explanations of possible outcomes [Scholar Thirteen, Year]. These practices support both the individual officeholder and the institutions that depend on presidential decisions.\n\n## Conclusion\n\nThe presidency brings together broad responsibility, constant public attention, and a steady flow of information. These features make well-being an important element of executive leadership. Research suggests that rest, thoughtful scheduling, sound delegation, and candid advice can support attention and judgment. Further study may clarify how presidential routines affect decision-making across different periods and administrations [Researcher Fourteen, Year].\n\nBecause access to private information is limited, scholarship should use measured language and verified evidence when discussing individual presidents. A focus on workplace demands and institutional supports offers a productive way to examine presidential well-being without making unsupported personal claims. This approach can contribute to a fuller understanding of how the nation’s highest office functions [Author Fifteen, Year].\n\n## References\n\n[Scholar One]. ([Year]). *[Title of work on executive decision-making]*. [Publisher or Journal].\n\n[Researcher Two]. ([Year]). *[Title of work on public visibility and leadership]*. [Publisher or Journal].\n\n[Author Three]. ([Year]). *[Title of work on organizational demands]*. [Publisher or Journal].\n\n[Author Four]. ([Year]). *[Title of work on delegation and communication]*. [Publisher or Journal].\n\n[Researcher Five]. ([Year]). *[Title of work on sleep and cognition]*. [Publisher or Journal].\n\n[Scholar Six]. ([Year]). *[Title of work on consultation and judgment]*. [Publisher or Journal].\n\n[Author Seven]. ([Year]). *[Title of work on leadership routines]*. [Publisher or Journal].\n\n[Historian Eight]. ([Year]). *[Title of historical study of presidential health]*. [Publisher or Journal].\n\n[Policy Analyst Nine]. ([Year]). *[Title of work on briefing systems]*. [Publisher or Journal].\n\n[Scholar Ten]. ([Year]). *[Title of work on presidential delegation]*. [Publisher or Journal].\n\n[Author Eleven]. ([Year]). *[Title of work on executive scheduling]*. [Publisher or Journal].\n\n[Researcher Twelve]. ([Year]). *[Title of work on health and cognitive performance]*. [Publisher or Journal].\n\n[Scholar Thirteen]. ([Year]). *[Title of work on advisory systems]*. [Publisher or Journal].\n\n[Researcher Fourteen]. ([Year]). *[Title of work on presidential routines]*. [Publisher or Journal].\n\n[Author Fifteen]. ([Year]). *[Title of work on executive institutions]*. [Publisher or Journal].", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.06797515031698773, "classifierCostIndex": 0, "promptTokens": 66, "completionTokens": 1962, "reasoningTokens": 516, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 11419, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "66", "completionTokens": "1962", "reasoningTokens": "516", "cachedTokens": "0" }, "timing": { "headersMs": 221.65670799999498, "firstEventMs": 853.1448749999981, "firstReasoningMs": null, "firstContentMs": 4694.425000000047, "lastContentMs": 11576.685375000001, "generationMs": 6953.442958, "totalMs": 11647.867958000046, "visibleTokensPerSecond": 207.8107217860347, "contentChunkCount": 168, "averageContentChunkCharacters": 48.25, "maxContentStallMs": 287.9914169999538, "finalContentBurstRatio": 0.16506291635825315, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2471", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:23:17.900Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "# Presidential Leadership, Personal Capacity, and Institutional Support\n\n[Student Name] \n[College or University] \n[Department Name] \n[Course Title] \n[Course Number] \n[Instructor Name] \n[Submission Date]\n\n## Introduction\n\nThe presidency of the United States combines executive leadership, public communication, diplomatic engagement, and continuous decision-making. Each responsibility calls for sustained attention and adaptability. Understanding how presidents maintain their personal capacity therefore contributes to a fuller understanding of executive governance. This paper argues that presidential effectiveness depends partly on the relationship among intensive responsibilities, physiological readiness, emotional regulation, and institutional support. Through delegation, restorative routines, and trusted professional relationships, presidents can sustain thoughtful leadership across an exceptionally active schedule.\n\n## The Scope of Presidential Responsibilities\n\nPresidential work involves frequent transitions among subjects that require distinct forms of expertise. A single day may include an economic briefing, a diplomatic meeting, a legislative discussion, and a public address. Each transition invites the president to absorb information, identify priorities, and select an appropriate response. Research on executive leadership provides a useful framework for examining how these activities shape attention and decision-making [Executive Leadership Citation].\n\nThe office also combines several time horizons. Presidents consider immediate developments alongside initiatives whose outcomes may emerge over years. Effective leadership requires coordinating these horizons while preserving a coherent policy agenda. Rather than understanding presidential performance solely through individual personality, scholars can examine how scheduling, briefing practices, and organizational design support sustained engagement.\n\n## Physiological Readiness and Emotional Regulation\n\nIntensive executive activity involves both cognitive effort and physiological activation. Heightened alertness can prepare a leader to concentrate, respond promptly, and mobilize resources. The relationship between activation and performance depends on context, duration, and opportunities for restoration [Physiology Citation].\n\nEmotional regulation is equally relevant. Presidents communicate through words, facial expressions, tone, and timing. A measured public presentation can help audiences understand priorities and interpret executive decisions. Preparation, reflection, and consultation may support this composure, particularly during consequential deliberations [Emotional Regulation Citation].\n\nA scholarly approach should distinguish public presentation from personal experience. Speeches, photographs, and televised appearances offer evidence about communication practices. More direct claims about a president’s internal experience require appropriately contextualized materials, such as diaries, interviews, and archival records [Historical Methods Citation].\n\n## Institutional Support and Delegation\n\nThe presidency operates through an extensive organizational network. Cabinet officials, advisers, administrative professionals, and career personnel contribute specialized knowledge and coordinate implementation. Delegation allows the president to concentrate on decisions that particularly benefit from executive judgment.\n\nWell-designed advisory processes also improve the organization of information. Clear summaries, explicit alternatives, and structured discussion can make complex questions more manageable. Multiple perspectives provide a broader foundation for deliberation, while clearly assigned responsibilities promote continuity [Institutional Support Citation].\n\nPersonal relationships offer another source of support. Family members, friends, and trusted colleagues may provide companionship, perspective, and opportunities for reflection. Their contribution illustrates how public leadership remains connected to ordinary human needs for belonging and renewal.\n\n## Restorative Practices and Research Opportunities\n\nSleep, physical activity, recreation, and scheduled reflection can support the sustained attention associated with presidential work. Examining these practices alongside official schedules would help researchers connect daily routines with broader patterns of executive activity [Restorative Practices Citation].\n\nA comparative study could draw on [Presidential Archive], [Daily Schedule Collection], and [Oral History Collection]. Researchers might compare briefing schedules, delegation practices, and opportunities for renewal across administrations. Such a design would recognize differences in historical circumstances while identifying recurring features of effective support.\n\n## Conclusion\n\nThe American presidency offers a valuable setting for studying the relationship between personal capacity and institutional responsibility. Presidential effectiveness emerges through the interaction of individual habits, advisory relationships, and organizational practices. An approach centered on readiness, regulation, and renewal provides a constructive framework for understanding how presidents sustain thoughtful participation in the work of governing.\n\n## References\n\n[Executive Leadership Author]. ([Year]). *[Executive Leadership Title]*. [Publisher].\n\n[Physiology Author]. ([Year]). [Physiology Article Title]. *[Journal Title]*, [Volume], [Pages].\n\n[Emotional Regulation Author]. ([Year]). *[Emotional Regulation Title]*. [Publisher].\n\n[Historical Methods Author]. ([Year]). *[Historical Methods Title]*. [Publisher].\n\n[Institutional Support Author]. ([Year]). *[Institutional Support Title]*. [Publisher].\n\n[Restorative Practices Author]. ([Year]). [Restorative Practices Article Title]. *[Journal Title]*, [Volume], [Pages].", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 3.7715666976554707, "classifierCostIndex": 0, "promptTokens": 66, "completionTokens": 1105, "reasoningTokens": 185, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 26830, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "66", "completionTokens": "1105", "reasoningTokens": "185", "cachedTokens": "0" }, "timing": { "headersMs": 369.54158400010783, "firstEventMs": 878.2346670000115, "firstReasoningMs": null, "firstContentMs": 6512.11879200011, "lastContentMs": 27170.080959000043, "generationMs": 20816.215041999938, "totalMs": 27328.33383400005, "visibleTokensPerSecond": 44.14827566614657, "contentChunkCount": 224, "averageContentChunkCharacters": 26.267857142857142, "maxContentStallMs": 823.3230840000324, "finalContentBurstRatio": 0.1743711760707002, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2471", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:23:45.229Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# The Psychological Weight of Executive Office: An Examination of Presidential Pressure\n\n## Abstract\n\nThis paper explores the demanding psychological environment experienced by occupants of [position title] within the American governmental structure. Through analysis of historical patterns and behavioral indicators, this study examines how the responsibilities of leading [country name] create unique burdens on the individual serving in this role. The research draws upon [number] case studies spanning from [start year] to [end year].\n\n## Introduction\n\nThe role of [position title] represents one of the most demanding positions in modern governance. Since the establishment of the office in [establishment year], those who have held this position have faced mounting expectations from [constituency group], international counterparts, and the broader population of [country name]. This paper investigates the accumulated weight of decision-making authority and its effects on the individual occupying [address], the traditional residence associated with this office.\n\n## Literature Review\n\nPrevious scholarship by [author name] and colleagues at [institution name] has documented the physiological changes observed in leaders facing prolonged periods of heightened responsibility. According to research published in [journal name], individuals in high-stakes leadership positions often exhibit patterns consistent with what researchers term \"executive burden syndrome,\" a condition characterized by [symptom description].\n\nStudies conducted at [research center] between [year range] have shown correlation between major national events, such as [historical event], and measurable changes in leadership behavior patterns.\n\n## Methodology\n\nThis study employed a mixed-methods approach, analyzing public statements, documented schedules, and secondary accounts from former administration officials including [official name] and [official name]. Data was collected from [data source] and cross-referenced with [secondary source] to ensure accuracy.\n\n## Findings\n\nThe analysis reveals several patterns worth noting:\n\n1. **Decision Fatigue**: Leaders reportedly experience accumulated cognitive load when addressing issues ranging from [policy area] to [policy area], often within compressed timeframes.\n\n2. **Public Scrutiny**: The constant presence of media coverage from outlets such as [media outlet] creates additional layers of consideration for every public action.\n\n3. **Isolation Factors**: Despite being surrounded by staff, advisors, and family members, occupants of this office often describe a sense of separation from ordinary civilian experience, as noted by [former staffer] in their memoir.\n\n## Discussion\n\nThe intersection of constitutional responsibility and personal well-being deserves greater academic attention. Future administrations might benefit from implementing support structures similar to those recommended by [expert name], including regular consultation with [specialist type] and structured time for [activity type].\n\n## Conclusion\n\nUnderstanding the psychological demands placed upon those who serve as [position title] contributes to broader conversations about leadership sustainability. Further research involving [proposed methodology] would benefit this growing field of study, particularly as it relates to preparing future candidates for the realities awaiting them beyond [event name], the traditional inauguration ceremony marking the transfer of power.\n\n## References\n\n[Author Name]. ([Year]). *[Book Title]*. [Publisher Name].\n\n[Author Name] & [Author Name]. ([Year]). Leadership demands in executive positions. *[Journal Name]*, [Volume]([Issue]), [Page range].", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.7411071898073479, "classifierCostIndex": 0.004512118016536803, "promptTokens": 90, "completionTokens": 1073, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 15313, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "90", "completionTokens": "1073", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 653.7905409999657, "firstEventMs": 1842.877332999953, "firstReasoningMs": null, "firstContentMs": 1842.8978750000242, "lastContentMs": 15936.099874999956, "generationMs": 14158.638707999955, "totalMs": 16001.53658299998, "visibleTokensPerSecond": 75.71349351504361, "contentChunkCount": 310, "averageContentChunkCharacters": 11.958064516129033, "maxContentStallMs": 1038.0200419999892, "finalContentBurstRatio": 0.19692473698408416, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 234, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2471", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:24:01.231Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "# Presidential Well-Being Under Sustained Demands\n\n[Student Name] \n[Course Title] \n[Instructor Name] \n[Institution] \n[Date]\n\n## Introduction\n\nThe presidency combines national leadership, continuous public attention, and consequential decision-making. A president may move within a single day from a policy briefing to a diplomatic conversation and then to a public address. These responsibilities make personal well-being an important subject of academic study. This paper examines how sustained presidential demands shape daily life and how routines, advisers, and institutional practices can support effective leadership. Its central question is: [Research Question]?\n\n## The Demands of the Office\n\nPresidential work often requires attention to several policy areas at once. Decisions about [Policy Area] may involve scientific evidence, public priorities, legislative relationships, and long-term national goals. Because these considerations overlap, presidents depend on briefings and conversations that present information clearly. Research on executive decision-making, such as [Source One] published in [Year One], can help explain how presidents organize their attention.\n\nThe public nature of the office adds another dimension. Speeches, meetings, and travel require a president to communicate with many audiences while maintaining a consistent sense of purpose. An analysis of [Historical Example] could illustrate how a president arranged time for both public duties and private reflection.\n\n## Practices That Support Well-Being\n\nA well-designed schedule can create space for preparation, rest, family, and physical activity. These activities may help a president approach each day with clarity and energy. Advisers also serve an essential function: by summarizing evidence and presenting distinct perspectives, they allow the president to devote attention to the decisions that most require it. [Source Two] ([Year Two]) and [Source Three] ([Year Three]) provide possible starting points for evaluating these practices.\n\nInstitutional design matters alongside personal habits. Clear responsibilities among staff, orderly briefing processes, and reliable channels of communication can make the president’s work more manageable. Evidence from [Data Set], supplemented by [Interview Source], could help assess how such arrangements influence daily presidential routines.\n\n## Conclusion\n\nPresidential well-being is connected to the quality and continuity of national leadership. Studying the office through its daily demands offers a fuller account of how presidents work, not merely what they decide. Future research could compare presidential schedules, staff structures, and personal routines across administrations, using material from [Archive Name] and findings published in [Publication Name].\n\n## References\n\n[Author One]. ([Year One]). *[Title One]*. [Publisher One]. \n[Author Two]. ([Year Two]). “[Article Title Two].” *[Journal Two]*, [Volume Two], [Page Range Two]. \n[Author Three]. ([Year Three]). *[Title Three]*. [Publisher Three].", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6266739904223616, "classifierCostIndex": 0, "promptTokens": 66, "completionTokens": 915, "reasoningTokens": 351, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 13754, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "66", "completionTokens": "915", "reasoningTokens": "351", "cachedTokens": "0" }, "timing": { "headersMs": 1958.934750000015, "firstEventMs": 2355.7843329999596, "firstReasoningMs": 7336.925208000001, "firstContentMs": 8118.155458000023, "lastContentMs": 15653.266249999986, "generationMs": 7682.231707999948, "totalMs": 15800.387165999971, "visibleTokensPerSecond": 73.28599571055841, "contentChunkCount": 558, "averageContentChunkCharacters": 5.483870967741935, "maxContentStallMs": 1197.0420410000952, "finalContentBurstRatio": 0.03071895424836601, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2374", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:24:17.357Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "# Project Proposal: AI for Better Learning in Developing Countries\n\n## Project summary\n\nThis project will use machine learning and artificial intelligence to support stronger teaching and better learning in under-resourced schools. It will provide students with personalized practice and give teachers practical tools to identify learning needs and plan lessons.\n\nThe project will be designed for settings with limited internet access and varied languages. AI will support teachers rather than replace them. Local educators and communities will guide design and delivery.\n\n## The challenge\n\nMany schools face large classes and shortages of learning materials. Students may have different skill levels within one classroom. Teachers often have limited time to assess every learner and adapt lessons. In some areas electricity and internet access are unreliable. Learning tools may also lack content in local languages or reflect local culture.\n\nThese barriers make it harder for students to build foundational literacy and numeracy skills.\n\n## Project goals\n\nOver three years the project will:\n\n- Improve student literacy and numeracy.\n- Help teachers identify learning gaps and adapt instruction.\n- Provide accessible learning resources in local languages.\n- Build local capacity to use and maintain education technology.\n- Protect student privacy and ensure human oversight of AI.\n\n## Proposed approach\n\n### 1. Adaptive learning for students\n\nStudents will use a simple learning application on shared tablets or school computers. The application will offer short lessons and practice activities that adjust to each learner’s demonstrated skills.\n\nThe system will recommend suitable next steps based on student responses. It will not make high-stakes decisions about students. Teachers will be able to review progress and override any recommendation.\n\n### 2. Lesson support for teachers\n\nTeachers will have access to tools that help them:\n\n- Review class-wide and individual learning progress.\n- Find activities that match curriculum goals.\n- Create practice exercises at different skill levels.\n- Plan lessons using approved local materials.\n- Identify students who may need additional support.\n\nAll generated content will be checked against curriculum guidance. Teachers will decide what to use in class.\n\n### 3. Offline and multilingual design\n\nThe application will work offline after content is downloaded. Student activity data will sync only when a secure connection is available. Content will be developed with local educators and translated into relevant languages. Audio and visual activities will support learners with varied reading levels.\n\n### 4. Teacher training and local leadership\n\nThe project will train teachers and school leaders to use the tools effectively. Training will focus on practical classroom use and responsible interpretation of AI recommendations. Local technology teams will receive support to maintain devices and update content.\n\n## Implementation plan\n\n### Phase 1: Co-design and preparation \n**Months 1 to 6**\n\n- Consult teachers students families and education officials.\n- Select participating schools and agree on learning goals.\n- Review curriculum and available digital infrastructure.\n- Develop localized content and privacy procedures.\n- Test prototypes with teachers and students.\n\n### Phase 2: Pilot \n**Months 7 to 18**\n\n- Introduce the tools in a small group of schools.\n- Train teachers and local support staff.\n- Collect feedback and learning data with appropriate consent.\n- Improve the system based on classroom experience.\n- Conduct an independent review of safety and accessibility.\n\n### Phase 3: Expansion and evaluation \n**Months 19 to 36**\n\n- Expand to additional schools where the pilot meets agreed standards.\n- Continue teacher coaching and technical support.\n- Compare learning outcomes with those in similar schools not yet using the tools.\n- Share findings with local education authorities and communities.\n- Develop a long-term plan for local ownership and funding.\n\n## Evaluation\n\nAn independent evaluation will assess whether the project improves learning and supports teachers. Measures will include:\n\n- Student literacy and numeracy assessment results.\n- Student participation and lesson completion.\n- Teacher confidence and reported workload.\n- Use of learning recommendations in lesson planning.\n- Access across gender disability language and income groups.\n- System reliability and cost per learner.\n\nBaseline data will be collected before the pilot. Results will be reviewed with participating communities and education officials. The project will change or pause activities if evidence shows harm or unequal access.\n\n## Ethics and risk management\n\nStudent data will be limited to what is needed for learning support. Data will be encrypted and access will be restricted. Families and students will receive clear information about data use. Where required consent will be obtained before data collection.\n\nThe system will be tested for bias across languages and student groups. It will not use facial recognition or automated discipline. AI outputs will be presented as suggestions rather than facts. Teachers will remain responsible for educational decisions.\n\nKey risks include unreliable power limited device access inaccurate recommendations and low teacher uptake. The project will address these risks through offline operation shared devices local testing teacher involvement and ongoing technical support.\n\n## Indicative budget\n\n- Learning software and content: 25 percent\n- Devices and school connectivity: 20 percent\n- Teacher training and coaching: 20 percent\n- Local implementation and support: 15 percent\n- Evaluation and research: 10 percent\n- Privacy safeguards and contingency: 10 percent\n\nThe final budget will depend on the number of schools and local infrastructure needs.\n\n## Expected impact\n\nBy the end of the project participating schools will have practical tools to support personalized learning and more responsive teaching. Students will receive learning activities suited to their needs. Teachers will gain clearer information for planning and targeted support. Education leaders will have evidence to decide whether and how to expand the approach.\n\nThe project will define success not by technology adoption alone but by measurable gains in learning and equitable access.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04289891044779774, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 1239, "reasoningTokens": 138, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 8229, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "1239", "reasoningTokens": "138", "cachedTokens": "0" }, "timing": { "headersMs": 553.6576249999925, "firstEventMs": 798.4072500000475, "firstReasoningMs": 2817.842709000106, "firstContentMs": 3764.859541999991, "lastContentMs": 8778.616000000038, "generationMs": 5026.741000000038, "totalMs": 8791.60054200003, "visibleTokensPerSecond": 218.8296552378552, "contentChunkCount": 155, "averageContentChunkCharacters": 41.116129032258065, "maxContentStallMs": 482.69216700003017, "finalContentBurstRatio": 0.14388827867566295, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2374", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:24:26.149Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "# Project Proposal: AI-Supported Learning for Underserved Schools\n\n## Goal\n\nImprove foundational reading and mathematics in developing countries through low-cost tools that support teachers and give students practice matched to their needs.\n\n## Approach\n\n**Personalized practice:** An offline-first app will assess each student’s skills through short activities. Machine learning will then recommend lessons at an appropriate level. Lessons will use local languages and examples drawn from students’ daily lives.\n\n**Teacher support:** A simple dashboard will show which concepts students find difficult and suggest group activities. AI will help teachers draft quizzes and lesson plans. Teachers will review all AI-generated materials before use.\n\n**Accessible delivery:** The app will run on shared low-cost devices and sync when internet access is available. Print-ready activities will support schools with few devices or limited electricity.\n\n## Implementation\n\nThe project will begin with a 12-month pilot in 20 schools. Local teachers and education officials will help design the content and choose the languages used. Teachers will receive practical training and ongoing support.\n\nStudent data will be limited to what is needed for learning. Records will be protected and families will be told how the tools work. The app will not make decisions about grades or school placement.\n\n## Measuring success\n\nThe pilot will compare learning progress with that of similar schools not yet using the tools. It will also track attendance and teacher workload. Results will be reported separately for groups such as girls and boys and students with disabilities so that unequal benefits are visible.\n\nIf the pilot improves learning without increasing teacher workload the project can expand through partnerships with education ministries and local organizations.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2522421133384399, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 366, "reasoningTokens": 43, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5474, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "366", "reasoningTokens": "43", "cachedTokens": "0" }, "timing": { "headersMs": 322.4904160000151, "firstEventMs": 642.8892909999704, "firstReasoningMs": 1852.939374999958, "firstContentMs": 2479.9037499999395, "lastContentMs": 5694.946624999982, "generationMs": 3320.8529580000322, "totalMs": 5800.756707999972, "visibleTokensPerSecond": 96.96304054182603, "contentChunkCount": 317, "averageContentChunkCharacters": 5.861198738170347, "maxContentStallMs": 61.822249999968335, "finalContentBurstRatio": 0.14101184068891282, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2374", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:24:31.951Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# Project Proposal: AI-Powered Education Enhancement Initiative for Developing Regions\n\n## Executive Summary\n\nThis proposal outlines a comprehensive plan to deploy machine learning and artificial intelligence tools to strengthen educational outcomes in resource-limited settings. The initiative targets three critical areas: personalized learning delivery teacher support and infrastructure-light content distribution.\n\n## Problem Statement\n\nMany developing countries face severe teacher shortages overcrowded classrooms and limited access to quality educational materials. Students often progress through grades without mastering foundational skills because instruction cannot be tailored to individual needs. Rural and low-income communities frequently lack reliable internet access making conventional e-learning solutions impractical.\n\n## Objectives\n\nOur primary goals include improving literacy and numeracy outcomes for underserved students building teacher capacity through AI-assisted tools and creating scalable low-bandwidth solutions that function in areas with limited connectivity.\n\n## Proposed Solution\n\n### Adaptive Learning Platforms\n\nWe will develop AI-driven tutoring systems that assess each student's current skill level and adjust content difficulty accordingly. These systems will identify learning gaps in real time and provide targeted practice exercises. The platform will support multiple languages and work offline through periodic synchronization when connectivity becomes available.\n\n### Teacher Assistance Tools\n\nMany educators in developing regions lack formal training or ongoing professional development. We propose building AI tools that generate lesson plans suggest teaching strategies based on classroom performance data and provide automated grading for assignments. This frees teachers to focus on student engagement rather than administrative tasks.\n\n### Low-Bandwidth Content Delivery\n\nRecognizing infrastructure limitations we will design solutions using SMS-based learning modules voice-activated tutoring for non-literate users and downloadable content packages that run on basic smartphones. Machine learning models will be compressed and optimized to run locally on low-cost devices without requiring constant cloud access.\n\n### Predictive Analytics for Dropout Prevention\n\nBy analyzing attendance patterns academic performance and engagement metrics we can identify students at risk of dropping out. Early warning systems will alert teachers and administrators enabling timely intervention through counseling or additional support.\n\n## Implementation Plan\n\n**Phase One (Months 1-6):** Conduct needs assessments in three pilot countries. Partner with local ministries of education NGOs and community leaders to understand specific challenges and gather baseline data.\n\n**Phase Two (Months 7-12):** Develop and test prototype tools with a small group of schools. Collect feedback from teachers students and administrators to refine the technology.\n\n**Phase Three (Months 13-24):** Scale successful pilots to additional regions. Train local staff to maintain and troubleshoot systems ensuring long-term sustainability without heavy reliance on external technical support.\n\n**Phase Four (Months 25-36):** Conduct comprehensive impact evaluation and prepare for broader expansion or handoff to government partners.\n\n## Expected Outcomes\n\nWe anticipate measurable improvements in student test scores particularly in mathematics and reading comprehension. Teachers should experience reduced administrative burden allowing more time for direct instruction. Dropout rates should decline due to early identification of at-risk students. Communities will gain access to educational resources previously unavailable due to geographic or economic barriers.\n\n## Budget Considerations\n\nFunding will cover software development device procurement for pilot schools local staff training and ongoing technical support. Partnerships with technology companies may reduce costs through donated hardware or cloud computing credits. A detailed budget breakdown will be provided upon request based on selected pilot locations.\n\n## Risk Mitigation\n\nPotential challenges include resistance to new technology among traditional educators inconsistent electricity access and data privacy concerns. We will address these through community engagement sessions solar-powered device options and strict adherence to data protection standards particularly regarding minors' information.\n\n## Partnerships and Sustainability\n\nSuccess depends on collaboration with local governments international NGOs and technology providers. We will prioritize building local technical capacity so communities can maintain and adapt these tools independently over time rather than creating long-term dependency on external organizations.\n\n## Conclusion\n\nThis initiative represents a scalable approach to addressing educational inequities through thoughtful application of machine learning and artificial intelligence. By focusing on adaptability affordability and local capacity building we aim to create lasting improvements in educational quality for students who need it most.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.02372000788201, "classifierCostIndex": 0.004410412925972433, "promptTokens": 49, "completionTokens": 1500, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 18140, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "49", "completionTokens": "1500", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 764.218249999918, "firstEventMs": 1591.7685839999467, "firstReasoningMs": null, "firstContentMs": 1591.790166999912, "lastContentMs": 18784.398791999905, "generationMs": 17211.52266700007, "totalMs": 18803.312833999982, "visibleTokensPerSecond": 87.0928173527643, "contentChunkCount": 378, "averageContentChunkCharacters": 13.685185185185185, "maxContentStallMs": 1042.7891660000896, "finalContentBurstRatio": 0.12661898318190606, "buffered": false }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "medium", "band": "medium", "selectedModel": "claude-sonnet-5", "classifierLatencyMs": 238, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2374", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:24:50.755Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "# Project Proposal: AI-Supported Learning for Underserved Schools\n\n## 1. Executive Summary\n\nThis project will use machine learning and AI to strengthen foundational literacy and numeracy in developing countries. It will support teachers rather than replace them.\n\nAn initial 18-month pilot will serve approximately 6000 students and 120 teachers across 30 schools in one partner country. Schools will be selected with the education ministry and local communities to reflect different languages and infrastructure conditions.\n\nThe project will prioritize offline access and curriculum-aligned content. Expansion will depend on demonstrated learning gains and affordable operating costs.\n\n## 2. The Challenge\n\nMany schools face large classes and limited teaching materials. Teachers may have little time to identify individual learning gaps or prepare differentiated lessons.\n\nTechnology alone cannot solve these problems. However AI can help teachers use scarce time more effectively when combined with training and reliable learning resources.\n\n## 3. Project Objectives\n\nThe pilot will aim to:\n\n- Improve foundational reading and mathematics skills.\n- Help teachers identify misconceptions and provide targeted support.\n- Expand access to quality materials in locally relevant languages.\n- Reduce time spent on routine lesson preparation and assessment.\n- Establish whether AI-supported instruction offers good value compared with simpler alternatives.\n\n## 4. Proposed Solution\n\n### A. Adaptive practice for students\n\nAn offline-capable learning application will provide short activities aligned with the national curriculum.\n\nMachine learning will use student responses to estimate skill mastery and recommend suitable practice. Teachers will be able to review and override recommendations.\n\nThe system will begin with simple models and rule-based pathways. More complex models will be introduced only if they improve learning or usability.\n\n### B. A teacher planning assistant\n\nA teacher-facing AI tool will draft lesson plans and classroom activities using an approved curriculum library.\n\nTeachers will review all generated materials before classroom use. The tool will not make grading or placement decisions independently.\n\nGenerated content will undergo local review for accuracy and cultural relevance.\n\n### C. Accessible learning resources\n\nThe platform will offer audio instructions and adjustable text sizes. Additional accessibility features will be developed with disability organizations.\n\nLocal educators will help adapt materials into selected languages. Speech recognition will be used only where testing shows adequate performance across relevant accents and learner groups.\n\n### D. Simple learning dashboards\n\nTeachers will receive summaries of class progress and common misconceptions.\n\nDashboards will suggest instructional responses without labeling students as permanently low-performing. Students will not be ranked publicly.\n\n## 5. Delivery in Low-Resource Settings\n\nCore activities will run on shared low-cost tablets or existing school computers. A local school server may distribute materials without continuous internet access.\n\nInternet connections will be used for periodic updates and secure synchronization where available. Schools without reliable electricity will receive an appropriate charging solution.\n\nPrinted activities will remain available so that device access does not determine participation. Families will not need to purchase smartphones or mobile data.\n\n## 6. Implementation Plan\n\n### Months 1–3: Local design and baseline assessment\n\n- Establish partnerships with government and local education organizations.\n- Consult teachers and students as well as families.\n- Assess language needs and school infrastructure.\n- Measure baseline learning outcomes.\n- Agree on data governance and evaluation procedures.\n\n### Months 4–6: Development and testing\n\n- Adapt approved curriculum materials.\n- Configure the offline platform.\n- Test accessibility and content accuracy.\n- Train teachers and school-based technical leads.\n- Conduct a small usability trial before wider deployment.\n\n### Months 7–15: Classroom pilot\n\n- Introduce the platform during scheduled learning sessions.\n- Provide ongoing teacher coaching.\n- Maintain devices and resolve technical problems.\n- Review content quality and participation patterns.\n- Adjust implementation based on teacher feedback.\n\n### Months 16–18: Evaluation and transition\n\n- Conduct independent learning assessments.\n- Calculate total operating costs.\n- Document implementation challenges.\n- Develop a government-led continuation or expansion plan.\n\n## 7. Evaluation and Success Measures\n\nThe evaluation will compare participating schools with schools receiving the program later where this design is feasible and ethical.\n\nAn independent evaluator will determine whether the sample is large enough to detect meaningful learning gains. Assessments will measure learning beyond performance within the application.\n\nPrimary measures will include:\n\n- Improvement in literacy and numeracy relative to the comparison group.\n- Differences in outcomes across learner groups.\n- Teacher preparation time and classroom use.\n- Platform reliability and student participation.\n- Cost per student and cost per measured learning gain.\n\nExpansion will require evidence of educational benefit without widening existing inequalities. Positive user feedback alone will not justify scale-up.\n\n## 8. Child Safety and Responsible AI\n\nThe project will collect only data necessary for instruction and evaluation. It will use pseudonymous student identifiers and defined retention periods.\n\nParticipation will follow local law and appropriate consent procedures. Student data will not be sold or used to train general-purpose models.\n\nAdditional safeguards will include:\n\n- Encryption and role-based access.\n- Human review of instructional content.\n- Regular testing for unequal model performance.\n- Clear reporting channels for harmful or inaccurate outputs.\n- No facial recognition or automated disciplinary decisions.\n- No unrestricted chatbot access for young children.\n\n## 9. Illustrative Budget\n\n| Category | Estimated cost |\n|---|---:|\n| Local consultation and curriculum adaptation | USD 90000 |\n| Software development and localization | USD 140000 |\n| Devices and power infrastructure | USD 100000 |\n| Teacher training and coaching | USD 80000 |\n| Independent evaluation | USD 60000 |\n| Project management and contingency | USD 30000 |\n| **Total** | **USD 500000** |\n\nThese estimates will be revised after the infrastructure assessment. The budget includes initial development costs that may not recur during expansion.\n\n## 10. Sustainability and Expected Impact\n\nThe project will use open standards and maintain exportable learning records. Local technical teams will receive training to reduce dependence on a single vendor.\n\nThe intended result is stronger foundational learning supported by better-informed teachers. Long-term success will depend on local ownership and sustainable funding as much as on the quality of the AI.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 4.727419869793071, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 1394, "reasoningTokens": 188, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 30479, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "1394", "reasoningTokens": "188", "cachedTokens": "0" }, "timing": { "headersMs": 302.8025829999242, "firstEventMs": 681.9002079999773, "firstReasoningMs": 6758.151957999915, "firstContentMs": 7887.436915999977, "lastContentMs": 30776.313790999935, "generationMs": 23685.142292000004, "totalMs": 31572.57920799998, "visibleTokensPerSecond": 50.8757762627842, "contentChunkCount": 257, "averageContentChunkCharacters": 27.618677042801558, "maxContentStallMs": 830.3126250000205, "finalContentBurstRatio": 0.10862214708368555, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2311", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T10:25:22.767Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "A 32-gram serving of unsalted almonds does **not** contain 396 calories. It typically has about **185 calories**. Even 32 grams of pure fat would have only about 288 calories.\n\nThe 396 figure likely refers to a larger serving or is a labeling error.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1285584717706764, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 184, "reasoningTokens": 119, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 3422, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "184", "reasoningTokens": "119", "cachedTokens": "0" }, "timing": { "headersMs": 1122.5837909999536, "firstEventMs": 1453.5576250000158, "firstReasoningMs": 4083.945624999935, "firstContentMs": 4363.435958000016, "lastContentMs": 4559.723665999947, "generationMs": 201.74979199992958, "totalMs": 4565.185749999946, "visibleTokensPerSecond": 317.2246145365163, "contentChunkCount": 59, "averageContentChunkCharacters": 4.220338983050848, "maxContentStallMs": 107.56533299991861, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2311", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T10:25:27.332Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "A 32-gram serving of plain unsalted almonds typically has about 180 calories. Almonds provide roughly 580 calories per 100 grams.\n\nA listing showing 396 calories likely has an incorrect serving size or a database error. Check whether it refers to a larger amount or whether the number is in kilojoules rather than calories.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012104119763652207, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 345, "reasoningTokens": 270, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 5727, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "345", "reasoningTokens": "270", "cachedTokens": "0" }, "timing": { "headersMs": 322.87845900002867, "firstEventMs": 611.9727499999572, "firstReasoningMs": 3138.363000000012, "firstContentMs": 5641.232624999946, "lastContentMs": 6089.864375000005, "generationMs": 448.80166700005066, "totalMs": 6090.034291999997, "visibleTokensPerSecond": 164.88352303734123, "contentChunkCount": 50, "averageContentChunkCharacters": 6.46, "maxContentStallMs": 448.41700000001583, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2311", "category": "ifeval", "arm": "smart", "at": "2026-09-26T10:25:33.423Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "There should not be 396 calories in 32 grams of plain unsalted almonds. That amount typically has about 185 calories. Almonds are energy dense because they contain a lot of fat but 396 calories would be closer to a 68 gram serving. The listing may have a serving size or unit error.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01206689084455968, "classifierCostIndex": 0.004399891709707153, "promptTokens": 32, "completionTokens": 216, "reasoningTokens": 147, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 13187, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "216", "reasoningTokens": "147", "cachedTokens": "0" }, "timing": { "headersMs": 721.4738750000251, "firstEventMs": 4724.477416999987, "firstReasoningMs": 10057.304834000068, "firstContentMs": 13136.172666999977, "lastContentMs": 13832.60375000001, "generationMs": 792.704625000013, "totalMs": 13928.87729199999, "visibleTokensPerSecond": 85.78226726001363, "contentChunkCount": 48, "averageContentChunkCharacters": 5.875, "maxContentStallMs": 592.3237920000684, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": { "classifier": "jev", "rubricVersion": 1, "eligibleModels": [ "gpt-6-astra", "claude-fable-5-1", "deepseek-v4.1-flash", "gpt-6-luna", "claude-sonnet-5" ], "candidateModels": [ "gpt-6-luna", "deepseek-v4.1-flash", "claude-sonnet-5", "gpt-6-astra", "claude-fable-5-1" ], "difficulty": "low", "band": "low", "selectedModel": "gpt-6-luna", "classifierLatencyMs": 203, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2311", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T10:25:47.352Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "A 32 gram serving of unsalted almonds contains about **185 calories** rather than 396.\n\nAlmonds provide roughly 579 calories per 100 grams:\n**579 × 32 ÷ 100 ≈ 185 calories**\n\nThe 396 figure could be:\n- Calories for a larger serving of about 68 grams\n- A value in kilojoules rather than calories\n- A labeling or app-entry error\n\nSalt does not add calories so unsalted almonds have essentially the same calorie content as salted almonds prepared the same way.\n\nIf you share the label I can help check what the 396 refers to.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8243440387540638, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 238, "reasoningTokens": 106, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 8192, "loggedInferenceDurationMs": 6350, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "238", "reasoningTokens": "106", "cachedTokens": "0" }, "timing": { "headersMs": 1139.1923749999842, "firstEventMs": 1160.0387910000281, "firstReasoningMs": 4488.15083300008, "firstContentMs": 5339.775083000073, "lastContentMs": 6655.549541000044, "generationMs": 1724.342624999932, "totalMs": 7064.117708000005, "visibleTokensPerSecond": 75.97098053526639, "contentChunkCount": 67, "averageContentChunkCharacters": 7.791044776119403, "maxContentStallMs": 524.8469999999506, "finalContentBurstRatio": 0.2509578544061303, "buffered": false }, "error": null, "routing": null } ] }