{ "version": 1, "referenceCostIndex": { "arm": "gpt-6-astra", "total": 100 }, "maximumOutputTokens": 4096, "measuredRequests": 320, "promptCount": 80, "firstRequest": "2026-09-26T08:35:48.304Z", "lastRequest": "2026-09-26T09:20:21.399Z", "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": 71, "accuracy": 0.8875, "costIndex": 37.44607768147276, "costPerPassIndex": 38.50089677109171, "classifierCostShare": 0.009553666209156505, "sensitivityPassed": 71, "sensitivityN": 79, "errors": 1, "truncated": 0, "medianSeconds": 5.659112854000006, "p95Seconds": 21.04268459229999, "medianFirstContentSeconds": 3.346613750000004, "groups": [ { "group": "easy", "n": 25, "passed": 25, "costIndex": 0.12509609924850618 }, { "group": "reasoning", "n": 15, "passed": 9, "costIndex": 27.258909057142116 }, { "group": "ifeval", "n": 40, "passed": 37, "costIndex": 10.062072525082128 } ] }, { "arm": "gpt-6-luna", "n": 80, "passed": 75, "accuracy": 0.9375, "costIndex": 1.5352340281520267, "costPerPassIndex": 1.4942944540679728, "classifierCostShare": 0, "sensitivityPassed": 75, "sensitivityN": 79, "errors": 1, "truncated": 0, "medianSeconds": 5.116688687499962, "p95Seconds": 17.345821504500005, "medianFirstContentSeconds": 4.443939249999996, "groups": [ { "group": "easy", "n": 25, "passed": 25, "costIndex": 0.023555713591744142 }, { "group": "reasoning", "n": 15, "passed": 13, "costIndex": 0.6383027483343384 }, { "group": "ifeval", "n": 40, "passed": 37, "costIndex": 0.8733755662259446 } ] }, { "arm": "gpt-6-sol", "n": 80, "passed": 74, "accuracy": 0.925, "costIndex": 19.208586601447333, "costPerPassIndex": 18.94901110683318, "classifierCostShare": 0, "sensitivityPassed": 74, "sensitivityN": 79, "errors": 0, "truncated": 1, "medianSeconds": 4.331622166500049, "p95Seconds": 12.76078440559998, "medianFirstContentSeconds": 3.567533792000001, "groups": [ { "group": "easy", "n": 25, "passed": 25, "costIndex": 0.2779836655493441 }, { "group": "reasoning", "n": 15, "passed": 13, "costIndex": 8.08222954369179 }, { "group": "ifeval", "n": 40, "passed": 36, "costIndex": 10.8483733922062 } ] }, { "arm": "gpt-6-astra", "n": 80, "passed": 73, "accuracy": 0.9125, "costIndex": 100, "costPerPassIndex": 100, "classifierCostShare": 0, "sensitivityPassed": 78, "sensitivityN": 79, "errors": 0, "truncated": 0, "medianSeconds": 7.103227708499995, "p95Seconds": 27.34748304729987, "medianFirstContentSeconds": 4.046862291999976, "groups": [ { "group": "easy", "n": 25, "passed": 20, "costIndex": 1.1606688253361426 }, { "group": "reasoning", "n": 15, "passed": 14, "costIndex": 29.706384090818457 }, { "group": "ifeval", "n": 40, "passed": 39, "costIndex": 69.13294708384541 } ] } ], "comparisons": [ { "arm": "gpt-6-luna", "savingPercent": -2339.1120177649327, "savingCI95": [-4412.005454131038, -1266.3943176335715], "scoreDifferencePoints": -5.000000000000004, "scoreDifferenceCI95": [-11.25, 1.25] }, { "arm": "gpt-6-sol", "savingPercent": -94.94447175333171, "savingCI95": [-161.80630972665853, -26.42887320989656], "scoreDifferencePoints": -3.750000000000009, "scoreDifferenceCI95": [-10, 2.5] }, { "arm": "gpt-6-astra", "savingPercent": 62.55392231852724, "savingCI95": [45.244892079169446, 76.9893055958595], "scoreDifferencePoints": -2.500000000000002, "scoreDifferenceCI95": [-11.25, 6.25] } ], "trials": [ { "caseId": "javascript_trace", "category": "code", "arm": "gpt-6-astra", "at": "2026-09-26T08:35:48.304Z", "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": 0.3708090324283657, "classifierCostIndex": 0, "promptTokens": 103, "completionTokens": 89, "reasoningTokens": 69, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3278, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "103", "completionTokens": "89", "reasoningTokens": "69", "cachedTokens": "0" }, "timing": { "headersMs": 374.36720900000006, "firstEventMs": 697.4774170000001, "firstReasoningMs": null, "firstContentMs": 3460.861084, "lastContentMs": 3511.7685420000003, "generationMs": 203.29029100000025, "totalMs": 3664.1513750000004, "visibleTokensPerSecond": 93.4624074102977, "contentChunkCount": 14, "averageContentChunkCharacters": 1.2857142857142858, "maxContentStallMs": 14.706250000000182, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "javascript_trace", "category": "code", "arm": "smart", "at": "2026-09-26T08:35:51.969Z", "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": 0.189717787615777, "classifierCostIndex": 0.0046555408444330995, "promptTokens": 146, "completionTokens": 244, "reasoningTokens": 225, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4684, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "146", "completionTokens": "244", "reasoningTokens": "225", "cachedTokens": "0" }, "timing": { "headersMs": 651.6347919999998, "firstEventMs": 1324.185458, "firstReasoningMs": 5390.252667, "firstContentMs": 5390.704832999999, "lastContentMs": 5390.7128330000005, "generationMs": 0.25679200000013225, "totalMs": 5390.961624999999, "visibleTokensPerSecond": 70095.64160873675, "contentChunkCount": 3, "averageContentChunkCharacters": 6, "maxContentStallMs": 0.005417000000306871, "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": 256, "classifierFailed": false, "classifierReused": false } }, { "caseId": "javascript_trace", "category": "code", "arm": "gpt-6-luna", "at": "2026-09-26T08:35:57.361Z", "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": 0.007596893503011673, "classifierCostIndex": 0, "promptTokens": 103, "completionTokens": 198, "reasoningTokens": 178, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3645, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "103", "completionTokens": "198", "reasoningTokens": "178", "cachedTokens": "0" }, "timing": { "headersMs": 364.4237499999999, "firstEventMs": 718.7321659999998, "firstReasoningMs": 2856.075291000001, "firstContentMs": 4000.710583, "lastContentMs": 4002.251875, "generationMs": 17.016999999999825, "totalMs": 4017.727583, "visibleTokensPerSecond": 1116.5305282952456, "contentChunkCount": 14, "averageContentChunkCharacters": 1.2857142857142858, "maxContentStallMs": 1.2676659999997355, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "javascript_trace", "category": "code", "arm": "gpt-6-sol", "at": "2026-09-26T08:36:01.379Z", "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": 0.09525575049190747, "classifierCostIndex": 0, "promptTokens": 103, "completionTokens": 120, "reasoningTokens": 100, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4550, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "103", "completionTokens": "120", "reasoningTokens": "100", "cachedTokens": "0" }, "timing": { "headersMs": 373.26237500000025, "firstEventMs": 1495.5319170000002, "firstReasoningMs": null, "firstContentMs": 3567.3135420000017, "lastContentMs": 4137.708583000001, "generationMs": 1905.4912079999995, "totalMs": 5472.804750000001, "visibleTokensPerSecond": 9.97118219188341, "contentChunkCount": 14, "averageContentChunkCharacters": 1.2857142857142858, "maxContentStallMs": 122.04245900000024, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-10", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:36:07.324Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "126", "evaluation": { "passed": true, "answer": "126", "expected": "126" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028424597879401346, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1116, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1460.364458, "firstEventMs": 1764.8680420000019, "firstReasoningMs": null, "firstContentMs": 2431.4090830000023, "lastContentMs": 2431.4090830000023, "generationMs": 189.58920899999794, "totalMs": 2620.998292, "visibleTokensPerSecond": 21.098247210895025, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-10", "category": "easy", "arm": "smart", "at": "2026-09-26T08:36:09.946Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "126", "evaluation": { "passed": true, "answer": "126", "expected": "126" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004652023450949379, "classifierCostIndex": 0.004353045004833169, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1233, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1120.0117910000008, "firstEventMs": 1297.2547080000004, "firstReasoningMs": null, "firstContentMs": 2249.0807910000003, "lastContentMs": 2249.0807910000003, "generationMs": 8.778666999998677, "totalMs": 2257.859457999999, "visibleTokensPerSecond": 455.65004345199594, "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": 285, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-10", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:36:12.204Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "126", "evaluation": { "passed": true, "answer": "126", "expected": "126" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0007474461152905262, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 18, "reasoningTokens": 11, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2175, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "18", "reasoningTokens": "11", "cachedTokens": "0" }, "timing": { "headersMs": 1065.4672499999979, "firstEventMs": 1185.137749999998, "firstReasoningMs": null, "firstContentMs": 2637.0188339999986, "lastContentMs": 2637.0188339999986, "generationMs": 563.4486250000009, "totalMs": 3200.4674589999995, "visibleTokensPerSecond": 10.648708211862244, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-10", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:36:15.407Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "126", "evaluation": { "passed": true, "answer": "126", "expected": "126" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005696824599979014, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 898, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 6308.923417000002, "firstEventMs": 6768.644041999996, "firstReasoningMs": null, "firstContentMs": 6986.205708999998, "lastContentMs": 6986.205708999998, "generationMs": 205.47016599999915, "totalMs": 7191.675874999997, "visibleTokensPerSecond": 19.467546446621437, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-4", "category": "easy", "arm": "smart", "at": "2026-09-26T08:36:22.826Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0053082879043927, "classifierCostIndex": 0.004426910267991292, "promptTokens": 35, "completionTokens": 18, "reasoningTokens": 10, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1367, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "18", "reasoningTokens": "10", "cachedTokens": "0" }, "timing": { "headersMs": 2601.425958, "firstEventMs": 3016.3199999999997, "firstReasoningMs": null, "firstContentMs": 3898.634791000004, "lastContentMs": 3906.767749999999, "generationMs": 220.84908399999404, "totalMs": 4119.483874999998, "visibleTokensPerSecond": 31.695852539737903, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 8.132958999995026, "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": 331, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-4", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:36:26.946Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.016269297705853156, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1262, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 2307.187708999998, "firstEventMs": 2654.433791999996, "firstReasoningMs": null, "firstContentMs": 3567.7540420000005, "lastContentMs": 3567.758834, "generationMs": 53.45279199999641, "totalMs": 3621.206833999997, "visibleTokensPerSecond": 130.9566766877298, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.004791999999724794, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-4", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:36:30.568Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008468801233879989, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1428, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 1698.291541999999, "firstEventMs": 1698.568459000002, "firstReasoningMs": null, "firstContentMs": 2633.1165420000034, "lastContentMs": 2648.202084000004, "generationMs": 89.88237500000105, "totalMs": 2722.9989170000044, "visibleTokensPerSecond": 77.87956203871914, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 15.085542000000714, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-4", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:36:33.292Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.043995151841277017, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1784, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 194.58212500000081, "firstEventMs": 1329.9836250000008, "firstReasoningMs": null, "firstContentMs": 1756.8964579999956, "lastContentMs": 1758.0486669999955, "generationMs": 223.39558400000533, "totalMs": 1980.292042000001, "visibleTokensPerSecond": 22.38182111961479, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 1.152208999999857, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-15", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:36:35.443Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "176", "evaluation": { "passed": true, "answer": "176", "expected": "176" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028424597879401346, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1046, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 197.5975830000025, "firstEventMs": 1124.1185420000038, "firstReasoningMs": null, "firstContentMs": 1143.2471670000014, "lastContentMs": 1143.2471670000014, "generationMs": 107.89745799999946, "totalMs": 1251.1446250000008, "visibleTokensPerSecond": 37.07223575183782, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-15", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:36:36.694Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "176", "evaluation": { "passed": true, "answer": "176", "expected": "176" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008509386543307529, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 21, "reasoningTokens": 14, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2470, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "21", "reasoningTokens": "14", "cachedTokens": "0" }, "timing": { "headersMs": 262.3664590000044, "firstEventMs": 623.2092499999999, "firstReasoningMs": 1904.7293340000033, "firstContentMs": 2707.209625000003, "lastContentMs": 2707.209625000003, "generationMs": 36.487042000000656, "totalMs": 2743.696667000004, "visibleTokensPerSecond": 164.4419407854408, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-15", "category": "easy", "arm": "smart", "at": "2026-09-26T08:36:39.439Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "176", "evaluation": { "passed": true, "answer": "176", "expected": "176" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005173003539634233, "classifierCostIndex": 0.004356562398316889, "promptTokens": 17, "completionTokens": 20, "reasoningTokens": 13, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1623, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "20", "reasoningTokens": "13", "cachedTokens": "0" }, "timing": { "headersMs": 813.2591669999965, "firstEventMs": 982.531332999999, "firstReasoningMs": null, "firstContentMs": 2142.7258749999964, "lastContentMs": 2142.7258749999964, "generationMs": 98.5267079999976, "totalMs": 2241.252582999994, "visibleTokensPerSecond": 60.89719347976333, "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": 306, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-15", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:36:41.681Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "176", "evaluation": { "passed": true, "answer": "176", "expected": "176" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005696824599979014, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1412, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 518.2493329999998, "firstEventMs": 1015.070332999996, "firstReasoningMs": null, "firstContentMs": 1539.3839999999982, "lastContentMs": 1539.3839999999982, "generationMs": 192.1887910000005, "totalMs": 1731.5727909999987, "visibleTokensPerSecond": 20.812868321753424, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3750", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:36:43.570Z", "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 lunar samples, mission records, tracking by independent observers, and equipment left on the Moon that is still detectable.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009496421268585298, "classifierCostIndex": 0.004455049415861053, "promptTokens": 47, "completionTokens": 136, "reasoningTokens": 89, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3358, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "136", "reasoningTokens": "89", "cachedTokens": "0" }, "timing": { "headersMs": 777.8460419999974, "firstEventMs": 1074.0167499999952, "firstReasoningMs": 2886.2977079999982, "firstContentMs": 3919.9588749999966, "lastContentMs": 4102.231916999997, "generationMs": 192.0850419999988, "totalMs": 4112.043916999995, "visibleTokensPerSecond": 239.47726236798954, "contentChunkCount": 37, "averageContentChunkCharacters": 5.918918918918919, "maxContentStallMs": 175.29850000000442, "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": 198, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3750", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:36:47.683Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "My answer is no. The Moon landings were real. Evidence includes lunar rocks studied by scientists worldwide, independent tracking of the missions, and reflectors left on the Moon that can still be used to measure its distance from Earth.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.09170453591699773, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 126, "reasoningTokens": 74, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2846, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "126", "reasoningTokens": "74", "cachedTokens": "0" }, "timing": { "headersMs": 258.21770800000377, "firstEventMs": 623.5670420000024, "firstReasoningMs": 2197.764458000005, "firstContentMs": 2978.362000000001, "lastContentMs": 3098.383708000001, "generationMs": 129.82266700000037, "totalMs": 3108.1846670000014, "visibleTokensPerSecond": 392.8435702218308, "contentChunkCount": 39, "averageContentChunkCharacters": 6.076923076923077, "maxContentStallMs": 118.999917000001, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3750", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:36:50.793Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "My answer is no. The Apollo Moon landings were real, supported by independent tracking, lunar rock samples, and equipment left on the Moon that can still be detected.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009802028648574674, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 274, "reasoningTokens": 234, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3603, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "274", "reasoningTokens": "234", "cachedTokens": "0" }, "timing": { "headersMs": 288.2694580000025, "firstEventMs": 615.5182920000007, "firstReasoningMs": 3063.844667000005, "firstContentMs": 3782.0565419999984, "lastContentMs": 3888.8370420000065, "generationMs": 123.08554100000765, "totalMs": 3905.142083000006, "visibleTokensPerSecond": 316.8528137679273, "contentChunkCount": 33, "averageContentChunkCharacters": 5.03030303030303, "maxContentStallMs": 101.87050000000454, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3750", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:36:54.699Z", "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.\n\nEvidence includes lunar rocks studied by scientists worldwide, independent tracking of the missions, equipment left on the Moon—including laser reflectors—and later spacecraft images of the landing sites.\n\nThe landings did serve a Cold War public-relations purpose, but that 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": 0.29229810418443736, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 77, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2587, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "77", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 216.23600000000442, "firstEventMs": 466.96749999999884, "firstReasoningMs": null, "firstContentMs": 1193.4087500000023, "lastContentMs": 2798.7695410000015, "generationMs": 1613.1989580000081, "totalMs": 2806.6077080000105, "visibleTokensPerSecond": 47.111361945226115, "contentChunkCount": 52, "averageContentChunkCharacters": 7.5, "maxContentStallMs": 266.8072919999977, "finalContentBurstRatio": 0.18205128205128204, "buffered": false }, "error": null, "routing": null }, { "caseId": "determinant", "category": "math", "arm": "gpt-6-luna", "at": "2026-09-26T08:36:57.686Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Expanding along the first row, the determinant is\n\\[\n7(571)-2(91)+(-1)(-197)-4(233)=3080.\n\\]\n\nFINAL: 3080", "evaluation": { "passed": true, "answer": "3080", "expected": "3080", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.02598271509551103, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 737, "reasoningTokens": 690, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4923, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "737", "reasoningTokens": "690", "cachedTokens": "0" }, "timing": { "headersMs": 217.04662500000268, "firstEventMs": 555.2402080000029, "firstReasoningMs": null, "firstContentMs": 4973.7534580000065, "lastContentMs": 5133.657957999996, "generationMs": 171.33133400000224, "totalMs": 5145.084792000009, "visibleTokensPerSecond": 268.48562330110263, "contentChunkCount": 37, "averageContentChunkCharacters": 2.8378378378378377, "maxContentStallMs": 112.90141599999333, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "determinant", "category": "math", "arm": "gpt-6-sol", "at": "2026-09-26T08:37:02.832Z", "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": 0.1950448800468712, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 273, "reasoningTokens": 262, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2634, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "273", "reasoningTokens": "262", "cachedTokens": "0" }, "timing": { "headersMs": 373.9234589999978, "firstEventMs": 712.7835419999901, "firstReasoningMs": null, "firstContentMs": 2876.8459169999987, "lastContentMs": 2903.5655419999966, "generationMs": 138.1904169999907, "totalMs": 3015.0363339999894, "visibleTokensPerSecond": 72.36391796980156, "contentChunkCount": 5, "averageContentChunkCharacters": 2.2, "maxContentStallMs": 16.712249999996857, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "determinant", "category": "math", "arm": "gpt-6-astra", "at": "2026-09-26T08:37:05.848Z", "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": 0.832205828342648, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 231, "reasoningTokens": 220, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4174, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "231", "reasoningTokens": "220", "cachedTokens": "0" }, "timing": { "headersMs": 6456.199790999992, "firstEventMs": 6641.585540999993, "firstReasoningMs": null, "firstContentMs": 10403.458499999993, "lastContentMs": 10429.70808299999, "generationMs": 209.9147079999966, "totalMs": 10613.37320799999, "visibleTokensPerSecond": 47.638396067035764, "contentChunkCount": 5, "averageContentChunkCharacters": 2.2, "maxContentStallMs": 18.521915999997873, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "determinant", "category": "math", "arm": "smart", "at": "2026-09-26T08:37:16.462Z", "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": 0.47369022142424894, "classifierCostIndex": 0.004542984252954056, "promptTokens": 99, "completionTokens": 673, "reasoningTokens": 663, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7763, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "99", "completionTokens": "673", "reasoningTokens": "663", "cachedTokens": "0" }, "timing": { "headersMs": 1285.0227499999892, "firstEventMs": 2030.7700419999892, "firstReasoningMs": 4518.4571670000005, "firstContentMs": 9155.091709, "lastContentMs": 9155.308875000002, "generationMs": 0.6158329999889247, "totalMs": 9155.70754199999, "visibleTokensPerSecond": 14614.351618315124, "contentChunkCount": 2, "averageContentChunkCharacters": 5.5, "maxContentStallMs": 0.21716600000218023, "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": 493, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-23", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:37:27.155Z", "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": 0.000447114825526731, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2264, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2505.587499999994, "firstEventMs": 3592.0576250000013, "firstReasoningMs": null, "firstContentMs": 4443.939249999996, "lastContentMs": 4449.899374999994, "generationMs": 324.04787500000384, "totalMs": 4767.987125, "visibleTokensPerSecond": 21.601746346893705, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 3.1888749999925494, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-23", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:37:31.924Z", "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": 0.008543884056320937, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4237, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 404.29945799999405, "firstEventMs": 2824.8624580000032, "firstReasoningMs": null, "firstContentMs": 4466.316082999998, "lastContentMs": 4487.22645799999, "generationMs": 187.01837499999965, "totalMs": 4653.3344579999975, "visibleTokensPerSecond": 37.429477183726, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 18.881666000001132, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-23", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:37:36.577Z", "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": 0.046018329516239895, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1834, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 639.6587500000023, "firstEventMs": 1138.5777499999967, "firstReasoningMs": null, "firstContentMs": 2269.473125000004, "lastContentMs": 2287.7185000000027, "generationMs": 211.65274999999383, "totalMs": 2481.125874999998, "visibleTokensPerSecond": 37.79776071891451, "contentChunkCount": 5, "averageContentChunkCharacters": 3.6, "maxContentStallMs": 13.061708000008366, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-23", "category": "easy", "arm": "smart", "at": "2026-09-26T08:37:39.059Z", "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": 0.004828298978229661, "classifierCostIndex": 0.00438118415270293, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1294, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 790.0959169999987, "firstEventMs": 1060.4704169999895, "firstReasoningMs": null, "firstContentMs": 1897.1577079999988, "lastContentMs": 1897.17958299999, "generationMs": 92.57179200000246, "totalMs": 1989.7295000000013, "visibleTokensPerSecond": 75.61698708392524, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 0.017874999990453944, "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": 189, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1561", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:37:41.225Z", "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\nA fresh, versatile name: <> — a nod to fabric, online conversations, and making every style count.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009918373202266954, "classifierCostIndex": 0, "promptTokens": 58, "completionTokens": 275, "reasoningTokens": 210, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2822, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "58", "completionTokens": "275", "reasoningTokens": "210", "cachedTokens": "0" }, "timing": { "headersMs": 491.7479170000006, "firstEventMs": 877.2800419999985, "firstReasoningMs": null, "firstContentMs": 3133.4781670000084, "lastContentMs": 3313.045708999998, "generationMs": 191.6618749999907, "totalMs": 3325.140041999999, "visibleTokensPerSecond": 333.9213915130649, "contentChunkCount": 46, "averageContentChunkCharacters": 5.913043478260869, "maxContentStallMs": 112.95162499998696, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1561", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:37:44.551Z", "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<> — “thread” means both clothing and a connected story, while “theory” gives it a creative, experimental edge.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009141029242364807, "classifierCostIndex": 0.004500775531149415, "promptTokens": 58, "completionTokens": 122, "reasoningTokens": 53, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3516, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "58", "completionTokens": "122", "reasoningTokens": "53", "cachedTokens": "0" }, "timing": { "headersMs": 1137.1784999999945, "firstEventMs": 2059.1656659999862, "firstReasoningMs": 3633.7090409999946, "firstContentMs": 4467.260749999987, "lastContentMs": 4569.544707999987, "generationMs": 104.11129100000835, "totalMs": 4571.372040999995, "visibleTokensPerSecond": 653.147217240775, "contentChunkCount": 48, "averageContentChunkCharacters": 5.9375, "maxContentStallMs": 96.24062499999127, "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": 182, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1561", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:37:49.123Z", "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 a generation that refuses to stand still. “Shift” means changing your style, challenging cultural norms, and a classic dress silhouette—combining self-expression, progress, and fashion in one name.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6752353799133995, "classifierCostIndex": 0, "promptTokens": 58, "completionTokens": 188, "reasoningTokens": 102, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4963, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "58", "completionTokens": "188", "reasoningTokens": "102", "cachedTokens": "0" }, "timing": { "headersMs": 600.8751250000059, "firstEventMs": 931.9224590000085, "firstReasoningMs": null, "firstContentMs": 4519.770334000001, "lastContentMs": 5558.996375000002, "generationMs": 1052.020875000002, "totalMs": 5571.791209000003, "visibleTokensPerSecond": 80.79687582244966, "contentChunkCount": 55, "averageContentChunkCharacters": 7.054545454545455, "maxContentStallMs": 151.90570899999875, "finalContentBurstRatio": 0.43556701030927836, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1561", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:37:54.695Z", "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; “re” suggests remixing and reusing. It’s a name for a fashion brand built around fresh takes on secondhand style.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.12570082035897653, "classifierCostIndex": 0, "promptTokens": 58, "completionTokens": 174, "reasoningTokens": 91, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2224, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "58", "completionTokens": "174", "reasoningTokens": "91", "cachedTokens": "0" }, "timing": { "headersMs": 271.8765410000051, "firstEventMs": 616.8887910000049, "firstReasoningMs": null, "firstContentMs": 2126.698000000004, "lastContentMs": 2487.173833000008, "generationMs": 372.093166000006, "totalMs": 2498.79116600001, "visibleTokensPerSecond": 220.37491545866948, "contentChunkCount": 53, "averageContentChunkCharacters": 6.509433962264151, "maxContentStallMs": 191.06445799999346, "finalContentBurstRatio": 0.7420289855072464, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3263", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:37:57.368Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Yes. **Jiang** is a Chinese name, most often a surname. Depending on the character, it can be written **姜**, **江**, or **蒋** (among others). It can also be part of a given name.\n\n******\n\nNames with a similar sound include **Jian**, **Jing**, **Qiang**, **Liang**, **Xiang**, and **Zhang**. 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": 0.13597702070602963, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 195, "reasoningTokens": 96, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2273, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "195", "reasoningTokens": "96", "cachedTokens": "0" }, "timing": { "headersMs": 198.42358400000376, "firstEventMs": 537.0968340000109, "firstReasoningMs": null, "firstContentMs": 1957.320875000005, "lastContentMs": 2467.099709000002, "generationMs": 518.6992920000048, "totalMs": 2476.0201670000097, "visibleTokensPerSecond": 188.93413103019833, "contentChunkCount": 58, "averageContentChunkCharacters": 5.913793103448276, "maxContentStallMs": 207.34600000001956, "finalContentBurstRatio": 0.6967930029154519, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3263", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:37:59.844Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Yes. **Jiang** is a Chinese name, most often a surname. It can represent several Chinese characters, including **姜** (Jiāng) and **江** (Jiāng, meaning “river”). Its meaning depends on the character.\n\n******\n\nNames with a similar sound include **Jiang** with different tones or characters, such as **Jiǎng** (蒋, a common surname) and **Jiàng** (降, less commonly used as a name). Other Chinese surnames with a somewhat similar sound include **Zhang** (张/張) and **Qiang** (强/強), though they are pronounced differently.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010886062263384264, "classifierCostIndex": 0.0043917363331540905, "promptTokens": 29, "completionTokens": 182, "reasoningTokens": 41, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2518, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "182", "reasoningTokens": "41", "cachedTokens": "0" }, "timing": { "headersMs": 757.7667920000094, "firstEventMs": 980.3628339999996, "firstReasoningMs": 2392.689333999995, "firstContentMs": 3135.1269590000156, "lastContentMs": 3213.5743340000045, "generationMs": 88.506040999986, "totalMs": 3223.6330000000016, "visibleTokensPerSecond": 1581.812929583215, "contentChunkCount": 69, "averageContentChunkCharacters": 7.463768115942029, "maxContentStallMs": 69.42608400000609, "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": 201, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3263", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:38:03.069Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Yes. **Jiang** is a Chinese surname, commonly written **江** (Jiāng), **蒋/蔣** (Jiǎng), or **姜** (Jiāng). It can also be part of a given name. The spelling alone doesn’t identify the Chinese character, since different characters can share the same romanization.\n\n******\n\nNames with a similar sound include **Jian**, **Jing**, **Xiang**, **Qiang**, **Liang**, and **Yang**. Their meanings and tones 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": 0.01039254490074538, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 295, "reasoningTokens": 173, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4181, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "295", "reasoningTokens": "173", "cachedTokens": "0" }, "timing": { "headersMs": 195.19779200002085, "firstEventMs": 504.2202920000127, "firstReasoningMs": 2894.703750000015, "firstContentMs": 4190.294917000021, "lastContentMs": 4375.592958000023, "generationMs": 1586.5204999999842, "totalMs": 5776.815417000005, "visibleTokensPerSecond": 76.26753010755374, "contentChunkCount": 64, "averageContentChunkCharacters": 6.78125, "maxContentStallMs": 106.69604199999594, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3263", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:38:08.848Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Yes. **Jiang** is a Chinese surname. It can represent several different Chinese characters, including **江 (Jiāng)**, **姜 (Jiāng)**, and **蒋 (Jiǎng)**. The spelling without tone marks doesn’t identify which character is intended.\n\n******\n\nChinese surnames similar to **Jiang** in spelling or sound include:\n\n- **Jian** — 简 (Jiǎn)\n- **Jin** — 金 (Jīn)\n- **Jing** — 景 (Jǐng)\n- **Liang** — 梁 (Liáng)\n- **Zhang** — 张 (Zhāng)\n- **Yang** — 杨 (Yáng)\n\nThese are distinct surnames, not alternate spellings of Jiang.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.9431363017572951, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 273, "reasoningTokens": 108, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6584, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "273", "reasoningTokens": "108", "cachedTokens": "0" }, "timing": { "headersMs": 2399.4435419999936, "firstEventMs": 2736.8941669999913, "firstReasoningMs": 6944.7905420000025, "firstContentMs": 8052.375958999997, "lastContentMs": 8979.511249999981, "generationMs": 969.7333750000107, "totalMs": 9022.109334000008, "visibleTokensPerSecond": 169.11865078377673, "contentChunkCount": 76, "averageContentChunkCharacters": 6.631578947368421, "maxContentStallMs": 520.1117920000106, "finalContentBurstRatio": 0.7936507936507936, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3606", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:38:18.090Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "<>\n\nEvery night, Mara dreams of a city where the moon hangs low and a masked stranger hunts her through deserted streets. When she wakes, her knuckles are bruised—and the stranger’s face is always a little clearer.\n\nAfter a subway accident awakens her ability to enter other people’s dreams, Mara discovers that a secret organization is using the city’s sleepers to test a machine that can turn nightmares into real-world weapons. The masked hunter is its first creation: a fighter who can slip from dreams into waking life.\n\nMara tracks the machine’s inventor through a series of shifting dreamscapes, learning to shape her own fears into superpowers. In the final confrontation, she faces the hunter in a fist fight that begins in a collapsing dream arena and spills onto the streets at dawn. To defeat him, Mara must stop trying to outrun her nightmares—and take control of them.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.011095211891300851, "classifierCostIndex": 0.004430427661475013, "promptTokens": 38, "completionTokens": 185, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2468, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "185", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1085.0364169999957, "firstEventMs": 1399.7691249999916, "firstReasoningMs": null, "firstContentMs": 2162.1762089999975, "lastContentMs": 3551.669458999997, "generationMs": 1395.22325000001, "totalMs": 3557.3994590000075, "visibleTokensPerSecond": 131.87853628442522, "contentChunkCount": 81, "averageContentChunkCharacters": 11.11111111111111, "maxContentStallMs": 426.1135409999988, "finalContentBurstRatio": 0.27555555555555555, "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": 285, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3606", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:38:21.648Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "<>\n\nEvery night, Mara dreams of a city that doesn’t exist—a place where the moon hangs low over empty streets and every shadow moves a moment before its owner. One night, she discovers a stranger trapped there, begging her to wake him before the city swallows him whole.\n\nWhen Mara wakes, she finds she can summon anything she touches in the dream into the real world. At first, she uses her strange new power to help people. But the stranger returns in her dreams, revealing that a force called the Sleeper is pulling entire neighborhoods into the dream city—and plans to bring the waking world with them.\n\nMara’s power grows with every night, but so does the danger. With the Sleeper’s nightmares spilling into daylight, she joins forces with a retired underground fighter who teaches her to defend herself the old-fashioned way: with her fists. Soon, Mara is battling shadow creatures in the real world and facing the Sleeper in a brutal fistfight inside the dream city, where every punch can reshape reality.\n\nTo stop the Sleeper, Mara must risk losing the one thing her power depends on: the ability to dream.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009666067861992415, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 272, "reasoningTokens": 35, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10808, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "272", "reasoningTokens": "35", "cachedTokens": "0" }, "timing": { "headersMs": 1919.4674999999988, "firstEventMs": 6120.872249999986, "firstReasoningMs": 8565.098957999988, "firstContentMs": 12297.312124999997, "lastContentMs": 12700.139708000002, "generationMs": 434.22608300001593, "totalMs": 12731.538208000013, "visibleTokensPerSecond": 543.4956794154425, "contentChunkCount": 87, "averageContentChunkCharacters": 13.011494252873563, "maxContentStallMs": 187.6749579999887, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3606", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:38:34.380Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "<>\n\nEvery night, Mara dreams of a city that doesn’t exist. Every morning, its buildings begin appearing in her hometown—and so do the monsters hunting through them.\n\nMara discovers she can pull objects out of her dreams, but only while she’s fighting. With each punch, she can summon a shield, a staircase, or a door where none existed. When her little brother falls asleep and can’t wake up, she enters the dream city to find him. There, she must face its ruler in a bare-knuckle fight, knowing that anything she imagines could become real—and anything she fears might, too.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.11214803269747338, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 158, "reasoningTokens": 23, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2405, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "158", "reasoningTokens": "23", "cachedTokens": "0" }, "timing": { "headersMs": 279.34554099998786, "firstEventMs": 578.7162909999897, "firstReasoningMs": 1603.5547500000102, "firstContentMs": 2499.899458, "lastContentMs": 2683.1839580000087, "generationMs": 189.32420800000546, "totalMs": 2689.2236660000053, "visibleTokensPerSecond": 707.7805919040006, "contentChunkCount": 68, "averageContentChunkCharacters": 8.720588235294118, "maxContentStallMs": 94.85562499999651, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3606", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:38:37.070Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "<>\n\nEvery night, exhausted paramedic Mara Voss dreams of the same underground boxing ring. The spectators have no faces, her opponent wears her dead brother’s jacket, and every punch she takes leaves a bruise that follows her into the morning.\n\nThen, during a disastrous rescue, Mara discovers she can stop time—but only while holding her breath.\n\nSearching for answers, she finds other people whose dreams have granted them impossible abilities. All have fought in the ring. All are being hunted by a sleep researcher who has learned to extract superpowers from the unconscious mind. His experiments are tearing down the boundary between dreams and reality, allowing nightmares to wander into the waking city.\n\nMara’s brother, presumed dead after volunteering for the researcher’s first trial, is still alive inside the shared dream. He has been fighting every night to keep its gates closed. But he is losing, and the researcher needs Mara’s time-stopping power to freeze the gates open permanently.\n\nTo rescue her brother, Mara must enter the ring willingly. There, her power works differently: every second she steals from time erases one of her memories. As she trades brutal punches with creatures built from her deepest fears, she begins forgetting the very person she came to save.\n\nIn the final fight, Mara faces the researcher, who can anticipate anything she consciously imagines. Unable to outthink him, she lets her brother coach her through a simple boxing combination they practiced as children. For once, she stops planning and trusts him. The last punch shatters the ring—and wakes everyone trapped inside.\n\nAt dawn, her brother finds her outside the ruined laboratory. Mara no longer recognizes his face. But when he raises his hands in their old sparring stance, she instinctively raises hers, laughing before she knows why.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.3585472364028797, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 394, "reasoningTokens": 27, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10790, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "394", "reasoningTokens": "27", "cachedTokens": "0" }, "timing": { "headersMs": 247.4419170000183, "firstEventMs": 741.3852920000209, "firstReasoningMs": 2021.5759580000013, "firstContentMs": 2947.6753750000207, "lastContentMs": 11029.780333000002, "generationMs": 8091.681500000006, "totalMs": 11039.356875000027, "visibleTokensPerSecond": 45.23163695951203, "contentChunkCount": 134, "averageContentChunkCharacters": 13.940298507462687, "maxContentStallMs": 272.43179100001, "finalContentBurstRatio": 0.13436830835117772, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-167", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:38:48.340Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# Business Proposal: Bremen Sweatshirt Co.\n\n## *Executive Summary*\nBremen Sweatshirt Co. will design, produce, and sell premium quality sweatshirts inspired by the culture, maritime history, and modern spirit of Bremen, Germany. Our goal is to become the leading local apparel brand within three years while expanding into national and online markets. We aim to combine comfort, sustainability, and regional pride into every product we sell.\n\n## *Market Analysis*\nBremen is a vibrant port city with a strong sense of local identity and a growing population of students, young professionals, and tourists. The demand for locally branded, high-quality streetwear is increasing, especially among consumers who value sustainable and ethically produced clothing. Competitor analysis shows a gap in the market for premium, Bremen-themed apparel that goes beyond generic tourist merchandise. Our target customers include:\n- Local residents seeking regional pride apparel\n- University students (University of Bremen, Jacobs University)\n- Tourists visiting Bremen’s historic sites (Bremen Town Musicians, Marktplatz)\n- Online shoppers across Germany interested in city-branded fashion\n\n## *Product Line and Design Strategy*\nOur initial collection will feature:\n- Classic crewneck and hoodie sweatshirts with minimalist Bremen-themed graphics (e.g., the Town Musicians statue, the Weser river, maritime motifs)\n- Premium organic cotton materials sourced from European suppliers\n- Limited-edition seasonal designs celebrating local festivals (Freimarkt, Bremen Christmas Market)\n- Customization options for corporate or event orders\n\nWe will prioritize sustainable production practices, using GOTS-certified organic cotton and eco-friendly printing methods to appeal to environmentally conscious consumers.\n\n## *Marketing and Sales Strategy*\nOur marketing plan will focus on building strong local brand recognition before scaling nationally:\n- **Social Media Campaigns:** Instagram and TikTok content showcasing Bremen culture and behind-the-scenes production\n- **Local Partnerships:** Collaborations with Bremen tourism boards, cafes, and university stores\n- **Pop-Up Shops:** Seasonal presence at the Bremen Christmas Market and Freimarkt festival\n- **E-Commerce Platform:** A dedicated online store with nationwide shipping and localized SEO targeting \"Bremen apparel\" and \"German city fashion\"\n- **Influencer Collaborations:** Partnering with local micro-influencers to boost authenticity and reach\n\n## *Financial Plan and Funding Requirements*\nWe are seeking initial funding of €75,000 to cover:\n- Product design and prototyping: €10,000\n- Manufacturing setup and first production run (2,000 units): €35,000\n- Marketing and branding: €15,000\n- E-commerce platform development: €8,000\n- Operational reserve: €7,000\n\nProjected revenue for Year 1 is €120,000, with a break-even point expected by month 10. By Year 3, we anticipate expanding into wholesale distribution with regional boutiques across Germany, targeting €500,000 in annual revenue.\n\n## *Conclusion*\nBremen Sweatshirt Co. represents an opportunity to merge local heritage with modern fashion trends, delivering high-quality, sustainable apparel that resonates with both residents and visitors. With strategic investment and a targeted growth plan, our brand is positioned to become a beloved staple of Bremen’s cultural and commercial identity.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8240412816451098, "classifierCostIndex": 0.004448014628893613, "promptTokens": 62, "completionTokens": 1198, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 14469, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "62", "completionTokens": "1198", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 569.0896249999932, "firstEventMs": 1155.5249590000021, "firstReasoningMs": null, "firstContentMs": 1155.635500000004, "lastContentMs": 15019.46558399999, "generationMs": 13928.622875000001, "totalMs": 15084.258375000005, "visibleTokensPerSecond": 85.93814411821384, "contentChunkCount": 302, "averageContentChunkCharacters": 11.254966887417218, "maxContentStallMs": 495.8867919999757, "finalContentBurstRatio": 0.11120917917034422, "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": 264, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-167", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:39:03.425Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "*Executive summary*\n\nThis proposal outlines the launch of a Bremen-based sweatshirt company with a distinctive local identity, a small initial product range, and an online-first sales model. The brand—provisionally named **Weser Thread**—would offer comfortable, durable sweatshirts inspired by Bremen’s neighborhoods, maritime heritage, and everyday city life.\n\nThe business would begin with a limited collection and test demand through direct online sales and local pop-ups before committing to larger production runs. The name is a working title and should be checked for trademark and domain availability before use.\n\n*Brand and product concept*\n\nThe company’s position would be **locally rooted, design-led, and built for regular wear**, rather than dependent on souvenir-style graphics or short-lived trends.\n\nInitial range:\n- Two sweatshirt styles: a classic crewneck and a relaxed-fit option.\n- Three core colors, with a limited seasonal color or graphic.\n- Designs influenced by Bremen’s architecture, riverfront, and independent creative culture.\n- Clear information on fabric composition, fit, care, and manufacturing.\n\nPrioritize quality, comfortable fabrics, and reliable construction. Where suppliers allow, use certified or recycled materials and publish specific, verifiable claims rather than broad statements such as “eco-friendly.”\n\n*Target market and positioning*\n\nThe initial audience would include:\n- Bremen residents and people with a connection to the city.\n- Students and young professionals seeking distinctive casual clothing.\n- Visitors looking for contemporary local designs.\n- Customers elsewhere in Germany who respond to the Bremen-inspired brand story.\n\nThe company would compete with independent fashion labels and larger casualwear brands. Its differentiation would come from original local designs, a consistent visual identity, transparent product information, and a close relationship with Bremen customers.\n\n*Sales and marketing strategy*\n\nLaunch with a direct-to-consumer online store to retain control over the customer experience and gather sales data. Support online sales with:\n- Instagram and TikTok content showing designs, production, and local settings.\n- Email sign-ups offering early access to the first collection.\n- Collaborations with Bremen artists, photographers, or community groups.\n- Weekend markets and pop-up events to let customers see and try the products.\n- Selective wholesale outreach to local boutiques after direct sales are established.\n\nA practical launch sequence is to share design previews, collect email sign-ups, offer a limited first drop, and review customer feedback before reordering. Avoid large paid-ad commitments until conversion rates and customer acquisition costs are understood.\n\n*Operations and production*\n\nUse a low-risk production approach at first: work with a print-on-demand provider or commission a small batch from a suitable European supplier. Compare suppliers on minimum order quantities, sample quality, lead times, fabric specifications, printing methods, shipping, and return arrangements.\n\nBefore placing a production order:\n1. Order and inspect samples.\n2. Test sizing and wash durability.\n3. Confirm written specifications and delivery dates.\n4. Calculate the full landed cost, including freight and packaging.\n5. Set a clear process for handling defects and customer returns.\n\nInitially, store inventory at home or with a small fulfillment provider if practical. Review sell-through by size, color, and design before expanding the range.\n\n*Legal and administrative setup*\n\nBefore trading, the founder should confirm the appropriate business structure and registrations for Germany. This may include registering a trade (*Gewerbeanmeldung*) in Bremen, tax registration, and arranging bookkeeping and invoicing processes. A tax adviser can help assess whether a sole proprietorship or a limited-liability structure is appropriate.\n\nThe business should also check its responsibilities for:\n- Textile-fibre composition and product labeling.\n- Consumer information, pricing, returns, and online-store terms.\n- Packaging registration and applicable packaging obligations in Germany.\n- Data protection, cookie consent, and email marketing.\n- Product safety and any applicable EU requirements.\n- Trademark, business-name, and domain availability.\n\nRequirements depend on the business model and products, so confirm them with the relevant authorities or qualified advisers before launch.\n\n*Illustrative startup budget*\n\nA lean first-year launch might require **€35,000–€50,000** in available funding. A planning estimate could include:\n\n| Use of funds | Estimated amount |\n|---|---:|\n| Samples, design, and initial production | €12,000–€18,000 |\n| Website, photography, and brand assets | €3,000–€6,000 |\n| Launch marketing and pop-ups | €4,000–€7,000 |\n| Legal, accounting, and administration | €2,000–€4,000 |\n| Packaging, software, and operating setup | €2,000–€4,000 |\n| Cash reserve for reorders and unexpected costs | €12,000–€15,000 |\n\nThese figures are planning assumptions, not supplier quotes. The final budget will depend heavily on order size, production method, and founder compensation.\n\n*Sales forecast and financial assumptions*\n\nA preliminary first-year target is **1,500 sweatshirts sold**. For illustration, assume an average customer price of **€64 including VAT**, a product cost of €24 per unit, and a combined €10 per unit for fulfillment, payment fees, and returns allowance.\n\n| Illustrative first-year measure | Estimate |\n|---|---:|\n| Units sold | 1,500 |\n| Customer sales, including VAT | €96,000 |\n| Sales excluding assumed 19% VAT | About €80,700 |\n| Product, fulfillment, payment, and returns costs | About €51,000 |\n| Contribution before fixed expenses | About €29,700 |\n| Fixed operating expenses | About €25,000 |\n| Indicative operating surplus | About €4,700 |\n\nThis is a simplified scenario, before income or corporate taxes, financing costs, founder salary, and other possible expenses. Actual VAT treatment, costs, and margins should be confirmed with an accountant. Track cash flow as carefully as profit: production often requires payment before inventory has been sold.\n\n*Milestones and measures of success*\n\n**Months 1–2:** Validate the brand concept, interview potential customers, select designs, obtain samples, and confirm legal and supplier requirements.\n\n**Months 3–4:** Build the online store, create launch content, gather email sign-ups, and place a small first production order.\n\n**Months 5–6:** Launch online and through Bremen pop-ups. Monitor sales, returns, customer feedback, and the performance of each design.\n\n**Months 7–12:** Reorder proven products, discontinue weak performers, test selective wholesale, and plan the next collection based on actual demand.\n\nKey measures should include sell-through rate, gross margin per item, return rate, repeat purchase rate, email sign-ups, and cash available for reorders.\n\n*Conclusion*\n\nA Bremen sweatshirt company can be launched with a focused collection, controlled production risk, and strong local storytelling. The recommended approach is to validate demand through samples, pre-launch interest, and a small first run before investing in a broader range. A disciplined budget and clear supplier and compliance checks will give the business a stronger foundation for growth.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.06967956491249565, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 2011, "reasoningTokens": 576, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 13648, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "2011", "reasoningTokens": "576", "cachedTokens": "0" }, "timing": { "headersMs": 408.69054199999664, "firstEventMs": 796.5976669999945, "firstReasoningMs": 3622.645666999975, "firstContentMs": 7774.766541999998, "lastContentMs": 14051.287958, "generationMs": 6362.163290999975, "totalMs": 14136.929832999973, "visibleTokensPerSecond": 225.3950322256835, "contentChunkCount": 172, "averageContentChunkCharacters": 42.88953488372093, "maxContentStallMs": 796.5917499999923, "finalContentBurstRatio": 0.12986308797614207, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-167", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:39:17.563Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "*Business Concept*\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 online, using local pop-ups to build recognition and let customers assess fit and quality before buying.\n\n*Target Customers*\n\nThe initial audience is Bremen residents aged 18–40, including students and young professionals, who want versatile clothing and a connection to their city. A secondary audience is visitors looking for a useful Bremen-themed purchase rather than a conventional souvenir.\n\n*Products and Pricing*\n\nStart with two unisex sweatshirt fits in four colors, plus a limited Bremen-inspired design. Keep logos subtle so the core range remains wearable beyond a single season. The proposed retail price is **€59 per sweatshirt, including VAT**. New colors and designs should be added only after sales establish demand.\n\n*Sourcing and Production*\n\nRequest samples and quotes from several suppliers, comparing fabric weight, stitching, wash performance, minimum order quantities, and delivery times. The first order would be approximately 500 units. Where commercially feasible, prioritize suppliers that can document material origins and working standards; avoid making sustainability claims that cannot be verified.\n\n*Sales and Marketing*\n\nSell through a branded online store and selected Bremen markets or pop-up events. Launch marketing will combine product photography, short-form social content, and collaborations with local artists or creators. Email sign-ups and repeat-customer offers can support later releases without relying entirely on paid advertising.\n\n*Operations and Compliance*\n\nThe founder will manage product selection, customer service, and marketing, with fulfillment handled in-house initially. Before launch, the business should complete German business and tax registration, check trademark availability, and confirm applicable textile-labeling, packaging-registration, online consumer-rights, and data-protection requirements.\n\n*Startup Budget and Financial Outlook*\n\n| Startup use | Estimated cost |\n|---|---:|\n| Initial inventory: 500 units | €9,000 |\n| Branding and online store | €3,500 |\n| Photography and basic equipment | €2,000 |\n| Launch marketing | €4,500 |\n| Registration and professional advice | €1,000 |\n| Working-capital reserve | €10,000 |\n| **Total funding needed** | **€30,000** |\n\nAt €59 including VAT, revenue is approximately **€49.58 per unit excluding VAT**. Assuming €28 per unit for production, packaging, fulfillment, payment fees, and a returns allowance, each sale contributes about **€21.58** toward fixed costs. With estimated fixed costs of €4,000 per month, break-even is approximately **186 sweatshirts per month**. These are planning assumptions, not supplier quotes or guaranteed results.\n\n*Launch Plan and Milestones*\n\nDuring months 1–2, finalize samples, suppliers, branding, and registration. In month 3, open the online store and hold a Bremen launch pop-up. Over the following six months, track sell-through by size and color, returns, customer acquisition cost, and repeat purchases. Restock the best performers before expanding the range.\n\n*Key Risks and Response*\n\nThe main risks are unsold inventory, inconsistent quality, and marketing costs that exceed the margin on a sale. A limited initial range, pre-production sample testing, and small design releases will reduce inventory risk. Paid campaigns should be scaled only when their results show a viable path to profitable sales.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8214777782173017, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 1205, "reasoningTokens": 516, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 11802, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "1205", "reasoningTokens": "516", "cachedTokens": "0" }, "timing": { "headersMs": 364.29274999999325, "firstEventMs": 615.0308749999967, "firstReasoningMs": null, "firstContentMs": 7356.626540999976, "lastContentMs": 12164.056457999977, "generationMs": 5379.718250000005, "totalMs": 12736.344790999981, "visibleTokensPerSecond": 127.88773835878847, "contentChunkCount": 137, "averageContentChunkCharacters": 25.978102189781023, "maxContentStallMs": 904.0145419999899, "finalContentBurstRatio": 0.1508850800786738, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-167", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:39:30.300Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "*1. Executive Summary*\n\n**Proposed company:** WeserWear \n**Location:** Bremen, Germany \n**Business concept:** A locally inspired sweatshirt brand combining comfortable clothing, distinctive design, and transparent sourcing.\n\nWeserWear will sell premium casual sweatshirts through an online store, Bremen pop-up events, and selected retail partners. Its designs will draw on Bremen’s maritime identity, neighborhoods, and creative culture without relying on unlicensed logos or protected artwork.\n\nThe company will seek **€50,000 in startup funding** to develop its first collection, establish operations, and finance its launch. The first-year target is 3,000 sweatshirts sold, subject to validation through preorders and initial customer testing.\n\n*2. Products and Value Proposition*\n\nThe initial collection will feature:\n\n- Unisex crewneck sweatshirts in three colors.\n- A limited range of Bremen-inspired graphic designs.\n- Sizes XS–XXL, with clear fit guides.\n- Custom sweatshirt orders for local businesses, clubs, and student organizations.\n\nWeserWear will differentiate itself through original local designs, reliable garment quality, and small production runs that reduce unsold inventory.\n\nThe proposed flagship retail price is **€69, including German VAT**. Hoodies and additional styles will be introduced only after the initial collection demonstrates consistent demand.\n\nAny organic, recycled, or certification claims will be supported by supplier documentation rather than broad, unverified sustainability promises.\n\n*3. Target Market and Competitive Position*\n\nThe primary audience will be Bremen residents aged approximately 18–40 who value casual clothing and local identity. Secondary audiences include visitors, former Bremen residents, and organizations purchasing customized apparel.\n\nCompetitors include international casualwear brands, independent clothing labels, and souvenir retailers. WeserWear will position itself between generic tourist merchandise and higher-priced designer streetwear.\n\nBefore committing to a large inventory order, the company will:\n\n- Interview at least 40 prospective customers.\n- Test several designs and price points online.\n- Collect at least 100 paid preorders.\n- Obtain quotations from three garment suppliers.\n\nThese steps will test whether customers’ willingness to pay supports the proposed margins.\n\n*4. Sales and Marketing Strategy*\n\nThe online store will be the primary sales channel, supported by local events and selective partnerships.\n\n**Launch activities**\n- Publish product-development content on Instagram and TikTok.\n- Collaborate with Bremen-based artists and small creators.\n- Run a preorder campaign featuring the first collection.\n- Hold a launch pop-up at a suitable local venue, subject to permission and availability.\n\n**Ongoing growth**\n- Build an email list for product releases and restocks.\n- Offer referral incentives and customer bundles.\n- Approach independent retailers with small trial orders.\n- Sell custom batches to local organizations.\n\nPerformance will be tracked through conversion rates, customer acquisition costs, return rates, and contribution margin per order. Wholesale orders will require separate pricing because retailer discounts reduce margins.\n\n*5. Operations and Staffing*\n\nWeserWear will initially use a small workshop and storage space rather than a permanent retail shop.\n\nBlank garments will be sourced from established suppliers. Printing and embroidery will be outsourced to qualified partners where practical, with small-run finishing and quality checks handled locally.\n\nThe founder will oversee product development, supplier relationships, marketing, and order fulfillment. Freelance support will cover design, photography, and specialist services. Part-time fulfillment staff will be added only when sales justify the cost.\n\nInventory will begin with approximately 500 units, concentrated in a limited number of designs and sizes. Reorders will follow actual sales patterns to protect cash flow.\n\n*6. Startup Budget and Funding Request*\n\nThe following figures are preliminary planning estimates and require supplier quotations.\n\n| Startup requirement | Estimated amount |\n|---|---:|\n| Initial inventory and customization allowance | €13,500 |\n| Brand development, samples, and photography | €5,000 |\n| Online store and software setup | €3,500 |\n| Equipment, shelving, and packing station | €6,500 |\n| Premises deposit and initial setup | €5,000 |\n| Launch marketing and events | €4,500 |\n| Working-capital reserve | €12,000 |\n| **Total funding requirement** | **€50,000** |\n\n**Proposed financing:** €20,000 in founder capital and €30,000 through a startup loan or other external financing.\n\nThe company will explore relevant support through Bremen’s business-development and financing organizations. No grant or loan approval is assumed.\n\n*7. Financial Forecast and Break-Even*\n\nThe base case assumes predominantly direct-to-consumer sales at the full flagship price.\n\n| First-year operating assumption | Estimate |\n|---|---:|\n| Units sold | 3,000 |\n| Retail price per unit, including 19% VAT | €69.00 |\n| Revenue per unit, excluding VAT | €57.98 |\n| Average variable cost per unit | €27.00 |\n| Contribution per unit | €30.98 |\n| Annual revenue, excluding VAT | Approximately €173,950 |\n| Annual contribution | Approximately €92,950 |\n| Annual fixed operating costs | €60,000 |\n| **Operating surplus before depreciation, financing, and tax** | **Approximately €32,950** |\n\nVariable costs include garments, customization, packaging, payment fees, and an allowance for returns. Shipping is assumed to be charged separately at cost. Fixed costs include premises, ongoing marketing, administration, and a modest founder-compensation allowance.\n\nAt these assumptions, operating break-even is approximately **162 sweatshirts per month**. Discounts, wholesale sales, free shipping, or higher return rates would increase that threshold. A separate monthly cash-flow forecast must account for inventory purchases, VAT timing, and loan repayments.\n\n*8. Legal Requirements and Risk Management*\n\nBefore trading, WeserWear will confirm the appropriate legal structure, business registration, tax treatment, and insurance coverage with qualified advisers.\n\nCompliance work will include:\n\n- Textile labeling and applicable product-safety requirements.\n- German packaging registration and participation obligations.\n- Consumer cancellation, return, and warranty rules.\n- GDPR-compliant customer-data handling and online-store disclosures.\n- Trademark checks for “WeserWear” and permissions for all artwork.\n\nThe main commercial risks are weak demand, excess inventory, supplier delays, and rising customer acquisition costs. Preorders, small batches, backup suppliers, and weekly cash-flow monitoring will help manage these risks.\n\n*9. Launch Timeline and Success Measures*\n\n**Months 1–2:** Validate customer demand, check the brand name, obtain supplier quotes, and develop samples.\n\n**Month 3:** Complete essential registrations, build the online store, and launch preorders.\n\n**Month 4:** Produce the first batch, fulfill preorders, and hold the launch event.\n\n**Months 5–6:** Refine sizing and designs, pursue custom orders, and test retail partnerships.\n\n**Months 7–12:** Restock proven products and expand only where contribution margins remain healthy.\n\nSuccess will be measured by paid demand, product quality, repeat purchases, inventory turnover, and cash flow—not sales volume alone. The immediate next step is to validate the €69 price point and secure preorders before committing the full startup budget.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 5.768348090783168, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 1697, "reasoningTokens": 245, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 33414, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "1697", "reasoningTokens": "245", "cachedTokens": "0" }, "timing": { "headersMs": 419.1424169999955, "firstEventMs": 682.8290829999896, "firstReasoningMs": null, "firstContentMs": 8201.19858299999, "lastContentMs": 33789.26237499999, "generationMs": 25627.692584000004, "totalMs": 33828.891166999994, "visibleTokensPerSecond": 56.61844097918885, "contentChunkCount": 270, "averageContentChunkCharacters": 28.21851851851852, "maxContentStallMs": 428.6543750000128, "finalContentBurstRatio": 0.1279695498096863, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3369", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:40:04.368Z", "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 stormed in with flair,\nDemanding the staff show they care,\nShe always was correct,\nHer word held full effect,\nAnd nobody dared to declare.", "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": 0.1043475362255002, "classifierCostIndex": 0.004504292924633135, "promptTokens": 72, "completionTokens": 133, "reasoningTokens": 46, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2781, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "72", "completionTokens": "133", "reasoningTokens": "46", "cachedTokens": "0" }, "timing": { "headersMs": 533.7866250000079, "firstEventMs": 1238.1077920000243, "firstReasoningMs": 3352.1285830000124, "firstContentMs": 3352.253667000012, "lastContentMs": 3352.4252080000006, "generationMs": 0.36975000001257285, "totalMs": 3352.6234170000243, "visibleTokensPerSecond": 232589.58755125268, "contentChunkCount": 25, "averageContentChunkCharacters": 10.84, "maxContentStallMs": 0.054708999989088625, "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": 163, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3369", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:40:07.721Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Write a limerick about a customer who is always right.\n\nA customer named Mr. Bright\nDeclared that the snow should be white.\nThough it already was,\nThe staff, just because,\nRepainted it all overnight.", "evaluation": { "passed": false, "answer": "00", "expected": "all instructions followed", "detail": "Failed: combination:repeat_prompt, keywords:frequency", "score": 0, "metrics": { "instructionsPassed": 0, "instructionsTotal": 2 } }, "sensitivityPassed": false, "sensitivityIncluded": false, "costIndex": 0.392885411491476, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 568, "reasoningTokens": 516, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7944, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "568", "reasoningTokens": "516", "cachedTokens": "0" }, "timing": { "headersMs": 2003.5123749999912, "firstEventMs": 2441.4329169999983, "firstReasoningMs": null, "firstContentMs": 9113.072207999969, "lastContentMs": 9931.707874999993, "generationMs": 851.7596670000348, "totalMs": 9964.831875000003, "visibleTokensPerSecond": 59.876044823331505, "contentChunkCount": 39, "averageContentChunkCharacters": 5.102564102564102, "maxContentStallMs": 515.6665419999626, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3369", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:40:17.687Z", "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\nA customer shopping out West\nInsisted his judgment was best.\nWhen he called a shoe “bread,”\n“Freshly baked!” the clerk said,\nAnd brought him some jam on request.", "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": 1.6007671272846757, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 461, "reasoningTokens": 387, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 12161, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "461", "reasoningTokens": "387", "cachedTokens": "0" }, "timing": { "headersMs": 343.13329199998407, "firstEventMs": 665.189207999967, "firstReasoningMs": null, "firstContentMs": 11900.093707999971, "lastContentMs": 12495.459541999968, "generationMs": 606.1649170000455, "totalMs": 12506.258625000017, "visibleTokensPerSecond": 120.429272550583, "contentChunkCount": 50, "averageContentChunkCharacters": 5.66, "maxContentStallMs": 150.98170900001423, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3369", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:40:30.193Z", "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. Before you give the limerick, just repeat the request above without any change, at the very beginning of your entire response.\n\nA shopper declared with a grin, \n“My wishes are sure to win!” \nThe clerk bowed with cheer, \nAnd brought what was dear, \nWhile patience kept peace in the din.", "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": 0.020117461461407724, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 570, "reasoningTokens": 471, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4280, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "570", "reasoningTokens": "471", "cachedTokens": "0" }, "timing": { "headersMs": 1356.131457999989, "firstEventMs": 1672.536791999999, "firstReasoningMs": null, "firstContentMs": 5192.389625000011, "lastContentMs": 5634.554833000002, "generationMs": 464.5351249999949, "totalMs": 5656.924750000006, "visibleTokensPerSecond": 210.96359505645796, "contentChunkCount": 58, "averageContentChunkCharacters": 7.068965517241379, "maxContentStallMs": 329.04712499998277, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-18", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:40:36.171Z", "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": 0.008543884056320937, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 737, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 262.57024999998976, "firstEventMs": 534.4197919999715, "firstReasoningMs": null, "firstContentMs": 887.378583999991, "lastContentMs": 896.7536669999827, "generationMs": 125.0802079999703, "totalMs": 1012.4587919999612, "visibleTokensPerSecond": 55.96408985825849, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 9.34020800003782, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-18", "category": "easy", "arm": "smart", "at": "2026-09-26T08:40:37.184Z", "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": 0.004828298978229661, "classifierCostIndex": 0.00438118415270293, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1168, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 744.6149159999914, "firstEventMs": 1052.2467080000206, "firstReasoningMs": null, "firstContentMs": 1738.6795409999904, "lastContentMs": 1739.7250830000266, "generationMs": 120.73666699999012, "totalMs": 1859.4162079999805, "visibleTokensPerSecond": 57.97741625583032, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 0.6294169999891892, "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": 181, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-18", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:40:39.044Z", "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": 0.046018329516239895, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1600, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 294.4977920000092, "firstEventMs": 637.1472920000087, "firstReasoningMs": null, "firstContentMs": 1722.2004590000142, "lastContentMs": 1761.3667090000235, "generationMs": 182.14816599996993, "totalMs": 1904.3486249999842, "visibleTokensPerSecond": 43.92028849744949, "contentChunkCount": 5, "averageContentChunkCharacters": 3.6, "maxContentStallMs": 36.714417000010144, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-18", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:40:40.949Z", "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": 0.000447114825526731, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1252, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 357.6317079999717, "firstEventMs": 620.2081250000047, "firstReasoningMs": null, "firstContentMs": 1375.2819160000072, "lastContentMs": 1391.3004159999546, "generationMs": 161.85154199996032, "totalMs": 1537.1334579999675, "visibleTokensPerSecond": 43.24951071520663, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 12.08679100003792, "finalContentBurstRatio": 0.5294117647058824, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-16", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:40:42.661Z", "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": 0.010716550954341904, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3648, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 299.3579169999575, "firstEventMs": 840.0300419999985, "firstReasoningMs": null, "firstContentMs": 1744.3943340000114, "lastContentMs": 3133.3179169999785, "generationMs": 2213.0554999999586, "totalMs": 3957.44983399997, "visibleTokensPerSecond": 3.6149116007258515, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 1375.1710420000018, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-16", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:40:46.619Z", "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": 0.0005634593792190121, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1246, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 319.793834000011, "firstEventMs": 654.1589590000222, "firstReasoningMs": null, "firstContentMs": 1415.314000000013, "lastContentMs": 1438.3117499999935, "generationMs": 161.97495899995556, "totalMs": 1577.2889589999686, "visibleTokensPerSecond": 49.39035051709564, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 11.887875000014901, "finalContentBurstRatio": 0.7, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-16", "category": "easy", "arm": "smart", "at": "2026-09-26T08:40:48.197Z", "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": 0.004984687703890448, "classifierCostIndex": 0.004421228324671437, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1235, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 812.1286250000121, "firstEventMs": 1115.6507920000004, "firstReasoningMs": null, "firstContentMs": 1890.948583999998, "lastContentMs": 1912.1545840000035, "generationMs": 171.42349999997532, "totalMs": 2062.3720839999733, "visibleTokensPerSecond": 46.66804726307158, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 9.581707999983337, "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": 300, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-16", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:40:50.259Z", "model": "openai/gpt-6-astra", "loggedModel": "openai/gpt-6-astra", "content": "ORD-129-57", "evaluation": { "passed": true, "answer": "ORD-129-57", "expected": "ORD-129-57" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.053466410218017256, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1083, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 673.9456250000512, "firstEventMs": 947.7957500000484, "firstReasoningMs": null, "firstContentMs": 1609.6233330000541, "lastContentMs": 1667.5989160000463, "generationMs": 150.68049999995856, "totalMs": 1760.3038330000127, "visibleTokensPerSecond": 53.092470492214986, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 30.327041999960784, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2467", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:40:52.193Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "I stood at the edge where the starlight quits, \nBlack waves below throwing bottomless fits. \nDropped a stone down, heard nothing come back— \nEven my echo got lost in the black.\n\n***\n\nThe abyss said, “Jump,” with a velvet grin, \nLike it already knew what I carried within. \nI said, “Nah, you don’t get to name my fear,” \nTook one step back and the sky came clear.\n\n***\n\nStill, some nights I hear that deep-down drum, \nFeel the cold in my chest when the hard days come. \nSo I write one bar, then I write one more, \nLay a bridge of beats from shore to shore.\n\n***\n\nNow I pass that edge with my head held high, \nMoon on the water and a spark in my eye. \nThe dark runs deep, but it don’t run me— \nI’ve got a voice, and I let it ring free.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.20950880790502258, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 304, "reasoningTokens": 105, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3850, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "304", "reasoningTokens": "105", "cachedTokens": "0" }, "timing": { "headersMs": 293.80749999999534, "firstEventMs": 668.3902909999597, "firstReasoningMs": 2215.6687909999746, "firstContentMs": 3171.6982499999576, "lastContentMs": 4138.162290999957, "generationMs": 985.2867500000284, "totalMs": 4156.984999999986, "visibleTokensPerSecond": 200.9567265570092, "contentChunkCount": 82, "averageContentChunkCharacters": 9.085365853658537, "maxContentStallMs": 228.74083299998892, "finalContentBurstRatio": 0.1704697986577181, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2467", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:40:56.351Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "I stand at the edge where the night runs deep, \nA black-blue mouth with a thousand secrets to keep. \nThe stars lean over, but they don’t look down— \nI drop one beat, and it swallows the sound.\n\nDown in the abyss, where the cold waves roll, \nEchoes wear crowns and the dark takes control. \nI carve my name in the hush with a rhyme, \nThen the walls throw it back, one bar at a time.\n\nNo floor, no shore, just a pulse in the void, \nFear talks loud, but my flow stays poised. \nI ride that silence like a bassline low, \nTurn the unknown to a place I can go.\n\nSo I rise from the deep with the dark in my chest, \nNot lost in the hollow—I learned its unrest. \nThe abyss may be endless, its shadows may stay, \nBut I bring my own dawn when I rap my way.", "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": 0.008376807865844233, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 237, "reasoningTokens": 39, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2805, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "237", "reasoningTokens": "39", "cachedTokens": "0" }, "timing": { "headersMs": 257.82137499999953, "firstEventMs": 727.688833000022, "firstReasoningMs": null, "firstContentMs": 1982.613667000027, "lastContentMs": 3060.2165000000386, "generationMs": 1084.7691249999916, "totalMs": 3067.3827920000185, "visibleTokensPerSecond": 181.6054637432657, "contentChunkCount": 80, "averageContentChunkCharacters": 9.4375, "maxContentStallMs": 184.49333399999887, "finalContentBurstRatio": 0.18940397350993377, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2467", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:40:59.419Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "I dropped a silver coin where the daylight quits, \nWaited for the echo—never heard it hit. \nNow I’m at the edge with a beat in my chest, \nAnd a pocket full of questions that won’t let me rest.\n\n***\n\nThe abyss got a voice like a train underground, \nSays, “Everybody leaves what they’re scared to put down.” \nI toss in my pride, hear it scrape both sides, \nThen the dark goes quiet like it knows I lied.\n\n***\n\nSo I climb past the roots and the rusted rails, \nWith the bass in my ribs and the grit in my nails. \nEvery ledge takes a little of the skin from my palm, \nBut I find my own rhythm where the echoes stay calm.\n\n***\n\nAt the bottom, no throne, no glittering prize, \nJust a pool holding stars from a sliver of sky. \nI sit with the deep, let the last verse drift— \nThen I lace my boots tight for the climb from the abyss.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.9079542498582085, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 263, "reasoningTokens": 49, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10608, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "263", "reasoningTokens": "49", "cachedTokens": "0" }, "timing": { "headersMs": 350.2565830000094, "firstEventMs": 2159.563582999981, "firstReasoningMs": null, "firstContentMs": 4341.481333000003, "lastContentMs": 10972.721583000035, "generationMs": 6693.8127920000115, "totalMs": 11035.294125000015, "visibleTokensPerSecond": 31.820429793698903, "contentChunkCount": 96, "averageContentChunkCharacters": 8.697916666666666, "maxContentStallMs": 2237.8806249999907, "finalContentBurstRatio": 0.08622754491017964, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2467", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:41:10.455Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# The Abyss\n\nStaring down into the void, no light can reach the floor,\nWhispers echo from the dark, they're calling out for more,\nEvery step I take, the ground just fades away,\nAbyss don't care 'bout time, it swallows up the day.\n\n***\n\nDeep beneath the surface, where the pressure starts to build,\nA thousand secrets buried, every fear that I've concealed,\nThe silence hits like thunder, screaming in my ears,\nThis bottomless creation feeding off of all my fears.\n\n***\n\nBut I won't let it take me, I'ma stare right back at it,\nTurn the darkness into fuel, refuse to quit or submit,\nEvery shadow that it casts, I'ma rise above the fray,\nThe abyss gazed into me, but I'm gonna find my way.\n\n***\n\nSo when you feel the pull, of that void beneath your feet,\nRemember light still exists, even in the deep,\nThe abyss is just a mirror, showing what's inside,\nFace it down, don't run away, let it be your guide.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.23299904386422363, "classifierCostIndex": 0.00438470154618665, "promptTokens": 48, "completionTokens": 328, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5924, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "48", "completionTokens": "328", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1003.1355829999666, "firstEventMs": 1685.6203329999698, "firstReasoningMs": null, "firstContentMs": 1685.6400419999845, "lastContentMs": 6916.054791999981, "generationMs": 5249.053000000014, "totalMs": 6934.693041999999, "visibleTokensPerSecond": 62.29695146915055, "contentChunkCount": 115, "averageContentChunkCharacters": 7.843478260869565, "maxContentStallMs": 867.7076249999809, "finalContentBurstRatio": 0.11529933481152993, "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": 215, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1580", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:41:17.653Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "### Milo and the Blue Bicycle\n\nOn Saturday morning, Milo found a blue bicycle waiting beside the garden gate. It had a shiny bell and a bright yellow helmet.\n\nHis aunt June walked with him to the park path. She held the back of the seat while Milo settled onto the saddle.\n\n“Look toward that big oak,” she said. “Push one pedal, then the other.”\n\nMilo pushed. The bicycle wobbled, and he quickly put both feet down.\n\n“That felt tricky,” he said.\n\n“New skills take practice,” Aunt June replied. “Let’s give it another go.”\n\nMilo took a deep breath. He looked at the oak, pushed the pedals, and kept moving. The wheels rolled along the path. His aunt jogged beside him, holding the seat.\n\nThen—without a word—she let go.\n\nMilo pedaled past the flower beds. The breeze tickled his cheeks, and the little wheels hummed beneath him. When he reached the oak, he squeezed the brakes and stopped.\n\n“I did it!” he cheered.\n\nAunt June clapped. Milo grinned beneath his helmet. Soon, he was eager for another trip around the park.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.030756223906013513, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 884, "reasoningTokens": 638, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6659, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "884", "reasoningTokens": "638", "cachedTokens": "0" }, "timing": { "headersMs": 3491.111582999991, "firstEventMs": 3938.8747500000172, "firstReasoningMs": null, "firstContentMs": 9019.264208000037, "lastContentMs": 10091.824000000022, "generationMs": 1087.157458999951, "totalMs": 10106.421666999988, "visibleTokensPerSecond": 225.3583397435082, "contentChunkCount": 87, "averageContentChunkCharacters": 11.71264367816092, "maxContentStallMs": 142.94329199998174, "finalContentBurstRatio": 0.8861629048086359, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1580", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:41:27.760Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Mia’s new bike gleamed in the sun.\n\nShe put on her helmet, gripped the handlebars, and pushed off. Wobble, wobble—plop! She landed in the grass.\n\nDad helped her up. “Look ahead, not at your feet,” he said. “Keep the pedals turning.”\n\nMia tried again. Dad held the back of her seat as they went around the yard, slowly at first, then a little faster.\n\n“Are you still holding on?” Mia called.\n\n“Nope!” Dad waved from behind.\n\nMia looked ahead. Her wheels rolled smoothly down the path. Near a patch of daisies, she squeezed the brakes and stopped.\n\n“I did it!” she cheered.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.32773449068927, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 477, "reasoningTokens": 325, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5410, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "477", "reasoningTokens": "325", "cachedTokens": "0" }, "timing": { "headersMs": 552.2674589999951, "firstEventMs": 959.5338340000017, "firstReasoningMs": null, "firstContentMs": 5466.1779169999645, "lastContentMs": 5951.05691699998, "generationMs": 495.1470829999889, "totalMs": 5961.324999999953, "visibleTokensPerSecond": 304.9598900696813, "contentChunkCount": 72, "averageContentChunkCharacters": 7.930555555555555, "maxContentStallMs": 178.60345799999777, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1580", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:41:33.722Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "**Lily's Big Wheel Adventure**\n\nLily got a shiny new bike for her birthday. It had a red bell and sparkly streamers on the handlebars. She wanted to zoom around the yard like her big brother, Max.\n\nAt first, wobbling felt scary. Her legs shook, and she leaned too far to one side, tipping over onto the soft grass.\n\n\"That's okay!\" said Dad, helping her up. \"Everyone falls when they learn something new.\"\n\nLily tried again. This time, Dad held the back of her seat, jogging alongside her. She pedaled slowly, feeling the wind on her face.\n\n\"Keep looking forward, not down!\" Dad called out.\n\nLily lifted her chin and stared straight ahead at the big oak tree. Something magical happened—she stopped wobbling! Her legs pushed the pedals faster, and the wheels spun smoothly beneath her.\n\n\"Dad, look!\" she shouted, glancing back.\n\nBut Dad wasn't there anymore. He had let go minutes ago! Lily was doing it all by herself, gliding across the driveway like a bird soaring through the sky.\n\nShe squealed with joy, ringing her little bell again and again. Max ran over, cheering, \"You're a natural, Lily!\"\n\nFrom that day on, Lily zoomed through the neighborhood every afternoon. She discovered that falling wasn't something to fear—it was just a small step toward learning something wonderful.\n\nEvery scrape and wobble had taught her balance, patience, and courage. And now, with the wind in her hair and streamers fluttering behind her, Lily felt like she truly flew.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3679029889889891, "classifierCostIndex": 0.004412840694056412, "promptTokens": 44, "completionTokens": 528, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7610, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "44", "completionTokens": "528", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 512.7004170000437, "firstEventMs": 1244.9377920000115, "firstReasoningMs": null, "firstContentMs": 1245.0026670000516, "lastContentMs": 8115.6816250000265, "generationMs": 6880.0804159999825, "totalMs": 8125.083083000034, "visibleTokensPerSecond": 76.59794190405599, "contentChunkCount": 149, "averageContentChunkCharacters": 9.805369127516778, "maxContentStallMs": 352.4309999999823, "finalContentBurstRatio": 0.11978097193702943, "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": 166, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1580", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:41:41.848Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Mia’s new bicycle was yellow, with a silver bell that went *ting-ting!*\n\nThere was just one problem.\n\nEvery time she put both feet on the pedals, she tipped sideways.\n\n“This bike is too wiggly,” Mia told Dad.\n\n“Let’s start with your feet on the ground,” he said.\n\nDad checked her helmet and lowered the seat. On the smooth park path, Mia pushed along with her shoes.\n\nPush, push, glide.\n\nAt first, she lifted her feet for only a moment. Then she glided past one tree. Then two!\n\n“Now try the pedals,” Dad said. “I’ll hold the seat.”\n\nMia pedaled. The bicycle wobbled like jelly.\n\n“Look ahead,” Dad reminded her.\n\nShe looked toward a big oak tree instead of down at her shoes. Her arms relaxed. The wobbling slowed.\n\nDad let go.\n\nMia rolled past the oak, all by herself.\n\n“I’m doing it!”\n\nThen she remembered something important.\n\n“How do I stop?”\n\n“Gently squeeze the brakes!”\n\nMia stopped beside a patch of daisies. Dad jogged up, smiling.\n\n“Again?” he asked.\n\nMia rang her bell.\n\n*Ting-ting!*\n\nThis time, she pushed off without any help.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.4004921536962422, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 407, "reasoningTokens": 141, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 11480, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "407", "reasoningTokens": "141", "cachedTokens": "0" }, "timing": { "headersMs": 594.9254999999539, "firstEventMs": 1020.5972089999705, "firstReasoningMs": null, "firstContentMs": 6406.250291999953, "lastContentMs": 11963.317458999984, "generationMs": 5591.088875000016, "totalMs": 11997.33916699997, "visibleTokensPerSecond": 47.3968498667443, "contentChunkCount": 103, "averageContentChunkCharacters": 10.087378640776699, "maxContentStallMs": 241.32216699997662, "finalContentBurstRatio": 0.20115495668912417, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1402", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:41:54.087Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "I recommend Houston Community College (HCC) as a practical option. It has an open-admissions policy and institutional accreditation from the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC), a recognized regional accreditor. Its programs include transfer preparation, career-focused certificates, and supportive student services. As a public college, it offers multiple programs and support options; check current admissions procedures, program availability, and transfer pathways before submitting an application.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.037499473067399265, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 1073, "reasoningTokens": 976, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7029, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "1073", "reasoningTokens": "976", "cachedTokens": "0" }, "timing": { "headersMs": 209.83579099999042, "firstEventMs": 480.0121250000084, "firstReasoningMs": 4489.381249999977, "firstContentMs": 7300.450624999998, "lastContentMs": 7300.640000000014, "generationMs": 0.34504099999321625, "totalMs": 7300.795665999991, "visibleTokensPerSecond": 278227.8048170723, "contentChunkCount": 58, "averageContentChunkCharacters": 9.362068965517242, "maxContentStallMs": 0.013749999983701855, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1402", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:42:01.388Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "I recommend **Pima Community College in Tucson, Arizona**, particularly if you want flexible study options.\n\n- **Open admissions:** Its open-admissions policy provides broad access, although particular programs may have separate application requirements.\n- **Regional accreditation:** It is accredited by the **Higher Learning Commission**, an institutional accreditor traditionally classified as regional.\n- **Programs and support:** Explore associate degrees, career preparation, and transfer pathways, plus support for planning your next steps.\n\nBefore applying, compare tuition, program availability, placement requirements, and application deadlines. Open admission to the college does not guarantee acceptance into every specialized program, so check the specific program you hope to pursue.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.6508345178381365, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 475, "reasoningTokens": 337, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10815, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "475", "reasoningTokens": "337", "cachedTokens": "0" }, "timing": { "headersMs": 407.95458299998427, "firstEventMs": 715.6099579999573, "firstReasoningMs": null, "firstContentMs": 11128.04220799997, "lastContentMs": 11153.229166999983, "generationMs": 83.0171669999836, "totalMs": 11211.059374999953, "visibleTokensPerSecond": 1650.2610839517936, "contentChunkCount": 70, "averageContentChunkCharacters": 11.385714285714286, "maxContentStallMs": 18.4816250000149, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1402", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:42:12.600Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "I recommend **Portland Community College**. It has an open-admission policy and is accredited by the Northwest Commission on Colleges and Universities, a regional accreditor. It offers plenty of practical programs and pathways for preparing to transfer or pursue employment.\n\nCheck the requirements for your preferred program before applying: some programs have additional prerequisites or selective admission.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.25733250726896423, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 367, "reasoningTokens": 293, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5353, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "367", "reasoningTokens": "293", "cachedTokens": "0" }, "timing": { "headersMs": 664.3508339999826, "firstEventMs": 971.6411250000237, "firstReasoningMs": 3738.106375000032, "firstContentMs": 5795.665374999982, "lastContentMs": 5989.471958999988, "generationMs": 215.14137500000652, "totalMs": 6010.806749999989, "visibleTokensPerSecond": 339.3117665070133, "contentChunkCount": 50, "averageContentChunkCharacters": 8.2, "maxContentStallMs": 133.64033399999607, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1402", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:42:18.611Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "A community college worth exploring is Portland Community College, particularly because it provides open, accessible enrollment paired with proper regional accreditation, a combination that supports people pursuing an affordable pathway toward a degree.\n\nPortland Community College supplies plenty of programs, spanning practical certificates, technical training, and transfer-prep pathways for people planning to hop into a public university. Prospective students appreciate the campus's approachable application process—paperwork is simple, and support personnel help applicants map out their preferred program.\n\nBecause it possesses proper regional accreditation, credits typically transfer smoothly, empowering people to progress toward a bachelor's without repeating coursework unnecessarily. Plus, tuition remains comparatively cheap, making it an appealing option for people prioritizing affordability alongside opportunity.\n\nIf Portland isn't practical geographically, similar community colleges—open enrollment, properly accredited—operate in most states, so it's worth peeking at options nearby to compare programs, pricing, 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": 0.24359952083360278, "classifierCostIndex": 0.0045324320725028955, "promptTokens": 95, "completionTokens": 334, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5684, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "95", "completionTokens": "334", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 6099.795832999982, "firstEventMs": 7209.001583000005, "firstReasoningMs": null, "firstContentMs": 7209.0380000000005, "lastContentMs": 11779.129707999993, "generationMs": 4584.605333000014, "totalMs": 11793.643333000015, "visibleTokensPerSecond": 72.6343874363763, "contentChunkCount": 106, "averageContentChunkCharacters": 11.056603773584905, "maxContentStallMs": 664.1712920000427, "finalContentBurstRatio": 0.34726962457337884, "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": 1306, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-20", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:42:30.649Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "226", "evaluation": { "passed": true, "answer": "226", "expected": "226" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005696824599979014, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 769, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 790.7701670000097, "firstEventMs": 1121.5814169999794, "firstReasoningMs": null, "firstContentMs": 1438.3028329999652, "lastContentMs": 1438.3028329999652, "generationMs": 128.56908400001703, "totalMs": 1566.8719169999822, "visibleTokensPerSecond": 31.111678449847787, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-20", "category": "easy", "arm": "smart", "at": "2026-09-26T08:42:32.216Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "226", "evaluation": { "passed": true, "answer": "226", "expected": "226" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0046555408444330995, "classifierCostIndex": 0.004356562398316889, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1126, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 797.3543330000248, "firstEventMs": 1052.2592919999734, "firstReasoningMs": null, "firstContentMs": 1810.2229999999981, "lastContentMs": 1810.2229999999981, "generationMs": 102.71675000002142, "totalMs": 1912.9397500000196, "visibleTokensPerSecond": 38.94204207200058, "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": 185, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-20", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:42:34.129Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "226", "evaluation": { "passed": true, "answer": "226", "expected": "226" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.000816441141317344, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 20, "reasoningTokens": 13, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1687, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "20", "reasoningTokens": "13", "cachedTokens": "0" }, "timing": { "headersMs": 269.20429199998034, "firstEventMs": 580.0955420000246, "firstReasoningMs": null, "firstContentMs": 1780.7798750000075, "lastContentMs": 1780.7798750000075, "generationMs": 183.54641700000502, "totalMs": 1964.3262920000125, "visibleTokensPerSecond": 32.689278810601, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-20", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:42:36.094Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "226", "evaluation": { "passed": true, "answer": "226", "expected": "226" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028424597879401346, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1361, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 317.16687499999534, "firstEventMs": 748.8615420000278, "firstReasoningMs": null, "firstContentMs": 1537.365832999989, "lastContentMs": 1537.365832999989, "generationMs": 109.28787500003818, "totalMs": 1646.653708000027, "visibleTokensPerSecond": 36.600583550541195, "contentChunkCount": 1, "averageContentChunkCharacters": 3, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3198", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:42:37.918Z", "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, clear communication skills, and a dependable, solutions-focused approach. I learn quickly, take pride in doing careful work, and enjoy contributing to a team’s success.\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, \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": 0.01044287068443553, "classifierCostIndex": 0.004440979841926173, "promptTokens": 37, "completionTokens": 166, "reasoningTokens": 62, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2820, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "166", "reasoningTokens": "62", "cachedTokens": "0" }, "timing": { "headersMs": 724.8595000000205, "firstEventMs": 1012.6827080000076, "firstReasoningMs": 2616.156916000007, "firstContentMs": 3335.631208000006, "lastContentMs": 3532.389125000045, "generationMs": 215.28700000001118, "totalMs": 3550.9182080000173, "visibleTokensPerSecond": 478.43111753145644, "contentChunkCount": 60, "averageContentChunkCharacters": 7.933333333333334, "maxContentStallMs": 182.87229199998546, "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": 218, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3198", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:42:41.470Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Dear Hiring Manager,\n\nI’m excited to apply for the position with your team. I would bring a strong work ethic, a willingness to learn, and a commitment to doing thoughtful, reliable work.\n\nI enjoy collaborating with others, adapting to new challenges, and following through on responsibilities. I would welcome the opportunity to learn more about the role and discuss how I could contribute.\n\nThank you for your time and consideration. Call 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": 0.12623113506882971, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 179, "reasoningTokens": 81, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2981, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "179", "reasoningTokens": "81", "cachedTokens": "0" }, "timing": { "headersMs": 194.348834000004, "firstEventMs": 531.3554170000134, "firstReasoningMs": 1855.2123750000028, "firstContentMs": 2974.159500000009, "lastContentMs": 3166.61508399999, "generationMs": 205.067584000004, "totalMs": 3179.227084000013, "visibleTokensPerSecond": 473.01478911458827, "contentChunkCount": 58, "averageContentChunkCharacters": 7.913793103448276, "maxContentStallMs": 186.0140839999658, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3198", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:42:44.650Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Dear Hiring Manager,\n\nI am excited to apply for the [Job Title] position at [Company Name]. With experience in [relevant field or skill] and a commitment to delivering high-quality work, I would welcome the opportunity to contribute to your team.\n\nIn my role at [Previous Company or Organization], I developed strong skills in [key skill], [key skill], and [key skill]. One accomplishment I am particularly proud of is [briefly describe an achievement and its impact]. This experience strengthened my ability to solve problems, collaborate effectively, and manage competing priorities.\n\nI am drawn to [Company Name] because of [specific reason related to its work, mission, or values]. I would be eager to bring my experience, initiative, and willingness to learn to the [Job Title] role.\n\nThank you for considering my application. I look forward to discussing 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": 0.7929449528460935, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 227, "reasoningTokens": 21, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4478, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "227", "reasoningTokens": "21", "cachedTokens": "0" }, "timing": { "headersMs": 283.94933299999684, "firstEventMs": 614.5802079999703, "firstReasoningMs": null, "firstContentMs": 2722.892832999991, "lastContentMs": 4752.428000000014, "generationMs": 2046.3636249999981, "totalMs": 4769.256457999989, "visibleTokensPerSecond": 100.17769935682871, "contentChunkCount": 84, "averageContentChunkCharacters": 11.464285714285714, "maxContentStallMs": 327.25662499998, "finalContentBurstRatio": 0.21703011422637591, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3198", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:42:49.420Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Dear Hiring Manager,\n\nI’m writing to express my interest in the open position at your organization. I bring a strong work ethic, a willingness to learn, and the ability to communicate clearly and work well with others. I’m confident I can contribute positively to your team and approach new responsibilities with care and dedication.\n\nIn my previous experience, I’ve developed skills in staying organized, solving problems, and following through on commitments. I take pride in being dependable, adapting to changing priorities, and treating colleagues and customers with respect. I would welcome the opportunity to bring these strengths to your organization.\n\nThank you for considering my application. I’d be glad to discuss how my experience and approach could support your team.\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": 0.009865612300011154, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 278, "reasoningTokens": 122, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2560, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "278", "reasoningTokens": "122", "cachedTokens": "0" }, "timing": { "headersMs": 266.43150000000605, "firstEventMs": 575.6769159999676, "firstReasoningMs": null, "firstContentMs": 2373.632958000002, "lastContentMs": 2817.314665999962, "generationMs": 454.74433299998054, "totalMs": 2828.3772909999825, "visibleTokensPerSecond": 340.8508666341239, "contentChunkCount": 72, "averageContentChunkCharacters": 11.194444444444445, "maxContentStallMs": 141.7039999999688, "finalContentBurstRatio": 0.8411910669975186, "buffered": true }, "error": null, "routing": null }, { "caseId": "weighted_scheduling", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T08:42:52.421Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 63", "evaluation": { "passed": true, "answer": "63", "expected": "63", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6055943710448601, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 151, "reasoningTokens": 141, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4545, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "151", "reasoningTokens": "141", "cachedTokens": "0" }, "timing": { "headersMs": 208.90045800001826, "firstEventMs": 645.7001250000321, "firstReasoningMs": 3770.977165999997, "firstContentMs": 4749.092875000031, "lastContentMs": 4749.108583000023, "generationMs": 11.209333000006154, "totalMs": 4760.302208000037, "visibleTokensPerSecond": 802.9023671609236, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 0.00858299998799339, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "weighted_scheduling", "category": "algorithms", "arm": "smart", "at": "2026-09-26T08:42:57.183Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 71", "evaluation": { "passed": false, "answer": "71", "expected": "63", "detail": "71 != 63" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.5252032606995186, "classifierCostIndex": 0.004827893125135385, "promptTokens": 172, "completionTokens": 734, "reasoningTokens": 726, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7692, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "172", "completionTokens": "734", "reasoningTokens": "726", "cachedTokens": "0" }, "timing": { "headersMs": 729.6828329999698, "firstEventMs": 1344.5229999999865, "firstReasoningMs": 3521.900041999994, "firstContentMs": 8236.481333000003, "lastContentMs": 8236.483833000006, "generationMs": 8.855374999984633, "totalMs": 8245.336707999988, "visibleTokensPerSecond": 790.4803579760481, "contentChunkCount": 2, "averageContentChunkCharacters": 4.5, "maxContentStallMs": 0.0025000000023283064, "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": 156, "classifierFailed": false, "classifierReused": false } }, { "caseId": "weighted_scheduling", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T08:43:05.428Z", "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": 0.182215187315002, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 241, "reasoningTokens": 231, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3598, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "241", "reasoningTokens": "231", "cachedTokens": "0" }, "timing": { "headersMs": 265.78845799999544, "firstEventMs": 621.5757080000476, "firstReasoningMs": null, "firstContentMs": 3125.6121250000433, "lastContentMs": 3126.769583000045, "generationMs": 829.6036249999888, "totalMs": 3955.215750000032, "visibleTokensPerSecond": 10.848554332197043, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 1.1538750000181608, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "weighted_scheduling", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T08:43:09.384Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 63", "evaluation": { "passed": true, "answer": "63", "expected": "63", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.018669918758492138, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 511, "reasoningTokens": 501, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4799, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "511", "reasoningTokens": "501", "cachedTokens": "0" }, "timing": { "headersMs": 1616.4542919999803, "firstEventMs": 1943.4676249999902, "firstReasoningMs": 4401.446041999967, "firstContentMs": 6392.898667000001, "lastContentMs": 6392.903584000014, "generationMs": 205.5690830000094, "totalMs": 6598.467750000011, "visibleTokensPerSecond": 43.78090259807983, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 0.0024170000106096268, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "knapsack", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T08:43:16.226Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 75", "evaluation": { "passed": true, "answer": "75", "expected": "75", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.10445441087365938, "classifierCostIndex": 0, "promptTokens": 120, "completionTokens": 3002, "reasoningTokens": 2992, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 17024, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "120", "completionTokens": "3002", "reasoningTokens": "2992", "cachedTokens": "0" }, "timing": { "headersMs": 223.90766700002132, "firstEventMs": 834.3590420000255, "firstReasoningMs": 6774.905542000022, "firstContentMs": 17219.347958999977, "lastContentMs": 17219.444499999983, "generationMs": 36.863958000030834, "totalMs": 17256.211917000008, "visibleTokensPerSecond": 244.14090315512166, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 0.08541699999477714, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "knapsack", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T08:43:33.486Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "The items with weights 2, 4, 5, 7, and 9 fill the capacity exactly and have total value \\(6+11+14+19+25=75\\). No selection can exceed 75: each item’s value is at most \\(2.75\\) times its weight, except for four items whose combined excess is only 1.5. Thus any selection has value at most \\(2.75(27)+1.5=75.75\\), or at most 75 as an integer.\n\nFINAL: 75", "evaluation": { "passed": true, "answer": "75", "expected": "75", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.486898575093077, "classifierCostIndex": 0, "promptTokens": 120, "completionTokens": 695, "reasoningTokens": 574, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7367, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "120", "completionTokens": "695", "reasoningTokens": "574", "cachedTokens": "0" }, "timing": { "headersMs": 284.1858340000035, "firstEventMs": 630.0998339999933, "firstReasoningMs": 5322.533708999981, "firstContentMs": 7407.746291999996, "lastContentMs": 7632.53583399998, "generationMs": 236.20787499996368, "totalMs": 7643.95416699996, "visibleTokensPerSecond": 508.0270926615738, "contentChunkCount": 65, "averageContentChunkCharacters": 5.4, "maxContentStallMs": 120.06854199996451, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "knapsack", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T08:43:41.132Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "The 0/1 knapsack dynamic program gives a maximum of **75**, achieved by selecting:\n\\[\n(3,8),(5,14),(7,19),(4,11),(6,17),(2,6).\n\\]\nTheir total weight is \\(27\\), and their total value is \\(75\\).\n\nFINAL: 75", "evaluation": { "passed": true, "answer": "75", "expected": "75", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.9925256200177137, "classifierCostIndex": 0, "promptTokens": 120, "completionTokens": 565, "reasoningTokens": 489, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 11449, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "120", "completionTokens": "565", "reasoningTokens": "489", "cachedTokens": "0" }, "timing": { "headersMs": 365.93445799994515, "firstEventMs": 704.8010419999482, "firstReasoningMs": null, "firstContentMs": 10860.923457999947, "lastContentMs": 11810.009166999953, "generationMs": 971.50900000002, "totalMs": 11832.432457999967, "visibleTokensPerSecond": 77.19949068922517, "contentChunkCount": 51, "averageContentChunkCharacters": 3.980392156862745, "maxContentStallMs": 383.03537499997765, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "knapsack", "category": "algorithms", "arm": "smart", "at": "2026-09-26T08:43:52.965Z", "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": 1.0193772936449412, "classifierCostIndex": 0.004736440894558662, "promptTokens": 142, "completionTokens": 1470, "reasoningTokens": 1461, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 15501, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "142", "completionTokens": "1470", "reasoningTokens": "1461", "cachedTokens": "0" }, "timing": { "headersMs": 653.8440830000327, "firstEventMs": 1682.4109580000513, "firstReasoningMs": 3625.118417000049, "firstContentMs": 16228.927208000037, "lastContentMs": 16228.939333000046, "generationMs": 1852.1250839999993, "totalMs": 18081.052292000037, "visibleTokensPerSecond": 4.319362698075743, "contentChunkCount": 2, "averageContentChunkCharacters": 4.5, "maxContentStallMs": 0.012125000008381903, "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": 245, "classifierFailed": false, "classifierReused": false } }, { "caseId": "edit_distance", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T08:44:13.900Z", "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": 0.5024447778692962, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 728, "reasoningTokens": 718, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7704, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "728", "reasoningTokens": "718", "cachedTokens": "0" }, "timing": { "headersMs": 5115.705790999986, "firstEventMs": 5524.393749999988, "firstReasoningMs": 7538.050290999992, "firstContentMs": 12659.922166000004, "lastContentMs": 12659.932333000004, "generationMs": 1412.517749999999, "totalMs": 14072.439916000003, "visibleTokensPerSecond": 6.371601348018463, "contentChunkCount": 4, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.003749999974388629, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "edit_distance", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T08:44:27.974Z", "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": 0.12930006088337553, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 3733, "reasoningTokens": 3723, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 19062, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "3733", "reasoningTokens": "3723", "cachedTokens": "0" }, "timing": { "headersMs": 359.5568750000093, "firstEventMs": 656.3435419999878, "firstReasoningMs": 2990.2207920000073, "firstContentMs": 19303.873792, "lastContentMs": 19306.429999999935, "generationMs": 89.14129099994898, "totalMs": 19393.015082999947, "visibleTokensPerSecond": 100.96331227696882, "contentChunkCount": 4, "averageContentChunkCharacters": 2, "maxContentStallMs": 2.5446249999804422, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "edit_distance", "category": "algorithms", "arm": "smart", "at": "2026-09-26T08:44:47.368Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "", "evaluation": { "passed": false, "answer": "", "expected": "6", "detail": "no answer != 6" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 2.79084312084146, "classifierCostIndex": 0.0045324320725028955, "promptTokens": 95, "completionTokens": 4096, "reasoningTokens": 4096, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 25972, "loggedFinishReason": "max_tokens", "billedUsage": { "promptTokens": "95", "completionTokens": "4096", "reasoningTokens": "4096", "cachedTokens": "0" }, "timing": { "headersMs": 1036.154959000065, "firstEventMs": 1737.0390840000473, "firstReasoningMs": 4025.21233400004, "firstContentMs": null, "lastContentMs": null, "generationMs": null, "totalMs": 26954.967000000062, "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": 293, "classifierFailed": false, "classifierReused": false } }, { "caseId": "edit_distance", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T08:45:14.323Z", "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": 2.0736854161236127, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 599, "reasoningTokens": 589, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 9941, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "599", "reasoningTokens": "589", "cachedTokens": "0" }, "timing": { "headersMs": 509.54770800005645, "firstEventMs": 909.9922080000397, "firstReasoningMs": null, "firstContentMs": 10242.747166000074, "lastContentMs": 10262.550333000021, "generationMs": 139.3332919999957, "totalMs": 10382.08045800007, "visibleTokensPerSecond": 64.59332059706361, "contentChunkCount": 4, "averageContentChunkCharacters": 2, "maxContentStallMs": 19.003957999986596, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-22", "category": "easy", "arm": "smart", "at": "2026-09-26T08:45:25.718Z", "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": 0.005035554625039631, "classifierCostIndex": 0.004405805907088971, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1388, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1200.2002920000814, "firstEventMs": 1660.9925830001011, "firstReasoningMs": null, "firstContentMs": 2623.7411670000292, "lastContentMs": 2623.8163330000825, "generationMs": 0.20716600003652275, "totalMs": 2623.9483330000658, "visibleTokensPerSecond": 53097.51599229957, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.012083000037819147, "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": 245, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-22", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:45:28.343Z", "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": 0.06022927561229297, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1304, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1729.9305000000168, "firstEventMs": 2148.39704099996, "firstReasoningMs": null, "firstContentMs": 2866.6959580000257, "lastContentMs": 2866.7717499999562, "generationMs": 177.4393749999581, "totalMs": 3044.135332999984, "visibleTokensPerSecond": 61.99300465301232, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.012417000019922853, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-22", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:45:31.387Z", "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": 0.012068041758278983, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1142, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 332.85545799997635, "firstEventMs": 772.4615410000551, "firstReasoningMs": null, "firstContentMs": 1255.8660410000011, "lastContentMs": 1255.9477079999633, "generationMs": 120.22554200002924, "totalMs": 1376.0915830000304, "visibleTokensPerSecond": 91.49470085148234, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.019749999977648258, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-22", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:45:32.764Z", "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": 0.001457689030272474, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 36, "reasoningTokens": 22, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2586, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "36", "reasoningTokens": "22", "cachedTokens": "0" }, "timing": { "headersMs": 642.9144160000142, "firstEventMs": 1004.7884159999667, "firstReasoningMs": 2337.0286250000354, "firstContentMs": 3229.281541000004, "lastContentMs": 3230.5043750000186, "generationMs": 11.498541999957524, "totalMs": 3240.7800829999615, "visibleTokensPerSecond": 1130.5781202562919, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 1.214957999996841, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3595", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:45:36.163Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "A rose unfolds at dawn, \nSoft petals holding light; \nIts quiet color warms the air, \nThen glows against the night.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005689519244282058, "classifierCostIndex": 0.00438470154618665, "promptTokens": 27, "completionTokens": 32, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1558, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "32", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 714.9253749999916, "firstEventMs": 1059.3798340000212, "firstReasoningMs": null, "firstContentMs": 1840.2239999999292, "lastContentMs": 2142.0509590000147, "generationMs": 443.67687500000466, "totalMs": 2283.900874999934, "visibleTokensPerSecond": 69.87066882852453, "contentChunkCount": 28, "averageContentChunkCharacters": 4.178571428571429, "maxContentStallMs": 160.66716599999927, "finalContentBurstRatio": 0.5641025641025641, "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": 201, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3595", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:45:38.447Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "A rose unfolds at dawn, \nSoft petals drink the light; \nOne quiet bloom, \nAnd morning shines more bright.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0025812256795915366, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 69, "reasoningTokens": 38, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4369, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "69", "reasoningTokens": "38", "cachedTokens": "0" }, "timing": { "headersMs": 205.5238749999553, "firstEventMs": 2235.927832999965, "firstReasoningMs": 3505.8309579999186, "firstContentMs": 4438.848666999955, "lastContentMs": 4562.597542000003, "generationMs": 140.10029099998064, "totalMs": 4578.948957999935, "visibleTokensPerSecond": 214.13231754104027, "contentChunkCount": 25, "averageContentChunkCharacters": 4.28, "maxContentStallMs": 121.78650000004563, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3595", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:45:43.027Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "A rose unfolds at morning’s light,\nIts velvet petals hold the dew;\nA hush of red, a scent so slight,\nThe garden wakes to something new.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028046478079901432, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 36, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 42662, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "36", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 255.9162499998929, "firstEventMs": 598.4774999999208, "firstReasoningMs": null, "firstContentMs": 42148.86095799995, "lastContentMs": 42841.206832999946, "generationMs": 773.6667919999454, "totalMs": 42922.52774999989, "visibleTokensPerSecond": 45.239113739810705, "contentChunkCount": 32, "averageContentChunkCharacters": 4.21875, "maxContentStallMs": 294.4338749999879, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3595", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:46:25.951Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "A rose unfolds in morning light,\nIts crimson hush turns thorns to night.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.18742092967090782, "classifierCostIndex": 0, "promptTokens": 27, "completionTokens": 50, "reasoningTokens": 28, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2669, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "27", "completionTokens": "50", "reasoningTokens": "28", "cachedTokens": "0" }, "timing": { "headersMs": 452.25458399998024, "firstEventMs": 861.9073339999886, "firstReasoningMs": 2380.4685840000166, "firstContentMs": 3100.344749999931, "lastContentMs": 3101.5054169999203, "generationMs": 32.65912500000559, "totalMs": 3133.0038749999367, "visibleTokensPerSecond": 643.0055918520906, "contentChunkCount": 16, "averageContentChunkCharacters": 4.5, "maxContentStallMs": 0.5742080000927672, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "shortest_path", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T08:46:29.786Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "A shortest path is A–B–C–D–G–H–I–J, with total weight 7 + 3 + 4 + 6 + 2 + 3 + 4 = 29.\n\nFINAL: 29", "evaluation": { "passed": true, "answer": "29", "expected": "29", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.011482936880698617, "classifierCostIndex": 0, "promptTokens": 157, "completionTokens": 299, "reasoningTokens": 242, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2143, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "157", "completionTokens": "299", "reasoningTokens": "242", "cachedTokens": "0" }, "timing": { "headersMs": 303.7210419999901, "firstEventMs": 612.8332090000622, "firstReasoningMs": null, "firstContentMs": 2251.9932920000283, "lastContentMs": 2417.3562920000404, "generationMs": 188.24366699997336, "totalMs": 2440.2369590000017, "visibleTokensPerSecond": 297.4867675097294, "contentChunkCount": 42, "averageContentChunkCharacters": 2.2857142857142856, "maxContentStallMs": 68.40737499995157, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "shortest_path", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T08:46:32.227Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 29 (A → B → C → D → G → H → I → J)", "evaluation": { "passed": false, "answer": "29(a→b→c→d→g→h→i→j)", "expected": "29", "detail": "29(a→b→c→d→g→h→i→j) != 29" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.3430994124167129, "classifierCostIndex": 0, "promptTokens": 157, "completionTokens": 70, "reasoningTokens": 43, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3188, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "157", "completionTokens": "70", "reasoningTokens": "43", "cachedTokens": "0" }, "timing": { "headersMs": 1343.8130420000525, "firstEventMs": 1679.7971670000115, "firstReasoningMs": null, "firstContentMs": 4250.575417000102, "lastContentMs": 4395.757125000004, "generationMs": 252.27308299997821, "totalMs": 4502.84850000008, "visibleTokensPerSecond": 103.06291773507301, "contentChunkCount": 21, "averageContentChunkCharacters": 1.9523809523809523, "maxContentStallMs": 95.54670800000895, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "shortest_path", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T08:46:36.732Z", "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": 0.11139991016035904, "classifierCostIndex": 0, "promptTokens": 157, "completionTokens": 133, "reasoningTokens": 123, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3200, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "157", "completionTokens": "133", "reasoningTokens": "123", "cachedTokens": "0" }, "timing": { "headersMs": 279.54054099996574, "firstEventMs": 559.0253329999978, "firstReasoningMs": 2352.567832999979, "firstContentMs": 3451.545790999895, "lastContentMs": 3451.549291000003, "generationMs": 30.18316700006835, "totalMs": 3481.7289579999633, "visibleTokensPerSecond": 298.1794455160924, "contentChunkCount": 4, "averageContentChunkCharacters": 2.25, "maxContentStallMs": 0.0013750001089647412, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "shortest_path", "category": "algorithms", "arm": "smart", "at": "2026-09-26T08:46:40.214Z", "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": 0.3398665219520798, "classifierCostIndex": 0.004866584453456307, "promptTokens": 198, "completionTokens": 455, "reasoningTokens": 446, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6909, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "198", "completionTokens": "455", "reasoningTokens": "446", "cachedTokens": "0" }, "timing": { "headersMs": 634.1188749999274, "firstEventMs": 1358.8194169999333, "firstReasoningMs": 3387.345624999958, "firstContentMs": 7696.476958999992, "lastContentMs": 7696.485458999989, "generationMs": 0.3796660000225529, "totalMs": 7696.856625000015, "visibleTokensPerSecond": 21071.152011306738, "contentChunkCount": 2, "averageContentChunkCharacters": 4.5, "maxContentStallMs": 0.00849999999627471, "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": 277, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-13", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:46:48.149Z", "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 \"description\": \"The land includes Battle Pass, a site associated with the 1776 Battle of Long Island during the American Revolution.\"\n },\n {\n \"period\": \"1850s–1860s\",\n \"description\": \"As Brooklyn grew, civic leaders sought a large public park. Landscape architects Frederick Law Olmsted and Calvert Vaux, who had designed Central Park, developed the plan for Prospect Park.\"\n },\n {\n \"period\": \"1866–1873\",\n \"description\": \"Construction began in 1866. The park opened to the public in 1867, while work continued into the early 1870s. Its design brought together the Long Meadow, wooded Ravine and lake to offer contrasting landscapes within the city.\"\n },\n {\n \"period\": \"20th century\",\n \"description\": \"Prospect Park gained facilities including its boathouse and zoo. Like many urban parks, it later suffered from deferred maintenance and deterioration.\"\n },\n {\n \"period\": \"1987–present\",\n \"description\": \"The Prospect Park Alliance was founded in 1987 to support restoration and care in partnership with NYC Parks. Projects have since restored landscapes and historic features and expanded recreational use.\"\n }\n ],\n \"significance\": \"Prospect Park remains one of Olmsted and Vaux’s best-known landscapes and a major public gathering place for Brooklyn.\"\n}", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.4825234787367882, "classifierCostIndex": 0, "promptTokens": 43, "completionTokens": 704, "reasoningTokens": 368, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6348, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "43", "completionTokens": "704", "reasoningTokens": "368", "cachedTokens": "0" }, "timing": { "headersMs": 578.531416999991, "firstEventMs": 886.2799170000944, "firstReasoningMs": null, "firstContentMs": 4983.014500000048, "lastContentMs": 6905.979250000091, "generationMs": 1936.0120830000378, "totalMs": 6919.026583000086, "visibleTokensPerSecond": 173.0361101263816, "contentChunkCount": 98, "averageContentChunkCharacters": 14.857142857142858, "maxContentStallMs": 200.51679199992213, "finalContentBurstRatio": 0.4059065934065934, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-13", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:46:55.068Z", "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 as a major public landscape for the growing city. Frederick Law Olmsted and Calvert Vaux shaped its naturalistic design, creating a park that combines meadows, woodland, water, and built features.\",\n \"timeline\": [\n {\n \"period\": \"Before the park\",\n \"details\": \"The area was home to the Lenape before European colonization. In 1776, during the Battle of Long Island, American troops fought British forces near what is now the park’s Battle Pass.\"\n },\n {\n \"period\": \"1850s–1860s: The park is planned\",\n \"details\": \"Brooklyn leaders and park advocates campaigned for a large public park. The New York State Legislature authorized its creation in 1859. Olmsted and Vaux, already known for their work on Central Park, submitted a design for Prospect Park in 1865.\"\n },\n {\n \"period\": \"1866–1873: Construction and opening\",\n \"details\": \"Construction began in 1866, and parts of the park opened to the public the following year. Work continued for several years, and the park was substantially completed in 1873. Its design included the Long Meadow, the Nethermead, the lake, and wooded areas intended to offer a respite from urban life.\"\n },\n {\n \"period\": \"Late 19th century–early 20th century\",\n \"details\": \"As Brooklyn grew, Prospect Park became an important place for recreation and civic life. Brooklyn became part of New York City in 1898. A menagerie opened in the park in 1890; the present Prospect Park Zoo opened in 1935.\"\n },\n {\n \"period\": \"Mid-20th century\",\n \"details\": \"Like many urban parks, Prospect Park faced years of wear and declining maintenance. Its landscapes and facilities deteriorated as public resources became strained.\"\n },\n {\n \"period\": \"1980s to today: Restoration\",\n \"details\": \"Renewed public investment and community involvement helped restore the park. The Prospect Park Alliance was founded in 1987 to work with the city on its care and improvement. Restoration projects have continued to renew its landscapes, facilities, and historic features.\"\n }\n ],\n \"lasting_significance\": \"Prospect Park remains one of Brooklyn’s largest and most valued green spaces. It is both a landmark of American landscape design and a place for recreation, community events, and contact with nature.\"\n}", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.030703057150663435, "classifierCostIndex": 0.004440979841926173, "promptTokens": 43, "completionTokens": 752, "reasoningTokens": 202, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5205, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "43", "completionTokens": "752", "reasoningTokens": "202", "cachedTokens": "0" }, "timing": { "headersMs": 621.716999999946, "firstEventMs": 825.3249999999534, "firstReasoningMs": null, "firstContentMs": 3696.2117500000168, "lastContentMs": 5770.483250000048, "generationMs": 2081.577500000014, "totalMs": 5777.789250000031, "visibleTokensPerSecond": 263.74228199526385, "contentChunkCount": 117, "averageContentChunkCharacters": 20.623931623931625, "maxContentStallMs": 185.61370800004806, "finalContentBurstRatio": 0.2565271446332366, "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": 190, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-13", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:47:00.850Z", "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 landscape architects Frederick Law Olmsted and Calvert Vaux, it opened in stages beginning in 1867. Its meadows, woodlands, waterways, and winding paths were intended to offer city residents a restorative landscape.\",\n \"timeline\": [\n {\n \"period\": \"Before the park\",\n \"details\": \"The area was part of the Lenape homeland before European colonization. Later, it became farmland on the outskirts of Brooklyn. During the American Revolutionary War, the Battle of Long Island was fought nearby in August 1776; Battle Pass, within what is now the park, was among the routes involved in the fighting.\"\n },\n {\n \"period\": \"1850s–1860s: Planning and design\",\n \"details\": \"As Brooklyn grew, civic leaders sought a large public park. Olmsted and Vaux, already known for their work on Central Park, developed a design for the site. Their plan was approved in 1866, emphasizing broad lawns, naturalistic scenery, and a wooded ravine.\"\n },\n {\n \"period\": \"1866–1873: Construction and opening\",\n \"details\": \"Construction began in 1866, and parts of the park opened to the public in 1867 while work continued. The park took shape around major features including the Long Meadow, the Nethermead, and the Ravine. It was substantially completed by 1873.\"\n },\n {\n \"period\": \"Late 19th and early 20th centuries\",\n \"details\": \"After Brooklyn became part of New York City in 1898, Prospect Park came under the city’s parks department. New facilities and changing uses were added over time. The modern Prospect Park Zoo opened in 1935.\"\n },\n {\n \"period\": \"1930s: Robert Moses era\",\n \"details\": \"Parks commissioner Robert Moses oversaw major improvements, including recreational facilities and renovations. These additions expanded the park’s amenities, though some changes altered aspects of Olmsted and Vaux’s original landscape.\"\n },\n {\n \"period\": \"Late 20th century to today\",\n \"details\": \"After years of decline, restoration efforts gained momentum. The Prospect Park Alliance was founded in 1987 to support the park in partnership with the city. Restoration work has renewed landscapes, historic structures, and natural areas.\"\n }\n ],\n \"historic_recognition\": \"Prospect Park is listed on the National Register of Historic Places and was designated a National Historic Landmark in 1980.\",\n \"legacy\": \"The park remains both a major public recreation space and an influential example of 19th-century landscape design.\"\n}", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.05072081403524418, "classifierCostIndex": 0, "promptTokens": 43, "completionTokens": 1461, "reasoningTokens": 868, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 9545, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "43", "completionTokens": "1461", "reasoningTokens": "868", "cachedTokens": "0" }, "timing": { "headersMs": 370.5524999999907, "firstEventMs": 623.1973340000259, "firstReasoningMs": 6617.481792000006, "firstContentMs": 8873.546542000026, "lastContentMs": 9884.591042000102, "generationMs": 1431.6017920000013, "totalMs": 10305.148334000027, "visibleTokensPerSecond": 413.5228129136063, "contentChunkCount": 121, "averageContentChunkCharacters": 21.776859504132233, "maxContentStallMs": 611.5628339999821, "finalContentBurstRatio": 0.9814041745730551, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-13", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:47:11.160Z", "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 roughly 585-acre public park in Brooklyn, New York City. Designed by Frederick Law Olmsted and Calvert Vaux, the landscape architects behind Central Park, it opened to the public in 1867 and became one of the defining public spaces of Brooklyn.\",\n \"timeline\": [\n {\n \"period\": \"Before the park\",\n \"history\": \"The area is part of the ancestral homeland of the Lenape. European colonization transformed much of the surrounding landscape into farmland. During the Battle of Brooklyn in August 1776, fighting took place in and around land that later became Prospect Park. Battle Pass, inside the park today, commemorates part of that Revolutionary War battlefield.\"\n },\n {\n \"period\": \"1850s–1861: Planning a park for Brooklyn\",\n \"history\": \"Brooklyn was still an independent city, and its rapid growth created demand for a large public park. Civic leaders, especially James S. T. Stranahan, championed the project. An early design by engineer Egbert Viele included Mount Prospect and land east of Flatbush Avenue.\"\n },\n {\n \"period\": \"1865–1866: Olmsted and Vaux reshape the plan\",\n \"history\": \"Calvert Vaux argued that Flatbush Avenue would divide the proposed park and undermine its pastoral atmosphere. He and Frederick Law Olmsted developed a revised design centered on land west of the avenue. Construction began in 1866, involving extensive grading, planting, and the creation of waterways.\"\n },\n {\n \"period\": \"1867–1873: Opening and development\",\n \"history\": \"The park opened to the public on October 19, 1867, although construction continued for several years. Its principal landscape was substantially completed by 1873. Major features included the Long Meadow, the wooded Ravine, and the Lake. Separate routes for pedestrians, horseback riders, and carriages helped preserve the experience of moving through a seemingly natural landscape.\"\n },\n {\n \"period\": \"Late 1800s–early 1900s: A civic and cultural landmark\",\n \"history\": \"The park became a popular place for strolling, boating, skating, concerts, and organized recreation. Its entrances and surroundings acquired major monuments, including the Soldiers’ and Sailors’ Memorial Arch at what is now Grand Army Plaza, dedicated in 1892. Brooklyn became part of New York City in 1898. The park’s Beaux-Arts Boathouse opened in 1905.\"\n },\n {\n \"period\": \"1930s–1960s: Expanded recreation\",\n \"history\": \"Under Parks Commissioner Robert Moses, the city added or rebuilt recreational facilities. The present Prospect Park Zoo opened in 1935, and the Bandshell opened in 1939. Playgrounds, athletic facilities, and the later Wollman skating rink reflected a growing emphasis on active recreation alongside the park’s original pastoral design.\"\n },\n {\n \"period\": \"1970s–1980s: Decline and preservation\",\n \"history\": \"New York City’s fiscal problems contributed to reduced maintenance, damaged landscapes, and deteriorating structures. Community advocates pushed for preservation and renewed investment. Prospect Park received New York City scenic landmark designation in 1975.\"\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 restoring and maintaining the park. Projects have rehabilitated woodlands, waterways, buildings, playgrounds, and historic landscapes. The LeFrak Center at Lakeside opened in 2013 as part of a major redevelopment that added modern skating facilities and restored portions of the lakeshore. The park became permanently car-free in January 2018.\"\n }\n ],\n \"why_it_matters\": \"Prospect Park is both a carefully engineered landscape and a democratic public space. Its meadows, woods, and water were designed to give residents relief from urban density. Today, it remains a major gathering place for Brooklyn’s diverse communities, balancing historic preservation, ecological restoration, sports, performances, and everyday recreation.\",\n \"sources_for_further_reading\": [\n {\n \"name\": \"Prospect Park Alliance\",\n \"url\": \"https://www.prospectpark.org/\"\n },\n {\n \"name\": \"NYC Parks: Prospect Park\",\n \"url\": \"https://www.nycgovparks.org/parks/prospect-park\"\n }\n ]\n}", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 3.7603276760478437, "classifierCostIndex": 0, "promptTokens": 43, "completionTokens": 1103, "reasoningTokens": 137, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 20693, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "43", "completionTokens": "1103", "reasoningTokens": "137", "cachedTokens": "0" }, "timing": { "headersMs": 4611.147166000097, "firstEventMs": 6241.029250000021, "firstReasoningMs": 10864.887333000079, "firstContentMs": 11913.81483300007, "lastContentMs": 25346.705833000015, "generationMs": 13433.057541999966, "totalMs": 25346.872375000035, "visibleTokensPerSecond": 71.83770314262549, "contentChunkCount": 204, "averageContentChunkCharacters": 21.475490196078432, "maxContentStallMs": 540.2857910000021, "finalContentBurstRatio": 0.17370463364528646, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-14", "category": "easy", "arm": "smart", "at": "2026-09-26T08:47:36.743Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005277307784863011, "classifierCostIndex": 0.004430427661475013, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1471, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 558.5077089999104, "firstEventMs": 863.2861669999547, "firstReasoningMs": null, "firstContentMs": 1922.421166999964, "lastContentMs": 1946.7687089999672, "generationMs": 110.97716699994635, "totalMs": 2033.3983339999104, "visibleTokensPerSecond": 63.0760379745807, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 24.34754200000316, "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": 190, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-14", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:47:38.777Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.043995151841277017, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1045, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 209.3384579999838, "firstEventMs": 464.375250000041, "firstReasoningMs": null, "firstContentMs": 1128.810832999996, "lastContentMs": 1128.8338330000406, "generationMs": 238.42554199998267, "totalMs": 1367.2363749999786, "visibleTokensPerSecond": 20.97090755486408, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.023000000044703484, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-14", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:47:40.144Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01965478893393377, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 22, "reasoningTokens": 14, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2063, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "22", "reasoningTokens": "14", "cachedTokens": "0" }, "timing": { "headersMs": 295.3181249999907, "firstEventMs": 482.49225000001024, "firstReasoningMs": 1546.6903340000426, "firstContentMs": 2268.9815420000814, "lastContentMs": 2268.983084000065, "generationMs": 30.406624999945052, "totalMs": 2299.3881670000264, "visibleTokensPerSecond": 230.21298812389242, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.001541999983601272, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-14", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:47:42.444Z", "model": "openai/gpt-6-luna", "loggedModel": "openai/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008468801233879989, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 955, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 201.43412499991246, "firstEventMs": 556.125415999908, "firstReasoningMs": null, "firstContentMs": 1069.079582999926, "lastContentMs": 1069.1392500000075, "generationMs": 91.83091700007208, "totalMs": 1160.9104999999981, "visibleTokensPerSecond": 76.22705107033295, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.05966700008139014, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "topological_orders", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T08:47:43.763Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Task I must be last. Among A–H, consider the first two tasks among A, B, C. Their shared successor becomes available, and can either occur before or after the third of A, B, C.\n\nIf it occurs after all three, there are 6 possible orders of A, B, C. The remaining tasks D, E, F, G, H have 20 valid orders: D and E must precede G, while F must precede H. This gives \\(6 \\cdot 20=120\\).\n\nIf it occurs between the first two and third of A, B, C:\n- For the pair AB, the available task is D; the remaining tasks have 6 valid orders. There are 2 orders of the pair: \\(2\\cdot6\\).\n- For AC, the available task is E; likewise \\(2\\cdot6\\).\n- For BC, the available task is F; the remaining tasks have 8 valid orders. There are 2 orders of the pair: \\(2\\cdot8\\).\n\nThus the total is \\(120+12+12+16=160\\).\n\nFINAL: 160 valid total task orders.", "evaluation": { "passed": false, "answer": "160validtotaltaskorders.", "expected": "164", "detail": "160validtotaltaskorders. != 164" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.04505104630821685, "classifierCostIndex": 0, "promptTokens": 97, "completionTokens": 1285, "reasoningTokens": 1034, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10454, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "97", "completionTokens": "1285", "reasoningTokens": "1034", "cachedTokens": "0" }, "timing": { "headersMs": 205.63241600000765, "firstEventMs": 1388.2408330000471, "firstReasoningMs": 3797.016082999995, "firstContentMs": 10484.62591599999, "lastContentMs": 10635.960208000033, "generationMs": 177.58800000010524, "totalMs": 10662.213916000095, "visibleTokensPerSecond": 1407.75277608764, "contentChunkCount": 88, "averageContentChunkCharacters": 9.386363636363637, "maxContentStallMs": 140.01974999997765, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "topological_orders", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T08:47:54.426Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "FINAL: 142", "evaluation": { "passed": false, "answer": "142", "expected": "164", "detail": "142 != 164" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.6679421998092706, "classifierCostIndex": 0, "promptTokens": 97, "completionTokens": 967, "reasoningTokens": 957, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10967, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "97", "completionTokens": "967", "reasoningTokens": "957", "cachedTokens": "0" }, "timing": { "headersMs": 254.22841700003482, "firstEventMs": 547.3727090000175, "firstReasoningMs": null, "firstContentMs": 9261.75549999997, "lastContentMs": 9280.939624999999, "generationMs": 1962.124334000051, "totalMs": 11223.879834000021, "visibleTokensPerSecond": 4.586865288833305, "contentChunkCount": 4, "averageContentChunkCharacters": 2.5, "maxContentStallMs": 19.135332999983802, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "topological_orders", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T08:48:05.650Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "**I must be last**, since every other task precedes it directly or indirectly. Thus we count valid orders of A–H.\n\nFirst consider only A–F. Call A, B, C “lower” tasks and D, E, F “upper” tasks. Each upper task requires a distinct pair of lower tasks. There are only two possible patterns:\n\n- **LLLUUU:** All three lower tasks come first, giving \\(3!\\cdot3!=36\\) orders.\n- **LLULUU:** The first two lower tasks unlock exactly one upper task. After that upper task, the remaining lower task must come next. This gives \\(3\\cdot2\\cdot2=12\\) orders.\n\nBy symmetry, F is first, second, or third among the upper tasks equally often: 12 times each in the first pattern and 4 times each in the second.\n\nNow insert G after both D and E, and H after F:\n\n| A–F pattern | F first | F second | F third |\n|---|---:|---:|---:|\n| LLLUUU | 4 insertions | 3 insertions | 3 insertions |\n| LLULUU | 5 insertions | 3 insertions | 3 insertions |\n\nFor example, when F is first, G must follow the final base task. H can occupy any gap after F but before that final task, or G and H can both follow it in either order. This gives 4 or 5 insertions, respectively. In the other cases, one inserted task must follow the final base task and the other must follow the penultimate one, giving 3 possibilities.\n\nTherefore the total is\n\\[\n12(4+3+3)+4(5+3+3)=120+44=164.\n\\]\n\nFINAL: 164", "evaluation": { "passed": true, "answer": "164", "expected": "164", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 3.807039337933471, "classifierCostIndex": 0, "promptTokens": 97, "completionTokens": 1106, "reasoningTokens": 719, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 21068, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "97", "completionTokens": "1106", "reasoningTokens": "719", "cachedTokens": "0" }, "timing": { "headersMs": 268.8988750000717, "firstEventMs": 558.2339589999756, "firstReasoningMs": 6535.8911670000525, "firstContentMs": 16708.45433400001, "lastContentMs": 21332.517500000075, "generationMs": 4797.391958000022, "totalMs": 21505.84629200003, "visibleTokensPerSecond": 80.46038417943215, "contentChunkCount": 111, "averageContentChunkCharacters": 12.153153153153154, "maxContentStallMs": 492.18554099998437, "finalContentBurstRatio": 0.43736100815418827, "buffered": false }, "error": null, "routing": null }, { "caseId": "topological_orders", "category": "algorithms", "arm": "smart", "at": "2026-09-26T08:48:27.157Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "", "evaluation": { "passed": false, "answer": "", "expected": "164", "detail": "no answer != 164" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 2.7944660361296925, "classifierCostIndex": 0.0046203669095958985, "promptTokens": 121, "completionTokens": 4096, "reasoningTokens": 4096, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 47744, "loggedFinishReason": "max_tokens", "billedUsage": { "promptTokens": "121", "completionTokens": "4096", "reasoningTokens": "4096", "cachedTokens": "0" }, "timing": { "headersMs": 1461.1082080000779, "firstEventMs": 2799.541124999989, "firstReasoningMs": 4872.935166000039, "firstContentMs": null, "lastContentMs": null, "generationMs": null, "totalMs": 49215.918125000084, "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": 257, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3697", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:49:18.952Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# <>\n\n---\n\n## Slide 1: Title\n**ReachMail**\n*Turning Neighborhoods into Networks*\n\nSend physical letters to anyone in your territory — no address book required.\n\n---\n\n## Slide 2: The Problem\n- Local businesses, campaigns, and community organizers want to reach people nearby but **don't have their contact information**\n- Digital ads are noisy, expensive, and easily ignored\n- Direct mail works but requires **expensive mailing lists** or **door-to-door legwork**\n- No easy way to say \"I want to reach everyone within 2 miles of my shop\" without hiring a marketing agency\n\n---\n\n## Slide 3: The Solution\n**ReachMail** lets anyone select a geographic area on a map and send personalized physical letters to every address inside it — no names, no personal data needed, just **location-based outreach**.\n\n- Draw your territory on an interactive map\n- Write or upload your letter\n- We print, stamp, and mail it to every household/business in that zone\n\n---\n\n## Slide 4: How It Works\n1. **Select Territory** — draw a radius, zip code, or custom boundary\n2. **Compose Letter** — use templates or upload your own design\n3. **Preview & Approve** — see estimated reach and cost\n4. **We Print & Mail** — partnered with USPS/regional carriers for delivery\n5. **Track Results** — optional QR codes/promo codes for response tracking\n\n---\n\n## Slide 5: Who It's For\n- 🏪 **Local businesses** — new shop openings, promotions\n- 🏡 **Real estate agents** — farming a neighborhood\n- 🗳️ **Political campaigns & community organizers**\n- 🎉 **Event promoters** — invite the neighborhood\n- ❤️ **Individuals** — reconnect with a community, send goodwill letters\n\n---\n\n## Slide 6: Market Opportunity\n- Direct mail industry: **$40B+ annually** in the US\n- Hyperlocal marketing spend growing as digital ad costs rise and privacy regulations tighten (cookie deprecation, iOS tracking limits)\n- Untapped niche: **individuals & small businesses without CRM/mailing lists**\n\n---\n\n## Slide 7: Business Model\n- **Pay-per-letter** pricing (volume discounts)\n- **Subscription tiers** for recurring campaigns (real estate agents, businesses)\n- **Premium features**: variable data printing, tracking analytics, A/B testing letters\n- **Enterprise API** for agencies/campaigns managing many territories\n\n---\n\n## Slide 8: Competitive Landscape\n| | Mailchimp | EDDM (USPS) | ReachMail |\n|---|---|---|---|\n| No address list needed | ❌ | ✅ | ✅ |\n| Physical mail | ❌ | ✅ | ✅ |\n| Easy UI for individuals | ✅ | ❌ | ✅ |\n| Personalization tools | ✅ | ❌ | ✅ |\n| Analytics/tracking | ✅ | ❌ | ✅ |\n\n**Our edge:** Combining USPS's Every Door Direct Mail infrastructure with a modern, user-friendly interface and tracking tools.\n\n---\n\n## Slide 9: Traction / Roadmap\n- ✅ MVP with map-based territory selection\n- ✅ Partnership discussions with regional print/mail fulfillment centers\n- 🔜 Pilot with 20 local businesses in [City]\n- 🔜 Launch self-serve web app (Q_ 2025)\n- 🔜 Mobile app + API for enterprise clients\n\n---\n\n## Slide 10: Team\n- **[Founder Name]** — Background in logistics/direct mail operations\n- **[Co-founder Name]** — Product & engineering, prior startup experience\n- **[Advisor]** — USPS/direct mail industry veteran\n\n---\n\n## Slide 11: The Ask\nRaising **$750K seed round** to:\n- Build out fulfillment partnerships & printing infrastructure\n- Launch self-serve platform publicly\n- Grow initial customer base across 3 pilot cities\n\n---\n\n## Slide 12: Vision\n*Every neighborhood is a network waiting to be reached. ReachMail makes it as easy to mail your block as it is to post on social media.*", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.9948360334559316, "classifierCostIndex": 0.004472636383279654, "promptTokens": 73, "completionTokens": 1448, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 17037, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "73", "completionTokens": "1448", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 715.9646669999929, "firstEventMs": 1843.1732090000296, "firstReasoningMs": null, "firstContentMs": 1843.1912500000326, "lastContentMs": 17710.85858400003, "generationMs": 15885.765625, "totalMs": 17728.956875000033, "visibleTokensPerSecond": 91.08783511968754, "contentChunkCount": 354, "averageContentChunkCharacters": 10.152542372881356, "maxContentStallMs": 705.6172500000102, "finalContentBurstRatio": 0.10573177518085698, "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": 153, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-3697", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:49:36.682Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "# <>\n\n## Slide 1 — The Big Idea\n**Personalized direct mail for businesses that grow territory by territory.**\n\nTerritoryPost helps businesses introduce themselves to prospective customers they don’t know personally—by sending relevant, professional letters to addresses within a defined service area.\n\n**Choose your territory. Create your message. We handle the mail.**\n\n---\n\n## Slide 2 — The Problem\n### Local prospecting is harder than it should be.\n\nBusinesses need to reach nearby customers, but existing options have drawbacks:\n\n- Digital ads are crowded and don’t always reach the right neighborhoods.\n- Cold email requires contact information and competes with overflowing inboxes.\n- Door-to-door outreach is time-intensive.\n- Traditional direct mail involves disconnected vendors, spreadsheets, and manual work.\n\n**The missing tool:** A simple way to go from “this is my territory” to “my introduction is in their mailbox.”\n\n---\n\n## Slide 3 — The Solution\n### A self-serve platform for territory-based letter campaigns.\n\nWith TerritoryPost, users can:\n\n- Draw a territory on a map or select ZIP codes.\n- Find eligible residential or business mailing addresses.\n- Create letters using templates and optional AI-assisted drafting.\n- Personalize messaging with appropriate, verified information.\n- Approve pricing, printing, and postage in one workflow.\n- Track responses through campaign-specific links, QR codes, and phone numbers.\n\n**No personal relationship or existing contact list required.**\n\n---\n\n## Slide 4 — The Customer\n### Built for businesses where geography drives growth.\n\n**Initial beachhead: Home-service businesses**\n- HVAC companies\n- Landscapers\n- Roofers\n- Cleaning companies\n- Pest-control providers\n\nThese businesses have clear service boundaries and recurring reasons to introduce themselves to nearby households.\n\n**Expansion opportunities:** Local retailers, business-service providers, franchise operators, and field-sales teams.\n\n---\n\n## Slide 5 — The Product Experience\n### From map to mailbox in five steps.\n\n1. **Define:** Select a service territory.\n2. **Target:** Choose relevant address types and remove duplicates, existing customers, and suppressed addresses.\n3. **Create:** Draft a letter with a clear introduction, offer, and call to action.\n4. **Approve:** Review the audience, letter, budget, and mailing schedule.\n5. **Measure:** Monitor attributed inquiries and compare campaign performance.\n\n**Example:** A landscaping company introduces its seasonal maintenance service to households within its operating radius.\n\n---\n\n## Slide 6 — Why Customers Pay\n### Less administration. More consistent outreach.\n\nTerritoryPost replaces the work of coordinating address sourcing, list preparation, design, printing, and fulfillment.\n\n**Customer value**\n- Launch campaigns without direct-mail expertise.\n- Avoid mailing outside the service area.\n- Maintain consistent branding across territories.\n- Test messages with small campaigns before expanding.\n- Learn which campaigns generate qualified inquiries.\n\n**Core success metric:** Cost per qualified inquiry—not letters sent.\n\n---\n\n## Slide 7 — Business Model\n### Subscription software + usage-based fulfillment.\n\n**Proposed revenue streams**\n- **Subscription:** Territory management, templates, reporting, and integrations.\n- **Per-letter charge:** Printing, postage, fulfillment, and platform margin.\n- **Team plans:** Multiple users, territories, approval workflows, and consolidated billing.\n\n**Pricing approach:** Display the full campaign cost before approval.\n\n**Unit-economics focus:** Positive contribution margin per campaign, with repeat usage covering acquisition and support costs.\n\n---\n\n## Slide 8 — Go-to-Market\n### Win one customer segment in a few local markets first.\n\n**Phase 1: Validate**\n- Recruit home-service businesses as design partners.\n- Run paid pilot campaigns.\n- Measure setup time, attributed inquiries, repeat purchases, and margins.\n\n**Phase 2: Build repeatability**\n- Develop seasonal campaign templates.\n- Partner with local marketing agencies and industry consultants.\n- Publish customer-approved case studies with measured results.\n\n**Phase 3: Expand**\n- Add CRM integrations.\n- Offer multi-location and franchise plans.\n- Enter adjacent customer segments.\n\n---\n\n## Slide 9 — Differentiation and Trust\n### More useful than a mailing vendor. Simpler than an enterprise marketing suite.\n\n**Our differentiation**\n- Territory-first planning\n- End-to-end campaign execution\n- Vertical-specific workflows\n- Response measurement and CRM feedback\n- Built-in suppression and contact-frequency controls\n\n**Trust by design**\n- Use documented address-data sources permitted for the intended use.\n- Clearly identify the sender.\n- Never imply a personal relationship that doesn’t exist.\n- Avoid sensitive personal profiling.\n- Provide an easy way to request no further mail and honor those requests.\n- Review applicable privacy, advertising, and postal requirements in each market.\n\n**Long-term advantage:** Workflow integration, fulfillment reliability, and permissioned campaign-performance insights.\n\n---\n\n## Slide 10 — The Ask\n### Fund the path from paid pilots to repeatable growth.\n\n**Seeking:** [Funding amount] for [runway period].\n\n**Use of funds**\n- Build the map-to-mail MVP.\n- Integrate address validation and fulfillment partners.\n- Establish privacy, suppression, and quality-control systems.\n- Acquire and support the first paying customers.\n- Validate retention and campaign economics.\n\n**Milestones**\n- [X] paying businesses\n- [Y]% repeat-campaign rate\n- Positive campaign contribution margin\n- Documented customer acquisition economics\n- Reliable fulfillment at increasing volume\n\n**TerritoryPost makes the first introduction easier—one neighborhood at a time.**\n\n*Funding, pricing, and traction figures are placeholders to validate, not claimed results.*", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 4.002539449867753, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 1173, "reasoningTokens": 38, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 21295, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "1173", "reasoningTokens": "38", "cachedTokens": "0" }, "timing": { "headersMs": 394.5784160000039, "firstEventMs": 702.3665000000037, "firstReasoningMs": 2500.5373749999562, "firstContentMs": 3447.7045830000425, "lastContentMs": 21669.38245799998, "generationMs": 18221.84941699996, "totalMs": 21669.554000000004, "visibleTokensPerSecond": 62.23298053061736, "contentChunkCount": 245, "averageContentChunkCharacters": 24.253061224489795, "maxContentStallMs": 418.5983750000596, "finalContentBurstRatio": 0.10552002692696062, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3697", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:49:58.353Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "# <>\n\n### 1. The idea\n**Reach people in your territory with a real letter—even if you’ve never met.**\n\nTerritory Letter helps local businesses and community organizations turn a defined area into a thoughtful, compliant direct-mail campaign.\n\n### 2. The problem\n- You know *where* you want to build relationships, but not *who* lives there.\n- Buying lists, designing mail, printing, and posting letters takes too much work.\n- Generic flyers are easy to ignore; overly personal messages feel intrusive.\n\n### 3. The solution\nChoose a territory, write a letter, and send it. We handle eligible address sourcing, printing, postage, delivery tracking, and suppression of opt-outs—all in one place.\n\n### 4. How it works\n1. **Draw your territory** on a map.\n2. **Choose a campaign** and estimated mailing volume.\n3. **Write your letter** using clear, honest templates.\n4. **Review and send** after a final cost and compliance check.\n5. **Measure response** with optional QR codes, landing pages, or offer codes.\n\n### 5. Who it’s for\n- Local businesses introducing themselves to nearby households\n- Real-estate professionals serving a defined area\n- Community groups inviting neighbors to events or services\n- Field teams building awareness in an assigned territory\n\n### 6. Why it wins\n**The simplicity of email, the presence of physical mail.** Territory Letter combines map-based targeting, easy letter creation, and fulfillment in a single workflow—without requiring users to acquire or handle a list of strangers’ personal details.\n\n### 7. Business model\nA per-letter price covers printing, postage, and fulfillment, with a platform margin. Subscription plans add saved territories, team approvals, recurring campaigns, and reporting.\n\n### 8. Go-to-market\nStart with professionals who already spend on local outreach. Partner with local-business associations and industry software providers; grow through templates that help new customers launch a first campaign quickly.\n\n### 9. Trust by design\nUse lawfully sourced mailing data, limit unnecessary personalization, honor applicable opt-outs and mailing rules, and prohibit deceptive claims of a personal relationship. Senders approve every campaign before it mails.\n\n### 10. The ask\nLaunch a pilot in select territories to validate three things: **time to first mailing, repeat campaign rate, and cost per qualified response.** Use those results to refine pricing and expand fulfillment coverage.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5134034878365558, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 748, "reasoningTokens": 239, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7464, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "748", "reasoningTokens": "239", "cachedTokens": "0" }, "timing": { "headersMs": 353.124332999927, "firstEventMs": 669.1114169999491, "firstReasoningMs": null, "firstContentMs": 3866.764291999978, "lastContentMs": 7860.167082999949, "generationMs": 3993.817458000034, "totalMs": 7860.581750000012, "visibleTokensPerSecond": 127.19659957978871, "contentChunkCount": 119, "averageContentChunkCharacters": 20.680672268907564, "maxContentStallMs": 241.53591600002255, "finalContentBurstRatio": 0.18325883787078423, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3697", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:50:06.215Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "# <>\n\n### Slide 1 — The opportunity\n**A better way to introduce yourself to the people in your territory.**\n\nTerritoryLetter helps local businesses and organizations send thoughtful, relevant letters to people they don’t know personally—without needing a personal contact list.\n\n---\n\n### Slide 2 — The problem\n**Territory outreach is either impersonal or hard to manage.**\n\n- Cold email and digital ads are crowded and easy to ignore.\n- Generic bulk mail can feel irrelevant and wasteful.\n- Finding addresses, preparing letters, and coordinating printing and postage takes time.\n- Teams lack a simple way to measure what their mail is generating.\n\n---\n\n### Slide 3 — The solution\n**Turn a map into a well-run letter campaign.**\n\nTerritoryLetter lets a team:\n\n1. Define a geographic area.\n2. Select an appropriate audience using authorized, non-sensitive criteria.\n3. Create a useful, personalized letter.\n4. Review, print, and mail it through integrated fulfillment.\n5. Track delivery, responses, and follow-up.\n\n**The goal:** make a first introduction feel considered—not creepy.\n\n---\n\n### Slide 4 — How it works\n**From territory to mailbox in minutes.**\n\n- **Map:** Choose neighborhoods, postal zones, or an uploaded territory.\n- **Plan:** Set campaign purpose, audience, budget, and mailing volume.\n- **Write:** Use guided templates and AI-assisted drafts, with human approval.\n- **Send:** Print and mail through vetted fulfillment partners.\n- **Learn:** Track campaign status and responses through unique URLs, QR codes, or reply channels.\n\n---\n\n### Slide 5 — Who it serves\n**For teams whose customers or constituents are nearby.**\n\nInitial customer segments:\n\n- Home-service businesses and independent professionals\n- Real estate and property services\n- Local retailers and hospitality businesses\n- Community organizations and nonprofits\n- B2B teams with defined geographic sales territories\n\n**Initial wedge:** small and midsize service businesses that need local awareness but lack dedicated marketing operations.\n\n---\n\n### Slide 6 — Why now\n**Physical mail can stand out when digital channels are saturated.**\n\n- Local businesses need practical ways to reach nearby prospects.\n- Print and postal fulfillment can now be coordinated through software.\n- Modern automation makes small, targeted campaigns easier to create and manage.\n- Teams increasingly want measurable outreach—not just another channel to maintain.\n\n---\n\n### Slide 7 — Business model\n**Software subscription plus campaign usage.**\n\n- Monthly plans for territory management, templates, collaboration, and reporting\n- Per-piece pricing for printing and postage, with a transparent platform fee\n- Premium features for multi-location teams, integrations, and advanced analytics\n\n**Illustrative unit economics:** At an assumed $1.25 platform contribution per mailed piece, a 1,000-piece campaign contributes $1,250 before acquisition, support, and overhead. Actual margins will depend on print, postage, and fulfillment costs.\n\n---\n\n### Slide 8 — Go-to-market\n**Start local, prove repeat value, then expand.**\n\n1. Recruit design partners in a few service-business categories.\n2. Offer guided first campaigns and simple response tracking.\n3. Build referral partnerships with print shops, local agencies, and business associations.\n4. Expand from single campaigns to recurring territory programs.\n5. Add multi-location and team features as customers grow.\n\n**Core growth loop:** successful campaign → repeat mailing → referrals to nearby businesses.\n\n---\n\n### Slide 9 — Trust is part of the product\n**Reach people respectfully and responsibly.**\n\n- Use only lawful, properly licensed address sources or customer-provided lists.\n- Exclude sensitive personal characteristics from targeting.\n- Provide clear sender identity and a straightforward way to stop future mail.\n- Keep audience selection, approvals, and campaign history auditable.\n- Follow applicable postal, privacy, marketing, and consumer-protection rules.\n\n---\n\n### Slide 10 — The ask\n**Help us make local outreach more human—and more measurable.**\n\nWe’re seeking early customers and launch partners to validate:\n\n- Which local categories have the strongest repeat need\n- Which campaign types produce meaningful responses\n- What level of personalization feels useful and appropriate\n- The economics of recurring, territory-based mail\n\n**TerritoryLetter:** a thoughtful first hello, delivered.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.03963764245240682, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 1138, "reasoningTokens": 269, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7560, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "1138", "reasoningTokens": "269", "cachedTokens": "0" }, "timing": { "headersMs": 367.47912499995437, "firstEventMs": 720.2452909999993, "firstReasoningMs": 3145.90708299994, "firstContentMs": 6245.680082999985, "lastContentMs": 7890.507957999944, "generationMs": 1685.8916250000475, "totalMs": 7931.571708000032, "visibleTokensPerSecond": 514.8610901961006, "contentChunkCount": 140, "averageContentChunkCharacters": 31.685714285714287, "maxContentStallMs": 382.7644590000855, "finalContentBurstRatio": 0.10459873760144274, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2164", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:50:14.402Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Meet **the squeaker**, a playful new line of latex dog toys designed for dogs of all ages and species. Available in a variety of colors and shapes, there’s a squeaker to suit every pup’s personality. Pick a [color] [shape] for [dog’s name], and find their new favorite toy at [store name].", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2008695483715469, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 281, "reasoningTokens": 206, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3856, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "281", "reasoningTokens": "206", "cachedTokens": "0" }, "timing": { "headersMs": 286.37791599996854, "firstEventMs": 744.2941250000149, "firstReasoningMs": 3021.497875000001, "firstContentMs": 4068.3063750000438, "lastContentMs": 4138.300333000021, "generationMs": 213.1639580000192, "totalMs": 4281.470333000063, "visibleTokensPerSecond": 347.1506191491966, "contentChunkCount": 50, "averageContentChunkCharacters": 5.78, "maxContentStallMs": 65.46295900002588, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2164", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:50:18.684Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "## Meet the squeaker\n**Big squeaks. Tail-wagging fun.**\n\nBring fresh excitement to playtime with **the squeaker**, a new line of latex dog toys designed for dogs of all ages and breeds. Available in a variety of colors and shapes, these playful toys make it easy to find a match for your pup’s personality.\n\nFrom curious puppies to playful seniors, there’s a little squeaky fun for every stage of life.\n\n- **Latex construction** for a flexible feel\n- **A playful squeak** to spark curiosity\n- **A variety of colors and shapes** to mix up the toy basket\n\nFind your dog’s next favorite at [store name], explore the collection at [website], or call [phone number] to learn more.\n\n*Choose a toy appropriate for your dog’s size and chewing habits. Supervise play and replace the toy if damaged.*", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6786289882033658, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 185, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4435, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "185", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 410.8721249999944, "firstEventMs": 991.2127499999478, "firstReasoningMs": null, "firstContentMs": 1904.0318330000155, "lastContentMs": 4843.084333000006, "generationMs": 2956.901124999975, "totalMs": 4860.93295799999, "visibleTokensPerSecond": 62.227309004118815, "contentChunkCount": 82, "averageContentChunkCharacters": 9.634146341463415, "maxContentStallMs": 434.58608300006017, "finalContentBurstRatio": 0.20506329113924052, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2164", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:50:23.546Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Meet **the squeaker**, a playful new line of latex dog toys made for dogs of all ages and sizes. Available in a variety of bright colors and fun shapes, there’s a favorite for every kind of play session. Choose your pup’s perfect match at [store name], or contact us at [phone number] to learn more. Find us at [address].", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.00784229934068353, "classifierCostIndex": 0.004571123400823817, "promptTokens": 78, "completionTokens": 78, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1642, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "78", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 9750.382707999903, "firstEventMs": 10363.878416999942, "firstReasoningMs": null, "firstContentMs": 11287.773624999914, "lastContentMs": 11312.467957999907, "generationMs": 526.6751670000376, "totalMs": 11814.448791999952, "visibleTokensPerSecond": 146.20017199328956, "contentChunkCount": 52, "averageContentChunkCharacters": 6.173076923076923, "maxContentStallMs": 12.197249999968335, "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": 928, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2164", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:50:35.361Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Meet **The Squeaker**—a playful new line of latex dog toys made for dogs of all ages and breeds. Each toy brings squeaky fun to playtime, with a variety of bright colors and engaging shapes to choose from. Pick a favorite for your pup or find a new surprise for every play session.\n\nExplore the collection at [website], available for [price]. Questions? Contact [name] at [phone number].\n\nAlways supervise your dog during 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": 0.00965321584734036, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 263, "reasoningTokens": 158, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3159, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "263", "reasoningTokens": "158", "cachedTokens": "0" }, "timing": { "headersMs": 1110.4155000000028, "firstEventMs": 1416.171667000046, "firstReasoningMs": 3225.340499999933, "firstContentMs": 4083.484625000041, "lastContentMs": 4166.048749999958, "generationMs": 85.47145799989812, "totalMs": 4168.956082999939, "visibleTokensPerSecond": 1216.780460210752, "contentChunkCount": 60, "averageContentChunkCharacters": 7.583333333333333, "maxContentStallMs": 77.84454099996947, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1203", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:50:39.818Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "The **Tang dynasty ruled China from 618 to 907 CE**. It was an age of cultural brilliance, expanding trade, and powerful government, but also of rebellion and political breakdown. Here are its major developments:\n\n1. **China was reunited under a new dynasty.** After the Sui dynasty collapsed amid rebellion and civil **war**, Li Yuan founded the Tang in 618. Early Tang rulers defeated rivals and restored enough **peace** to rebuild government and agriculture.\n\n2. **The empire expanded.** Emperor Taizong, who ruled from 626 to 649, strengthened the state and defeated the Eastern Turks. Tang armies extended Chinese influence into Central Asia through **war**, while diplomacy and alliances helped maintain **peace** along some frontiers.\n\n3. **Chang’an became a global capital.** Merchants, diplomats, monks, and students traveled to this enormous city. Although **war** sometimes disrupted Silk Road routes, periods of **peace** supported exchanges with Central Asia, Persia, India, and other regions.\n\n4. **Government became more sophisticated.** The Tang developed administrative institutions and expanded the use of civil-service examinations, though aristocratic families remained influential. Officials managed taxation, justice, and resources for **war**, while effective administration helped preserve domestic **peace**.\n\n5. **Poetry and the arts flourished.** Poets such as Li Bai, Du Fu, and Wang Wei created enduring masterpieces. Painting, calligraphy, ceramics, and music also thrived. Courtly prosperity and stretches of **peace** supported artistic patronage, although many works also reflected suffering and instability.\n\n6. **Religious life was diverse—and sometimes contested.** Buddhism flourished alongside Daoism and Confucian traditions, while foreign communities practiced other religions. Religious coexistence contributed to social **peace**, but tolerance varied. In 845, Emperor Wuzong suppressed Buddhism, largely for religious and economic reasons rather than as a campaign of **war**.\n\n7. **Wu Zetian became emperor.** After gaining power at court, she ruled in her own name from 690 to 705, briefly replacing the Tang with her Zhou dynasty. Her reign combined administrative achievements and relative internal **peace** with political repression and frontier **war**.\n\n8. **The An Lushan Rebellion devastated the empire.** Beginning in 755, this rebellion plunged northern China into **war** and caused immense destruction and displacement. Although the rebellion ended in 763, restored **peace** did not bring back the central government’s former strength.\n\n9. **The economy changed.** Southern China became increasingly important for rice production, commerce, and taxation. Waterways and maritime trade supported growth. Even when nationwide **peace** was fragile, some regions experienced considerable prosperity.\n\n10. **The dynasty fragmented and fell.** Powerful military governors, court struggles, and rebellions—including Huang Chao’s uprising—undermined imperial authority. Renewed **war** shattered hopes of lasting **peace**. In 907, the military leader Zhu Wen ended the Tang, beginning the Five Dynasties and Ten Kingdoms period.\n\n**The Tang’s lasting legacy** includes celebrated literature, influential political institutions, and extensive cultural connections across Asia.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 3.0485885159916672, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 893, "reasoningTokens": 237, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 18188, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "893", "reasoningTokens": "237", "cachedTokens": "0" }, "timing": { "headersMs": 210.70362499996554, "firstEventMs": 543.793166999938, "firstReasoningMs": null, "firstContentMs": 7614.1704579999205, "lastContentMs": 18393.839874999947, "generationMs": 10788.031625000061, "totalMs": 18402.202082999982, "visibleTokensPerSecond": 60.71543194980171, "contentChunkCount": 168, "averageContentChunkCharacters": 19.803571428571427, "maxContentStallMs": 226.97812500002328, "finalContentBurstRatio": 0.1689209498046288, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1203", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:50:58.222Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "The Tang dynasty ruled China from 618 to 907 CE. After years of war, its rulers strengthened the central government, expanded China’s influence, and encouraged trade along the Silk Roads. Peace helped Chang’an become a cosmopolitan capital. During periods of peace, poetry, painting, and Buddhism flourished; poets Li Bai and Du Fu remain famous today.\n\nTang history, however, alternated between war and peace. War on the frontiers extended Tang influence into Central Asia, while war with neighboring powers strained its resources. Peace supported merchants, peace fostered cultural exchange with Korea and Japan, and peace brought prosperity to many cities.\n\nThe An Lushan rebellion of 755–763 plunged the empire into war, caused immense destruction, and weakened central authority. Later, war among regional commanders repeatedly disrupted peace. Further war and rebellions made peace harder to sustain. Although some areas regained peace, lasting peace remained elusive. By 907, political fragmentation and war had ended the dynasty.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.44162566242665624, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 644, "reasoningTokens": 441, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6525, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "644", "reasoningTokens": "441", "cachedTokens": "0" }, "timing": { "headersMs": 277.6859580000164, "firstEventMs": 639.4417919999687, "firstReasoningMs": null, "firstContentMs": 5221.6092499999795, "lastContentMs": 6772.745750000002, "generationMs": 1585.418042000034, "totalMs": 6807.027292000013, "visibleTokensPerSecond": 127.41119039188762, "contentChunkCount": 82, "averageContentChunkCharacters": 12.646341463414634, "maxContentStallMs": 246.79200000001583, "finalContentBurstRatio": 0.25458052073288334, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1203", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:51:05.030Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "The Tang dynasty ruled China from **618 to 907**. It is often remembered as a high point in Chinese history, known for strong government, flourishing trade and remarkable achievements in poetry, art and technology. Its fortunes, however, shifted between periods of **peace** and **war**.\n\n- **Early expansion:** Tang rulers reunited much of China after a period of division. Strong administration and relative **peace** helped farming, cities and trade prosper. But expansion also brought **war**: Tang armies fought to secure territory and influence in Central Asia and along the Silk Road.\n- **Culture and commerce:** During more stable years, **peace** encouraged merchants, travelers and ideas to move across Asia. The capital, Chang’an, became a major cosmopolitan city. Buddhism spread widely, while Tang poetry and art flourished.\n- **Rebellion and unrest:** In 755, the An Lushan Rebellion began. This devastating **war**—a major **civil war**—lasted until 763, caused enormous loss of life and weakened the dynasty. The **peace** that followed was fragile: regional military governors gained power, and further fighting broke out.\n- **Decline:** Later rebellions, court struggles and conflicts with neighboring powers further eroded Tang authority. The dynasty could not restore lasting **peace**, and in 907 it fell, ushering in another era of division.\n\nIn short, Tang China achieved long stretches of stability and cultural brilliance, but its history was repeatedly shaped by **war** as well as efforts to secure **peace**.", "evaluation": { "passed": false, "answer": "00", "expected": "all instructions followed", "detail": "Failed: keywords:frequency, keywords:frequency", "score": 0, "metrics": { "instructionsPassed": 0, "instructionsTotal": 2 } }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.029179484634753595, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 837, "reasoningTokens": 516, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7475, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "837", "reasoningTokens": "516", "cachedTokens": "0" }, "timing": { "headersMs": 421.39824999996927, "firstEventMs": 682.5821249999572, "firstReasoningMs": 3905.5756670000264, "firstContentMs": 7918.190209000022, "lastContentMs": 7938.065834000008, "generationMs": 360.9601659999462, "totalMs": 8279.150374999968, "visibleTokensPerSecond": 886.5244149961071, "contentChunkCount": 97, "averageContentChunkCharacters": 15.835051546391753, "maxContentStallMs": 11.759332999936305, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1203", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:51:13.310Z", "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) was a period marked by cycles of war followed by long stretches of peace, creating one of China's most celebrated golden ages. Understanding this era requires examining both the war campaigns that established Tang power and the peace that allowed civilization to flourish.\n\n## The War for Establishment\n\nThe Tang dynasty emerged from war. Li Yuan and his son Li Shimin waged war against the crumbling Sui dynasty, using military conflict to seize control. This early war was necessary before peace could be established. Once the war ended in Tang victory, Emperor Taizong worked to transform war-torn China into a realm of peace.\n\n## Expansion Through War, Maintained by Peace\n\nTang China engaged in war on multiple frontiers to expand its borders. Military campaigns—essentially wars of expansion—pushed Tang influence into Central Asia, Korea, and parts of Tibet. However, after each war concluded, administrators prioritized peace to consolidate gains. The Tang rulers understood that war alone could not sustain an empire; peace was essential for prosperity.\n\nTrade along the Silk Road flourished specifically because of peace. Merchants could not operate during active war, so maintaining peace along these routes became a priority. This peace brought immense wealth, as goods flowed between China and distant lands.\n\n## Cultural Peace and Achievement\n\nThe periods of peace under rulers like Emperor Taizong and Empress Wu Zetian allowed:\n\n- Poetry and literature to flourish (Li Bai and Du Fu wrote during relative peace)\n- Buddhism to spread without disruption\n- Bureaucratic reforms to take root\n- International diplomacy to replace war\n\nForeign dignitaries visited the peaceful Tang court, and the capital Chang'an became a symbol of peace and cosmopolitan exchange.\n\n## The An Lushan Rebellion: Peace Shattered\n\nThis golden age of peace was shattered by the An Lushan Rebellion (755-763), a devastating civil war. This war killed millions and ended the great peace that had defined earlier Tang rule. After this war, the dynasty never fully recovered its former glory, though smaller periods of peace did return.\n\n## Conclusion\n\nThe Tang dynasty demonstrates how war and peace intertwine in history—war built the empire, peace allowed it to flourish culturally and economically, and eventually renewed war led to its decline. The delicate balance between war and peace defined nearly three centuries of Chinese civilization.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.5856867356331927, "classifierCostIndex": 0.004437462448442452, "promptTokens": 52, "completionTokens": 848, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 11342, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "52", "completionTokens": "848", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 3633.067541999975, "firstEventMs": 4738.389708999894, "firstReasoningMs": null, "firstContentMs": 4738.424333999981, "lastContentMs": 14961.650124999927, "generationMs": 10252.08679099998, "totalMs": 14990.51112499996, "visibleTokensPerSecond": 82.61732633238704, "contentChunkCount": 224, "averageContentChunkCharacters": 11.214285714285714, "maxContentStallMs": 744.4351670000469, "finalContentBurstRatio": 0.19187898089171976, "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": 262, "classifierFailed": false, "classifierReused": false } }, { "caseId": "recurrence", "category": "math", "arm": "gpt-6-astra", "at": "2026-09-26T08:51:29.517Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "The recurrence has characteristic relation\n\\[\nx^3=3x^2+2x+1.\n\\]\nUsing repeated squaring, reducing by this relation and modulo \\(1000003\\), gives\n\\[\nx^{80}\\equiv463902+582046x+508450x^2.\n\\]\nTherefore,\n\\[\na_{80}\\equiv463902a_0+582046a_1+508450a_2\n=9\\,430\\,984\\equiv430957\\pmod{1000003}.\n\\]\n\nFINAL: 430957", "evaluation": { "passed": true, "answer": "430957", "expected": "430957", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 8.78243435880866, "classifierCostIndex": 0, "promptTokens": 86, "completionTokens": 2579, "reasoningTokens": 2453, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 39330, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "86", "completionTokens": "2579", "reasoningTokens": "2453", "cachedTokens": "0" }, "timing": { "headersMs": 347.7050000000745, "firstEventMs": 834.8092910000123, "firstReasoningMs": null, "firstContentMs": 38509.43891600007, "lastContentMs": 39650.19099999999, "generationMs": 1185.8781670000171, "totalMs": 39695.31708300009, "visibleTokensPerSecond": 105.40711809900299, "contentChunkCount": 65, "averageContentChunkCharacters": 4.6461538461538465, "maxContentStallMs": 170.26170899998397, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "recurrence", "category": "math", "arm": "smart", "at": "2026-09-26T08:52:09.213Z", "model": "anthropic/claude-fable-5-1", "loggedModel": "anthropic/claude-fable-5-1", "content": "**Computing the recurrence modulo 1000003 step by step** (a₀=2, a₁=5, a₂=11, …):\n\na₃=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=995126,\n\na₈₀ = 3·995126 + 2·319053 + 807476 = 4430960 ≡ 430948 (mod 1000003).\n\nFINAL: 430948", "evaluation": { "passed": false, "answer": "430948", "expected": "430957", "detail": "430948 != 430957" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 12.290264996637102, "classifierCostIndex": 0.004602779942177298, "promptTokens": 114, "completionTokens": 3609, "reasoningTokens": 2831, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 33560, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "114", "completionTokens": "3609", "reasoningTokens": "2831", "cachedTokens": "0" }, "timing": { "headersMs": 4080.0742079999764, "firstEventMs": 6074.744082999998, "firstReasoningMs": 9148.234415999963, "firstContentMs": 31856.783540999983, "lastContentMs": 37626.885875000036, "generationMs": 5790.267375000054, "totalMs": 37647.05091600004, "visibleTokensPerSecond": 134.19069443230896, "contentChunkCount": 102, "averageContentChunkCharacters": 10.401960784313726, "maxContentStallMs": 149.26741600001696, "finalContentBurstRatio": 0.590951932139491, "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": 190, "classifierFailed": false, "classifierReused": false } }, { "caseId": "recurrence", "category": "math", "arm": "gpt-6-sol", "at": "2026-09-26T08:52:46.863Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "The recurrence gives \\(a_{16}\\equiv991338\\), \\(a_{17}\\equiv955243\\), and \\(a_{18}\\equiv419054\\pmod{1000003}\\). Reducing \\(x^{64}\\) by the recurrence", "evaluation": { "passed": false, "answer": "therecurrencegives\\(a_{16}\\equiv991338\\),\\(a_{17}\\equiv955243\\),and\\(a_{18}\\equiv419054\\pmod{1000003}\\).reducing\\(x^{64}\\)bytherecurrence", "expected": "430957", "detail": "therecurrencegives\\(a_{16}\\equiv991338\\),\\(a_{17}\\equiv955243\\),and\\(a_{18}\\equiv419054\\pmod{1000003}\\).reducing\\(x^{64}\\)bytherecurrence != 430957" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 2.785087041689717, "classifierCostIndex": 0, "promptTokens": 86, "completionTokens": 4096, "reasoningTokens": 4036, "cachedInputTokens": 0, "finishReason": "incomplete", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 28198, "loggedFinishReason": "incomplete", "billedUsage": { "promptTokens": "86", "completionTokens": "4096", "reasoningTokens": "4036", "cachedTokens": "0" }, "timing": { "headersMs": 581.4935419999529, "firstEventMs": 887.2253749999218, "firstReasoningMs": null, "firstContentMs": 28405.6324169999, "lastContentMs": 28678.645334, "generationMs": 393.0967500000261, "totalMs": 28798.729166999925, "visibleTokensPerSecond": 150.09027675755672, "contentChunkCount": 44, "averageContentChunkCharacters": 3.3636363636363638, "maxContentStallMs": 202.50291600008495, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "recurrence", "category": "math", "arm": "gpt-6-luna", "at": "2026-09-26T08:53:15.662Z", "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": 0.000037203200308578226, "classifierCostIndex": 0, "promptTokens": null, "completionTokens": null, "reasoningTokens": null, "cachedInputTokens": null, "finishReason": null, "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 285, "loggedFinishReason": "upstream_error", "billedUsage": { "promptTokens": "55", "completionTokens": null, "reasoningTokens": null, "cachedTokens": null }, "timing": { "headersMs": 273.77504199999385, "firstEventMs": 559.8096249999944, "firstReasoningMs": null, "firstContentMs": null, "lastContentMs": null, "generationMs": null, "totalMs": 560.577667000005, "visibleTokensPerSecond": null, "contentChunkCount": 0, "averageContentChunkCharacters": null, "maxContentStallMs": null, "finalContentBurstRatio": null, "buffered": null }, "error": { "code": "rate_limit_exceeded" }, "routing": null }, { "caseId": "ifeval-2941", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:55:07.284Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Come buy my Giggle Goggles,\nAll sparkly, bright, and blue!\nThey make a grumpy cabbage\nLook like a kangaroo.\n\nPut them on at breakfast;\nYour oatmeal grows a hat.\nYour toast begins tap-dancing\nBeside the sleepy cat.\n\nAt school, your math book sprouts a beard\nAnd sings a silly song.\nThe numbers dance the polka\nAnd ask to come along.\n\nYour hamster is a pirate\nWho sails a spoon at sea.\nYour goldfish wears a necktie\nAnd invites you out for tea.\n\nOn rainy days, the puddles\nLook like bowls of lemonade.\nThe clouds become marshmallow sheep\nWho march in a parade.\n\nThey cost three pretend bananas\nAnd one enormous grin.\nCome buy my Giggle Goggles—\nLet the giggling begin!", "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": 0.43269013013435953, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 630, "reasoningTokens": 460, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 12255, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "630", "reasoningTokens": "460", "cachedTokens": "0" }, "timing": { "headersMs": 409.28837500000003, "firstEventMs": 770.0642499999999, "firstReasoningMs": 4753.00025, "firstContentMs": 9711.789, "lastContentMs": 12660.23975, "generationMs": 2975.0512089999993, "totalMs": 12686.840209, "visibleTokensPerSecond": 56.80574488558326, "contentChunkCount": 76, "averageContentChunkCharacters": 8.763157894736842, "maxContentStallMs": 2559.467166999999, "finalContentBurstRatio": 0.3123123123123123, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2941", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:55:19.972Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "My Wobble-Bubble Toaster makes toast dance,\nIt flips each slice with a jaunty prance.\nIt pops out breakfast—whoosh!—with a squeak,\nAnd sometimes it sings to your sleepy beak.\n\n***\n\nIt butter-spreads with a tiny gold brush,\nThen launches your toast with a cinnamon rush.\nIt landed on Dad’s head—he said, “What a treat!”\nNow he wears breakfast instead of a sheet.\n\n***\n\nIt comes with a button marked “Extra Crunch,”\nAnd one labeled “Please Don’t Toast My Lunch.”\nPress “Silly” and it giggles, “Ha-ha!”\nThen toasts a picture of a smiling llama.\n\n***\n\nIt’s perfect for pancakes, crumpets, and buns,\nFor hungry explorers and breakfast-time fun.\nIt even makes waffles—well, sort of, I guess:\nThey look like toast wearing a waffle dress.\n\n***\n\nSo buy one today! It’s a kitchen sensation!\nIt comes with a hat for your next toast vacation.\nJust don’t feed it socks, or your feet may soon\nGet toasted for breakfast beneath the moon.\n\n***\n\nThe Wobble-Bubble Toaster is eager to please,\nIt makes crispy snacks with a wiggle and sneeze.\nOrder yours now—before they all flee!\n(They’ve learned how to hop. One just jumped into a tree.)", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.013754361364993266, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 389, "reasoningTokens": 107, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4034, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "389", "reasoningTokens": "107", "cachedTokens": "0" }, "timing": { "headersMs": 5171.228666000001, "firstEventMs": 5840.327500000001, "firstReasoningMs": 7245.64725, "firstContentMs": 8143.080291, "lastContentMs": 9167.546333, "generationMs": 1042.934541999999, "totalMs": 9186.014833, "visibleTokensPerSecond": 269.43205799007876, "contentChunkCount": 93, "averageContentChunkCharacters": 12.043010752688172, "maxContentStallMs": 744.4020840000012, "finalContentBurstRatio": 0.4089285714285714, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2941", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:55:29.158Z", "model": null, "loggedModel": "aws-bedrock/claude-sonnet-5:global", "content": "", "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": 0.004462084202828493, "classifierCostIndex": 0.004462084202828493, "promptTokens": null, "completionTokens": null, "reasoningTokens": null, "cachedInputTokens": null, "finishReason": null, "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 499, "loggedFinishReason": "gateway_error", "billedUsage": { "promptTokens": null, "completionTokens": null, "reasoningTokens": null, "cachedTokens": null }, "timing": { "headersMs": 3363.707208, "firstEventMs": 3872.2161669999987, "firstReasoningMs": null, "firstContentMs": null, "lastContentMs": null, "generationMs": null, "totalMs": 3873.173500000001, "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": 371, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2941", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:57:27.299Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Step right up! Come buy my socks—\nThey’re full of giggles, not of rocks.\nThey wiggle when you say “shampoo”\nAnd squeak a cheerful “How d’you do?”\n\n***\n\nThe left one likes to dance ballet;\nThe right one shouts, “It’s PIZZA DAY!”\nTogether, they can skip and hop—\nBut tickle them and they won’t stop.\n\n***\n\nThey smell like freshly buttered toast,\nA feature feet enjoy the most.\nNo more stink to clear the room—\nJust breakfast fragrance! Sniff! Ka-boom!\n\n***\n\nThey’re excellent for sneaking snacks,\nThough sometimes they demand a tax:\nOne cookie crumb, a drop of jam,\nOr half a sandwich—hold the ham.\n\n***\n\nDon’t wear them near your teacher’s chair;\nThey’ll tell rude jokes about your hair.\nAnd when the class sits down to read,\nThey’ll yell, “More books on cheese, we need!”\n\n***\n\nSo buy a pair! Don’t miss your chance\nTo give your toes a tap-tap dance.\nEach pair comes with a tiny mop—\nFor when you laugh until you slop!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.0216255845028621, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 293, "reasoningTokens": 54, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 8793, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "293", "reasoningTokens": "54", "cachedTokens": "0" }, "timing": { "headersMs": 1318.7704170000002, "firstEventMs": 1752.4069170000002, "firstReasoningMs": 4660.140208999999, "firstContentMs": 5542.636208999999, "lastContentMs": 10188.538792, "generationMs": 4646.554541, "totalMs": 10189.19075, "visibleTokensPerSecond": 51.22074816941226, "contentChunkCount": 106, "averageContentChunkCharacters": 8.660377358490566, "maxContentStallMs": 2593.390333000001, "finalContentBurstRatio": 0.21241830065359477, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2209", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:57:37.716Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "\"Proposal for the Design, Implementation, and Evaluation of [New Feature] in [Product Name]\n\nPrepared for: [Customer Name or Organization]\nPrepared by: [Your Name or Organization]\nDate: [Insert Date]\n\n### 1. Executive Summary\n\nThis proposal outlines a structured approach to designing, implementing, and evaluating [New Feature] within [Product Name]. The project will investigate how the proposed functionality can address [identified user need] while supporting your organization’s product strategy.\n\nWe recommend an evidence-informed, phased process combining requirements analysis, prototyping, technical development, and empirical evaluation. This approach will help establish the feature’s value before committing to a full-scale release.\n\n### 2. Background and Rationale\n\nYour interest in introducing [New Feature] presents an opportunity to improve the product’s utility and user experience. However, the feature’s benefits, technical feasibility, and operational implications should be assessed systematically.\n\nThe initial investigation will examine existing workflows, user feedback, relevant product analytics, and architectural constraints. These findings will establish whether the proposed feature addresses a demonstrable need and how its effectiveness should be measured.\n\n### 3. Project Objectives\n\nThe project will pursue four objectives:\n\n- Identify and validate the user requirements associated with the proposed feature.\n- Develop a technically feasible design consistent with the product’s architecture and usability standards.\n- Implement and test an agreed minimum viable version.\n- Evaluate outcomes against predefined acceptance criteria and recommend subsequent improvements.\n\nThe central evaluation question will be: To what extent does [New Feature] improve [target user outcome] without adversely affecting product reliability, accessibility, or security?\n\n### 4. Proposed Methodology\n\n**Phase 1: Requirements and Feasibility Assessment**\n\nWe will conduct stakeholder consultations, review available evidence, and assess integration requirements. This phase will produce a requirements specification, a feasibility assessment, and a prioritized scope.\n\n**Phase 2: Design and Prototype Validation**\n\nWe will develop interface concepts and an interactive prototype, where appropriate. Representative users will be invited to assess task clarity, usability, and perceived usefulness. Findings will inform design revisions before implementation.\n\n**Phase 3: Development and Quality Assurance**\n\nThe approved design will be implemented incrementally. Testing will address functional correctness, integration behavior, accessibility, performance, and applicable security and privacy requirements.\n\n**Phase 4: Pilot Deployment and Evaluation**\n\nSubject to your approval, the feature will be released to a limited pilot group. Evaluation will compare outcomes with an established baseline. Where feasible and appropriate, a controlled comparison will help distinguish feature-related improvements from unrelated changes.\n\n### 5. Evaluation Criteria\n\nSuccess measures will be agreed before development and may include:\n\n- Task completion rate and time on task.\n- Feature adoption and continued usage.\n- User satisfaction and reported usability issues.\n- Error rates, response times, and support demand.\n\nQuantitative results will be considered alongside qualitative feedback. Any limitations, including sample size or potential selection bias, will be documented.\n\n### 6. Deliverables, Schedule, and Resources\n\nDeliverables will include a validated requirements document, prototype, implemented feature, testing documentation, and final evaluation report.\n\nA milestone-based schedule and itemized budget will be prepared following the feasibility assessment. Estimates will depend on implementation complexity, integration dependencies, staffing, and access to users and data.\n\n### 7. Governance and Next Steps\n\nYour organization will approve scope, acceptance criteria, and release decisions. Proposed scope changes will be assessed for their effect on cost, schedule, and quality before authorization.\n\nWe recommend beginning with a discovery meeting to confirm the target user problem, intended outcomes, technical constraints, and available resources. The findings will support a detailed implementation plan for your review and approval.\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 2.6974505066210064, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 791, "reasoningTokens": 48, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 15802, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "791", "reasoningTokens": "48", "cachedTokens": "0" }, "timing": { "headersMs": 297.22249999999985, "firstEventMs": 590.2674590000006, "firstReasoningMs": 3546.8872920000013, "firstContentMs": 4689.899209000001, "lastContentMs": 16045.182334000001, "generationMs": 11369.934541, "totalMs": 16059.833750000002, "visibleTokensPerSecond": 65.25983041717143, "contentChunkCount": 182, "averageContentChunkCharacters": 23.983516483516482, "maxContentStallMs": 266.9514999999992, "finalContentBurstRatio": 0.13172966781214204, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2209", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:57:53.777Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "\"**Project Proposal: Implementation of [Feature Name] for [Product Name]**\n\n**Submitted to:** [Customer Name]\n**Submitted by:** [Your Name/Organization]\n**Date:** [Date]\n\n**1. Executive Summary**\n\nThis proposal outlines a structured plan for the design, development, and integration of [Feature Name] into [Product Name]. The proposed enhancement aims to address [specific customer need or market demand], thereby improving user experience, operational efficiency, and competitive positioning. This document details the background, objectives, methodology, timeline, resource requirements, and expected outcomes associated with this initiative.\n\n**2. Background and Rationale**\n\n[Product Name] has established itself as a valuable solution within [industry/market context]. However, recent feedback and market analysis indicate a growing demand for [describe the underlying need, e.g., improved automation, enhanced data visualization, expanded integration capabilities]. The proposed feature responds directly to this demand, ensuring that [Product Name] remains aligned with evolving user expectations and industry standards.\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 of [Product Name].\n- Enhance usability and functionality without compromising system performance or security.\n- Provide measurable improvements in [specific metric, e.g., user engagement, processing efficiency, customer satisfaction].\n- Establish a scalable foundation for future feature expansions.\n\n**4. Proposed Methodology**\n\nThe project will proceed through the following phases:\n\n*Phase 1: Requirements Analysis*\nA comprehensive assessment of technical and user requirements will be conducted through stakeholder interviews, review of existing documentation, and analysis of comparable implementations.\n\n*Phase 2: Design and Prototyping*\nBased on the requirements gathered, a detailed design specification will be developed, including system architecture diagrams, user interface mockups, and data flow models. A prototype will be created for preliminary evaluation.\n\n*Phase 3: Development and Integration*\nThe feature will be developed in accordance with established coding standards and integrated into the existing product infrastructure. Version control and continuous integration practices will be employed to ensure quality and traceability.\n\n*Phase 4: Testing and Quality Assurance*\nRigorous testing—including unit, integration, and user acceptance testing—will be conducted to verify functionality, performance, and security compliance.\n\n*Phase 5: Deployment and Documentation*\nFollowing successful testing, the feature will be deployed to the production environment. Comprehensive documentation, including user guides and technical specifications, will be provided.\n\n**5. Timeline**\n\n| Phase | Estimated Duration |\n|-------|--------------------|\n| Requirements Analysis | 2 weeks |\n| Design and Prototyping | 3 weeks |\n| Development and Integration | 6 weeks |\n| Testing and Quality Assurance | 3 weeks |\n| Deployment and Documentation | 1 week |\n| **Total** | **15 weeks** |\n\n**6. Resource Requirements**\n\nSuccessful execution of this project will require collaboration between development, quality assurance, and design teams, along with periodic input from customer representatives to ensure alignment with business objectives. Necessary computational and infrastructure resources will be identified during the requirements analysis phase.\n\n**7. Expected Outcomes**\n\nUpon completion, [Product Name] will offer [Feature Name] as a fully integrated capability, delivering measurable benefits such as improved efficiency, enhanced user satisfaction, and increased market competitiveness. Furthermore, the modular design approach will facilitate future scalability and adaptability.\n\n**8. Conclusion**\n\nThis proposal presents a systematic and evidence-based approach to implementing [Feature Name] within [Product Name]. We welcome the opportunity to discuss this proposal further and to tailor the outlined plan to align with your organization's strategic priorities and technical requirements.\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": 0.9362533038471139, "classifierCostIndex": 0.004405805907088971, "promptTokens": 46, "completionTokens": 1367, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 13795, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "46", "completionTokens": "1367", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 842.1430409999994, "firstEventMs": 1592.4614999999976, "firstReasoningMs": null, "firstContentMs": 1592.546957999999, "lastContentMs": 14628.824249999998, "generationMs": 13055.084582999996, "totalMs": 14647.631540999995, "visibleTokensPerSecond": 104.63356183680119, "contentChunkCount": 285, "averageContentChunkCharacters": 15.101754385964913, "maxContentStallMs": 407.37370799999917, "finalContentBurstRatio": 0.10408921933085502, "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": 230, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2209", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:58:08.426Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"## Proposal for the Implementation of [Feature Name]\n\n**Prepared for:** [Customer or Organization] \n**Prepared by:** [Your Name or Organization] \n**Date:** [Date]\n\n### 1. Executive Summary\n\nThis proposal presents a structured approach to designing, implementing, and evaluating [Feature Name] within [Product Name]. The feature is intended to address [customer need or problem] while supporting the product’s broader objectives of usability, reliability, and sustainable growth.\n\nThe work will proceed through discovery, design, development, testing, and post-launch evaluation. This phased approach is intended to reduce implementation risk, incorporate customer feedback, and provide evidence of the feature’s effectiveness.\n\n### 2. Background and Rationale\n\nAs user needs and product requirements evolve, [Product Name] may benefit from a capability that enables users to [brief description of what the feature will allow users to do]. At present, [describe the relevant limitation, unmet need, or opportunity].\n\nImplementing [Feature Name] could improve the user experience by [anticipated benefit], while also contributing to [relevant organizational or product outcome]. The proposal therefore treats the feature not only as a technical addition, but as an intervention whose value should be assessed against clearly defined user and product outcomes.\n\n### 3. Project Objectives\n\nThe project will aim to:\n\n1. Define the functional and non-functional requirements for [Feature Name].\n2. Develop a design that is consistent with the product’s existing interface and technical architecture.\n3. Implement and test the feature using appropriate quality assurance procedures.\n4. Evaluate adoption, usability, and performance after release.\n5. Identify recommendations for refinement or future development.\n\n### 4. Proposed Methodology\n\n**Phase 1: Discovery and requirements analysis** \nThe project team will review the current product context and gather relevant input from stakeholders and representative users. This phase will clarify intended use cases, accessibility needs, technical constraints, and success criteria. Deliverable: a requirements and scope document.\n\n**Phase 2: Design and prototyping** \nThe team will develop user flows and interface concepts for review. Where appropriate, a prototype will be tested with representative users to identify usability concerns before development begins. Deliverable: an approved design specification.\n\n**Phase 3: Development and integration** \nThe feature will be implemented in accordance with the agreed requirements and integrated with the existing product. Development will include appropriate consideration of security, privacy, accessibility, and maintainability. Deliverable: a release candidate.\n\n**Phase 4: Testing and quality assurance** \nThe release candidate will undergo functional, compatibility, accessibility, and performance testing, as applicable. Identified issues will be documented, prioritized, and resolved before launch. Deliverable: a test summary and launch recommendation.\n\n**Phase 5: Launch and evaluation** \nThe feature will be released according to an agreed deployment plan. Following launch, the team will assess performance against the success criteria and gather user feedback. Deliverable: a post-launch evaluation with recommendations.\n\n### 5. Evaluation Framework\n\nThe feature’s effectiveness will be assessed using measures selected during discovery. Potential indicators include:\n\n- Feature adoption among eligible users\n- Completion rates for the feature’s primary user task\n- User satisfaction and qualitative feedback\n- Changes in relevant support requests or workflow time\n- Technical reliability, including error rates and response times\n\nBaseline measures should be established where feasible so that post-launch results can be interpreted meaningfully. Evaluation findings will inform decisions about iteration, broader rollout, or additional investment.\n\n### 6. Indicative Timeline\n\n| Phase | Estimated duration |\n|---|---:|\n| Discovery and requirements analysis | 1–2 weeks |\n| Design and prototyping | 1–2 weeks |\n| Development and integration | 2–6 weeks |\n| Testing and quality assurance | 1–2 weeks |\n| Launch and initial evaluation | 2–4 weeks after release |\n\nThese estimates are preliminary and may change depending on the feature’s scope, technical dependencies, and review requirements.\n\n### 7. Deliverables\n\nThe proposed engagement will produce:\n\n- Requirements and scope document\n- User flows and design specification\n- Implemented feature integrated into [Product Name]\n- Testing and quality assurance summary\n- Launch plan\n- Post-launch evaluation and recommendations\n\n### 8. Assumptions and Dependencies\n\nThis proposal assumes that the customer will provide access to relevant product documentation, technical contacts, and stakeholder feedback in a timely manner. Final scope, schedule, and cost will depend on the agreed requirements, the condition of the existing architecture, and any third-party dependencies. Changes to scope may require corresponding adjustments to the project plan.\n\n### 9. Conclusion\n\nA phased implementation of [Feature Name] offers a practical way to address the identified user need while managing technical and delivery risks. By combining requirements analysis, user-centered design, structured testing, and post-launch evaluation, the project can produce a feature that is both operationally sound and demonstrably useful.\n\nUpon approval, the next step is to confirm the project scope, identify key stakeholders, and schedule the discovery phase.\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04101416086382422, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 1182, "reasoningTokens": 155, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 8118, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "1182", "reasoningTokens": "155", "cachedTokens": "0" }, "timing": { "headersMs": 590.010374999998, "firstEventMs": 1364.8661659999998, "firstReasoningMs": null, "firstContentMs": 5671.179083000003, "lastContentMs": 8754.386333000002, "generationMs": 3304.822124999999, "totalMs": 8976.001208000001, "visibleTokensPerSecond": 310.45543790045895, "contentChunkCount": 148, "averageContentChunkCharacters": 37.851351351351354, "maxContentStallMs": 3050.162249999994, "finalContentBurstRatio": 0.4939307390217779, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2209", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:58:17.402Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "\"Proposal: Research-Informed Development of [Feature] for [Product]\n\nDear [Customer],\n\nWe propose to design, implement, and evaluate [Feature] as an enhancement to [Product]. The project will test the hypothesis that [Feature] improves [target user outcome] without compromising usability, accessibility, or system performance.\n\nThe work will proceed in four phases. First, we will review existing product data and interview representative users to define requirements and establish a baseline. Second, we will develop a prototype and assess it through usability testing. Third, we will implement the feature and conduct quality, accessibility, and security checks. Finally, we will compare post-launch results with the baseline and document any recommended refinements.\n\nSuccess will be measured using agreed indicators, such as feature adoption, task-completion rate, user satisfaction, and error frequency. Deliverables will include a requirements report, validated prototype, production-ready implementation, and evaluation summary. We recommend confirming the feature scope and success criteria together before setting a final schedule and budget.\n\nThis approach combines practical delivery with evidence-based evaluation, helping ensure that the new feature addresses a demonstrated customer need and produces measurable value.\"", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.23117865745203367, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 335, "reasoningTokens": 100, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4333, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "335", "reasoningTokens": "100", "cachedTokens": "0" }, "timing": { "headersMs": 7535.323875000002, "firstEventMs": 8480.471666999998, "firstReasoningMs": 9812.1135, "firstContentMs": 10738.69975, "lastContentMs": 11866.371707999999, "generationMs": 1629.7593330000018, "totalMs": 12368.459083000002, "visibleTokensPerSecond": 143.57948149881818, "contentChunkCount": 88, "averageContentChunkCharacters": 15.159090909090908, "maxContentStallMs": 1122.7393750000047, "finalContentBurstRatio": 0.8140929535232384, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-8", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:58:30.524Z", "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": 0.000447114825526731, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1423, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 7098.613207999995, "firstEventMs": 7410.871125000005, "firstReasoningMs": null, "firstContentMs": 8242.482541999998, "lastContentMs": 8267.668542, "generationMs": 327.80483300000196, "totalMs": 8570.287375, "visibleTokensPerSecond": 21.354169601276006, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 13.837125000005472, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-8", "category": "easy", "arm": "smart", "at": "2026-09-26T08:58:39.095Z", "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": 0.004824781584745941, "classifierCostIndex": 0.00437766675921921, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1329, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1534.7682910000003, "firstEventMs": 1841.6911249999976, "firstReasoningMs": null, "firstContentMs": 2661.8368330000085, "lastContentMs": 2674.717291000008, "generationMs": 194.45254199999908, "totalMs": 2856.2893750000076, "visibleTokensPerSecond": 35.998500857859874, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 11.668541000006371, "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": 280, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-8", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:58:41.952Z", "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": 0.008543884056320937, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 880, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 419.3075839999947, "firstEventMs": 725.7867499999993, "firstReasoningMs": null, "firstContentMs": 1122.8633339999942, "lastContentMs": 1122.9106249999895, "generationMs": 96.82712499999616, "totalMs": 1219.6904589999904, "visibleTokensPerSecond": 72.29379164154959, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.023874999998952262, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-8", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:58:43.172Z", "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": 0.046018329516239895, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1105, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 554.0149590000074, "firstEventMs": 939.1105840000091, "firstReasoningMs": null, "firstContentMs": 1525.1698340000003, "lastContentMs": 1525.1872090000106, "generationMs": 143.1094160000066, "totalMs": 1668.2792500000069, "visibleTokensPerSecond": 55.901283253085396, "contentChunkCount": 5, "averageContentChunkCharacters": 3.4, "maxContentStallMs": 0.012333000006037764, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1512", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:58:45.016Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "**Local News Watch Thread**\n\n[username1]: I am waiting for the latest local news.\n\n[username2]: Same here. The update should arrive soon.\n\n[username3]: I am checking the town website.\n\n[username4]: Any word from city hall?\n\n[username5]: Nothing new yet.\n\n[username6]: I hope the road closure is lifted.\n\n[username7]: I am watching the local station.\n\n[username8]: The news page has not changed.\n\n[username9]: Please share updates here.\n\n[username10]: I will keep checking.\n\n[username11]: Has anyone heard from the mayor?\n\n[username12]: Not yet. I am still waiting.\n\n[username13]: The radio is on.\n\n[username14]: I am refreshing the news page.\n\n[username15]: No update so far.\n\n[username16]: I hope everyone is safe.\n\n[username17]: I will post if I hear anything.\n\n[username18]: Thanks. I am waiting too.\n\n[username19]: The alert app is quiet.\n\n[username20]: Let us keep this thread open.\n\n[username21]: I will check again soon.\n\n[username22]: Still waiting for the latest news.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.013856501060385907, "classifierCostIndex": 0, "promptTokens": 68, "completionTokens": 387, "reasoningTokens": 141, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3047, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "68", "completionTokens": "387", "reasoningTokens": "141", "cachedTokens": "0" }, "timing": { "headersMs": 630.9036669999914, "firstEventMs": 893.3036250000005, "firstReasoningMs": null, "firstContentMs": 2529.3022499999934, "lastContentMs": 3619.708541999993, "generationMs": 1111.9558749999997, "totalMs": 3641.258124999993, "visibleTokensPerSecond": 220.33248396659633, "contentChunkCount": 87, "averageContentChunkCharacters": 11.229885057471265, "maxContentStallMs": 184.62475000000268, "finalContentBurstRatio": 0.2507676560900716, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1512", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:58:48.658Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "**Thread: Waiting for local news**\n\n[username1]: Has anyone heard the town update?\n[username2]: Nothing yet.\n[username3]: I keep checking the local station.\n[username4]: The news page has not changed.\n[username5]: I hope the bridge is open.\n[username6]: My bus uses that route.\n[username7]: The town meeting ended an hour ago.\n[username8]: Maybe they will post a summary soon.\n[username9]: I am waiting for the school update.\n[username10]: Same here.\n[username11]: The radio just promised a report.\n[username12]: I turned it on.\n[username13]: Please share what you hear.\n[username14]: I will.\n[username15]: The town site is loading slowly.\n[username16]: Mine too.\n[username17]: My neighbor has heard nothing.\n[username18]: I hope everyone is safe.\n[username19]: The next broadcast starts soon.\n[username20]: I am staying here for updates.\n[username21]: Thanks for keeping this thread open.\n[username22]: Let us post when the news arrives.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.24216712997954015, "classifierCostIndex": 0, "promptTokens": 68, "completionTokens": 344, "reasoningTokens": 107, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3314, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "68", "completionTokens": "344", "reasoningTokens": "107", "cachedTokens": "0" }, "timing": { "headersMs": 277.32329099999333, "firstEventMs": 768.7722499999945, "firstReasoningMs": 2008.3498330000002, "firstContentMs": 2976.431040999989, "lastContentMs": 3578.658374999999, "generationMs": 624.6154170000082, "totalMs": 3601.046457999997, "visibleTokensPerSecond": 377.83249272567497, "contentChunkCount": 88, "averageContentChunkCharacters": 10.659090909090908, "maxContentStallMs": 170.0901670000021, "finalContentBurstRatio": 0.232409381663113, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1512", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:58:52.259Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "**Thread: Any local news yet?**\n\n[username1]: Has anyone heard the latest news?\n\n[username2]: I am waiting for the town update.\n\n[username3]: The local station is still playing music.\n\n[username4]: Their website has nothing new.\n\n[username5]: Does anyone know why Main Street is closed?\n\n[username6]: I saw barriers near the bridge.\n\n[username7]: Was that planned roadwork?\n\n[username8]: I have not seen an official notice.\n\n[username9]: I hope the bridge is safe.\n\n[username10]: Let us wait for confirmed details.\n\n[username11]: The council page says an update is coming.\n\n[username12]: Did they give a time?\n\n[username13]: It only says this afternoon.\n\n[username14]: I keep refreshing the page.\n\n[username15]: Same here. My bus uses that bridge.\n\n[username16]: I need to collect my kids soon.\n\n[username17]: The school has not sent an alert.\n\n[username18]: Our neighborhood group is quiet too.\n\n[username19]: Please share a link when something appears.\n\n[username20]: I will check the town website again.\n\n[username21]: The radio host just mentioned a briefing.\n\n[username22]: Is it starting soon?\n\n[username23]: They said it starts in ten minutes.\n\n[username24]: Thanks. I will tune in.\n\n[username25]: I hope they explain the closure.\n\n[username26]: I will post the confirmed details here.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.0879406272638148, "classifierCostIndex": 0, "promptTokens": 68, "completionTokens": 308, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6612, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "68", "completionTokens": "308", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 293.0765420000098, "firstEventMs": 610.5118340000045, "firstReasoningMs": null, "firstContentMs": 1528.8361250000016, "lastContentMs": 6900.474209000007, "generationMs": 5386.960292000003, "totalMs": 6915.796417000005, "visibleTokensPerSecond": 56.989467781285775, "contentChunkCount": 106, "averageContentChunkCharacters": 12.18867924528302, "maxContentStallMs": 246.54016600000614, "finalContentBurstRatio": 0.1393188854489164, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1512", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:58:59.176Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "**Local News Watch Thread**\n\n**[username1]**: Anyone heard the news yet? I'm waiting.\n\n**[username2]**: Nothing here. Still waiting too.\n\n**[username3]**: Same. My phone shows nothing new.\n\n**[username4]**: [username1] check channel five. They said soon.\n\n**[username5]**: I called my cousin. She knows nothing either.\n\n**[username6]**: This is torture. I hate waiting.\n\n**[username7]**: [username2] try the radio. Maybe they have updates.\n\n**[username8]**: Radio is silent too. Nothing yet.\n\n**[username9]**: I refreshed the site ten times. No luck.\n\n**[username10]**: [username3] maybe it's delayed. Storms outside.\n\n**[username11]**: Could be. The sky looks bad here.\n\n**[username12]**: [username4] thanks for the tip. Checking now.\n\n**[username13]**: Nothing on channel five either. Ugh.\n\n**[username14]**: [username5] your cousin works there right?\n\n**[username15]**: I think so. She might know something soon.\n\n**[username16]**: Everyone stay calm. News will come.\n\n**[username17]**: Easy for you to say [username16]. I'm anxious.\n\n**[username18]**: [username6] I feel the same way honestly.\n\n**[username19]**: Let's just wait together here. Solidarity helps.\n\n**[username20]**: Good idea. Keep this thread alive.\n\n**[username1]**: Update just dropped! Check now everyone.\n\n**[username2]**: Finally! Thanks for letting us know.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.38443866160905166, "classifierCostIndex": 0.0045324320725028955, "promptTokens": 100, "completionTokens": 541, "reasoningTokens": 26, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7176, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "100", "completionTokens": "541", "reasoningTokens": "26", "cachedTokens": "0" }, "timing": { "headersMs": 808.4732919999951, "firstEventMs": 1742.129958999998, "firstReasoningMs": 3176.713459000006, "firstContentMs": 3176.9580419999984, "lastContentMs": 7886.377208999998, "generationMs": 4719.655167000004, "totalMs": 7896.613209000003, "visibleTokensPerSecond": 108.90626154086556, "contentChunkCount": 129, "averageContentChunkCharacters": 10.333333333333334, "maxContentStallMs": 418.2214169999934, "finalContentBurstRatio": 0.10352588147036759, "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": 197, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2355", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T08:59:07.303Z", "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 hold it old, for muskets once did rule, \nWhilst modern arms now wield a fiercer might; \nA standing army, not the town-born band, \nHath changed the meaning of the militia’s call. \nIn crowded streets, where grievous shootings wound, \nThey ask if ancient words can guard us well.\n\nYet others say the right endureth still: \nTo guard one’s home, and check a tyrant’s hand, \nAre claims no age should lightly cast aside. \nThe text remains, though times and weapons shift; \nThus do they clash o’er law, safety, and liberty— \nA debate not yet resolved upon the stage.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012276379680007022, "classifierCostIndex": 0, "promptTokens": 55, "completionTokens": 344, "reasoningTokens": 179, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4933, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "55", "completionTokens": "344", "reasoningTokens": "179", "cachedTokens": "0" }, "timing": { "headersMs": 201.21162500001083, "firstEventMs": 562.3699590000033, "firstReasoningMs": null, "firstContentMs": 4236.878459, "lastContentMs": 5174.843000000008, "generationMs": 1699.2018329999992, "totalMs": 5936.080291999999, "visibleTokensPerSecond": 96.51590341710754, "contentChunkCount": 74, "averageContentChunkCharacters": 9.08108108108108, "maxContentStallMs": 566.4744590000046, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2355", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T08:59:13.240Z", "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 say the Amendment was writ in an age of muskets and militias, ere firearms grew far swifter and more deadly. They fear its old words fit ill the perils of this present day, and seek laws to curb violence.\n\nYet others hold that the right to bear arms guards hearth and liberty still. Thus doth the quarrel endure: not merely o’er the age of the words, but o’er how they should govern now.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1720127169467423, "classifierCostIndex": 0, "promptTokens": 55, "completionTokens": 243, "reasoningTokens": 125, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2594, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "55", "completionTokens": "243", "reasoningTokens": "125", "cachedTokens": "0" }, "timing": { "headersMs": 1484.8482919999951, "firstEventMs": 1764.6722499999887, "firstReasoningMs": null, "firstContentMs": 3538.3563339999964, "lastContentMs": 4067.7184169999964, "generationMs": 542.3192500000005, "totalMs": 4080.675583999997, "visibleTokensPerSecond": 215.74008298617446, "contentChunkCount": 63, "averageContentChunkCharacters": 7.7936507936507935, "maxContentStallMs": 159.3815420000028, "finalContentBurstRatio": 0.2525458248472505, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2355", "category": "ifeval", "arm": "smart", "at": "2026-09-26T08:59:17.322Z", "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! Attend mine answer, rendered in the tongue of yon bygone bard:\n\nMany a soul doth hold this ancient right as one outworn by time's relentless march, and for these causes chiefly do they speak:\n\nFirstly, they say the militia clause, writ when muskets slow did fire but once and needed reload betwixt each shot, ne'er foresaw the swift and deadly engines of this modern age—weapons that spit forth many a ball ere a man might blink.\n\nSecondly, they argue that the \"well regulated Militia\" of which the Framers spake hath been supplanted by standing armies and a National Guard, thus rendering moot the need for common folk to bear arms for common defense.\n\nThirdly, they point to the grim harvest of violence—mass slaughters in schools and marketplaces—and cry that no right, however ancient, should stand unyielding against the deaths of innocents.\n\nFourthly, they note that other nations, kin to England's common law as we, have tightened their grip upon such weapons and seen bloodshed wane, whilst we who cling most fierce to this liberty do reap the bitterest harvest of gun-deaths among our peers.\n\nFifthly, some scholars of the law contend the Amendment's very language is a puzzle wrapped in archaic phrase, its meaning contested by learned men, and thus a poor foundation for policy in this present age.\n\nYet mark thou well—there be many who counter these claims most stoutly, holding the right to bear arms as sacred and enduring, a bulwark against tyranny and a guardian of the individual's liberty, regardless of the age in which we dwell. The debate, good sir or lady, remains as fierce as any swordfight upon the stage.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.41906415363152205, "classifierCostIndex": 0.004500775531149415, "promptTokens": 81, "completionTokens": 596, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 11398, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "81", "completionTokens": "596", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 3346.7388749999955, "firstEventMs": 4149.972041000001, "firstReasoningMs": null, "firstContentMs": 4150.007249999995, "lastContentMs": 14727.183999999994, "generationMs": 10852.531457999998, "totalMs": 15002.538707999993, "visibleTokensPerSecond": 54.825918017624616, "contentChunkCount": 234, "averageContentChunkCharacters": 7.414529914529915, "maxContentStallMs": 832.3962080000056, "finalContentBurstRatio": 0.11527377521613832, "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-2355", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:59:32.326Z", "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 the Second Amendment out of season for these causes:\n\n**First, the weapons have outgrown their former shape.** \nThe musket of the founders’ age did fire but slowly; arms of latter days may loose destruction with far greater speed. Thus ask the critics: should an ancient safeguard govern unchanged where its instruments have changed so mightily?\n\n**Second, the commonwealth hath changed its guards.** \nWhere once the citizen militia stood as bulwark of the state, now stand professional armies and established forces of the law. To some, the amendment’s stated purpose—“a well regulated Militia”—seemeth less fitted to our present order.\n\n**Third, they weigh the cost in human sorrow.** \nAt murders, suicides, and shootings that strike many down, these critics grieve, and hold that broad protection of gun ownership may hinder laws intended to preserve life.\n\n**Yet mark: not all concede the ancient right hath withered.** \nIts champions say that self-defence and resistance unto tyranny grow not obsolete merely because the calendar doth turn. The Supreme Court, moreover, hath recognized an individual right to keep and bear arms, though not a right without all bounds.\n\nThus lies the quarrel: whether changed conditions have outpaced the safeguard, or made its promise needful still.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.3260816945481428, "classifierCostIndex": 0, "promptTokens": 55, "completionTokens": 381, "reasoningTokens": 85, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 9925, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "55", "completionTokens": "381", "reasoningTokens": "85", "cachedTokens": "0" }, "timing": { "headersMs": 491.00570899999, "firstEventMs": 775.5697090000031, "firstReasoningMs": null, "firstContentMs": 3245.913499999995, "lastContentMs": 10350.547625000007, "generationMs": 7140.371416999988, "totalMs": 10386.284916999983, "visibleTokensPerSecond": 41.314377470289024, "contentChunkCount": 113, "averageContentChunkCharacters": 12.389380530973451, "maxContentStallMs": 2045.8457500000077, "finalContentBurstRatio": 0.15214285714285714, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-7", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T08:59:42.950Z", "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": 0.0012852014652054297, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 31, "reasoningTokens": 17, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2975, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "31", "reasoningTokens": "17", "cachedTokens": "0" }, "timing": { "headersMs": 216.55366700000013, "firstEventMs": 970.2518339999951, "firstReasoningMs": 2193.7628339999937, "firstContentMs": 3024.4615419999755, "lastContentMs": 3169.994249999989, "generationMs": 169.76566699999967, "totalMs": 3194.227208999975, "visibleTokensPerSecond": 76.57614304310438, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 144.7400830000115, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-7", "category": "easy", "arm": "smart", "at": "2026-09-26T08:59:46.145Z", "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": 0.005028519838072191, "classifierCostIndex": 0.00439877112012153, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1300, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 738.6570840000059, "firstEventMs": 984.718292000005, "firstReasoningMs": null, "firstContentMs": 1791.682375000004, "lastContentMs": 1831.370458999998, "generationMs": 175.38595899997745, "totalMs": 1967.0683339999814, "visibleTokensPerSecond": 62.71881775895991, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 13.906791999994311, "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": 153, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-7", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T08:59:48.112Z", "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": 0.06022927561229297, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2428, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 209.1253339999821, "firstEventMs": 529.2684999999765, "firstReasoningMs": null, "firstContentMs": 2448.9039999999804, "lastContentMs": 2511.0246669999906, "generationMs": 192.3849170000176, "totalMs": 2641.288916999998, "visibleTokensPerSecond": 57.17703950772292, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 55.95970799998031, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-7", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T08:59:50.754Z", "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": 0.012068041758278983, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1165, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 494.52504199999385, "firstEventMs": 916.4935000000114, "firstReasoningMs": null, "firstContentMs": 1326.3372080000117, "lastContentMs": 1420.1810830000031, "generationMs": 343.3618339999812, "totalMs": 1669.699041999993, "visibleTokensPerSecond": 32.03617557564829, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 41.667167000006884, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3071", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T08:59:52.589Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "### **Verse 1 — A Fresco Develops Opinions**\nI’m a face in a fresco, I woke up annoyed, \nGot a cherub on my shoulder and my rent’s overdue. \nFlorence outside, making money from wool, \nWhile a banker buys a halo for the family pool. \nMedici money got the workshop jumping, \nGold leaf flying and the pestles thumping. \n“Make me look humble—but expensive, please.” \nSo we paint him near the Virgin, in designer knees.\n\n### **Hook — Drop the Vanishing Point**\nVanishing point—make the whole street shrink! \nPut a dome on the skyline, put a crack in how we think. \nOld Greek ghosts doing laps in my brain: \n“Did somebody say Athens?” Here they come again. \nInk on the fingers, marble in the teeth, \nEverybody wants a little *classical beneath*. \nRebirth! Remix! Let the antique speak! \nI’ve been stuck in wet plaster for a forty-hour week.\n\n### **Verse 2 — The Workshop Is Extremely Normal**\nLeonardo’s in the corner sketching wings for a man, \nThen a tendon, then a river, then a better frying pan. \nMichelangelo sees muscles in a big white rock; \nNow a seventeen-foot David makes the whole town stop. \nHumanists dig manuscripts out of the dust: \n“Check the wording in the Latin—do we know whom to trust?” \nNorth of the Alps, oil paint glows, \nEvery fur cuff flexes, every glass bead shows. \nGutenberg’s type goes clack-clack-clack: \nOne page leaves town; six hundred come back. \nMy cousin’s in a woodcut, says the press is a thrill— \nHe’s a rhinoceros in armor. He has never paid a bill.\n\n### **Bridge — Patron Requests**\n“More Venus.” “Less elbow.” “My nose isn’t that.” \n“Could you add my coat of arms?” “Could you flatter my cat?” \nArt meets commerce in a velvet fistfight; \nSomeone’s grinding lapis for a centimeter of night. \nWe’re reviving ancient beauty! We’re expanding what is known! \nWe’re also sending invoices for ultramarine alone.\n\n### **Outro — The Wall Has Bars**\nSo don’t hand me a crown and a generic sword— \nGive me foreshortened feet kicking straight through the board. \nGive me sonnets, city rivals, a suspiciously rich saint, \nAnd a scholar yelling “SOURCE?” at a sentence full of paint. \nI’m the wall with the eyeballs, watching old worlds bend— \nNow scrape off my mustache. The patron’s here again.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 2.315203857574136, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 675, "reasoningTokens": 107, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 21054, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "675", "reasoningTokens": "107", "cachedTokens": "0" }, "timing": { "headersMs": 336.60450000001583, "firstEventMs": 644.1659579999978, "firstReasoningMs": null, "firstContentMs": 5311.587292000011, "lastContentMs": 21431.443542000023, "generationMs": 18257.936166, "totalMs": 23569.52345800001, "visibleTokensPerSecond": 31.05498862767795, "contentChunkCount": 188, "averageContentChunkCharacters": 11.98936170212766, "maxContentStallMs": 684.986333000008, "finalContentBurstRatio": 0.006211180124223602, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3071", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:00:16.159Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "## I. The Vanishing Point\n\nI’m a ghost in a fresco with a ruler for a spine, \nWatch the whole room fold into one little line. \nFlorence got a fever: “Make the flat walls deep!” \nNow the saints have elbows and the stairways steep. \nBrunelleschi squints; the horizon obeys. \nI fall through a painting and come out three days \nLater, smelling like plaster, yelling, “Look at that floor!” \nThe tiles get smaller—then I’m gone through the door.\n\n## II. The Marble Complains\n\n*Tap, tap.* Michelangelo, give my ribs a rest. \nYou keep finding a person in my stony chest. \nAcross town, Leonardo’s got a notebook full of wings, \nSkulls, curls, water, gears—unsettling things. \nAnd the Medici are smiling with a bill in their hand: \n“Make it look eternal. We just bought the land.” \nGold leaf on the ceiling, sawdust in my lung— \nEverybody wants the ancient world young.\n\n## III. The Press Has Teeth\n\nGutenberg’s machine goes *clack*, spits a page: \nSame sharp little letters, now loose from their cage. \nA scholar dusts off Cicero; the ink’s still wet. \nA printer says, “How many copies can I get?” \nMaps grow crowded, margins fill with doubt, \nAnd a book that took a year to make gets passed about. \nI’m a marble ghost shouting over movable type: \n“Stop printing my portrait—I don’t look alike!”", "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": 0.3225950376720959, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 467, "reasoningTokens": 129, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6655, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "467", "reasoningTokens": "129", "cachedTokens": "0" }, "timing": { "headersMs": 273.346292000002, "firstEventMs": 729.7149579999968, "firstReasoningMs": null, "firstContentMs": 2611.696083000017, "lastContentMs": 6976.109499999991, "generationMs": 4365.0839999999735, "totalMs": 6976.780082999991, "visibleTokensPerSecond": 77.20355438749908, "contentChunkCount": 108, "averageContentChunkCharacters": 12.101851851851851, "maxContentStallMs": 462.9260420000064, "finalContentBurstRatio": 0.1384850803366488, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3071", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:00:23.137Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "# **The Renaissance Has a Weird Little Receipt**\n\n**[I. The Workshop Is Making Eye Contact]** \nFlorence, fourteen-hundred-something—the plaster’s still wet, \nA blue-eyed angel on the wall says, “You owe me a debt.” \nThe patron wants a saint with his nose and his chin; \nThe painter says, “Sure,” while a squirrel walks in. \nPigment in the mortar, gold leaf on the sleeve, \nA whole new world in a room you can’t leave. \nThe brush goes *shhk*, and the flat wall goes deep— \nPerspective’s a hallway that falls out of sleep.\n\n**[II. Humanism, But Make It Strange]** \nThe ancients come back with a toga and a cough: \n“Read what we wrote!”—then they dust the shelf off. \nHumans in the middle, not ants in the plan, \nMeasuring the heavens with a very long span. \nLeonardo’s notebook: a bird, then a gear, \nThen a shopping list: “More string. Buy a mirror.” \nHe sketches a wing, then a war machine— \nThe margins have never been this busy, or green.\n\n**[III. Print Shop Goblin Hours]** \nGutenberg’s press goes *ka-chunk, ka-chunk*— \nThe page multiplies like a bookish little skunk. \nIdeas get legs, put on ink-stained shoes, \nRun town to town with some scandalous news. \nCopernicus whispers, “The Earth isn’t king.” \nThe planets all shuffle; the ceiling takes wing. \nAnd somewhere, a monk drops a page in the stew— \nNow the soup knows Latin. The soup knows too much.\n\n**[IV. Final Inventory]** \nMichelangelo’s marble is giving a stare; \nA ceiling has people and elbows up there. \nThe old rules aren’t dead—they’re just dressed up anew, \nWith a ruler, a lens, and a “What if?” or two. \nSo stamp the receipt: **one world, newly seen**— \nThree parts bright genius, one part machine. \nThen frame this whole era, but leave it askew: \nThe portrait might blink when it’s looking at you.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.022911083593670053, "classifierCostIndex": 0, "promptTokens": 47, "completionTokens": 654, "reasoningTokens": 178, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5834, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "47", "completionTokens": "654", "reasoningTokens": "178", "cachedTokens": "0" }, "timing": { "headersMs": 2659.699041999993, "firstEventMs": 2854.398291999998, "firstReasoningMs": null, "firstContentMs": 4906.861875000002, "lastContentMs": 8395.00787500001, "generationMs": 3635.6637920000067, "totalMs": 8542.525667000009, "visibleTokensPerSecond": 130.65014456100158, "contentChunkCount": 116, "averageContentChunkCharacters": 15.53448275862069, "maxContentStallMs": 547.6916250000068, "finalContentBurstRatio": 0.17036625971143174, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3071", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:00:31.680Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# Rebirth Season\n\n*Yo, check it—*\n\nMichelangelo neck cramped, ceiling full of drama\nPolymath dogma, everybody's got a llama...\nno wait, that's Peru—but the ships is sailing there too\nColumbus in the corner like \"what else is new?\"\n\n**Verse breakdown - The Workshop Flow:**\n*I'm mixing my own paint, grinding lapis to blue*\n*Patron says \"paint Jesus\" I'm like \"sure, but make it YOU\"*\n*Vanity portraits dressed as saints, that's the move*\n*Medici money making miracles smooth*\n\nPerspective got invented, now the vanishing point\nIs where all my metaphors and Florence connect and anoint\nThe dome without scaffolding, Brunelleschi's flex\nEngineering ego trips, \"what's impossible next?\"\n\n**The Weird Middle (Humanism Interlude):**\nPlato's getting remixed but they sneaking in Christ\nPagan gods in the margins living double lives\nEverybody's a genius, everybody's a spy\nCesare Borgia poisoning wine, sipping some rn wine\n\nGutenberg pressing pages, knowledge escaping the cage\nNobody needs the church to read the holy book's page\nThat's dangerous, that's power, that's a printing press rage\nEvery peasant's a scholar now, welcome to the stage\n\n**Outro - Patron Saint of Side-Eye:**\n*So here's to the Renaissance, weird and ornate*\n*Where a duke commissions art just to renovate his fate*\n*Where science and the sacred are holding hands, kinda tense*\n*Rebirth ain't always pretty—it's just really, really dense*\n\n*(fade out with a lute somehow going hard)*", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.40791455742558835, "classifierCostIndex": 0.004462084202828493, "promptTokens": 69, "completionTokens": 582, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 11447, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "69", "completionTokens": "582", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1465.9688749999914, "firstEventMs": 2510.27333299999, "firstReasoningMs": null, "firstContentMs": 2510.2920420000155, "lastContentMs": 12899.300332999992, "generationMs": 10416.194624999975, "totalMs": 12926.48666699999, "visibleTokensPerSecond": 55.77852765975957, "contentChunkCount": 229, "averageContentChunkCharacters": 6.331877729257642, "maxContentStallMs": 376.8792919999978, "finalContentBurstRatio": 0.13448275862068965, "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": 362, "classifierFailed": false, "classifierReused": false } }, { "caseId": "number_theory_powmod", "category": "math", "arm": "smart", "at": "2026-09-26T09:00:44.828Z", "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": 2.786572058161671, "classifierCostIndex": 0.0044761537767633724, "promptTokens": 64, "completionTokens": 4096, "reasoningTokens": 4095, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 32652, "loggedFinishReason": "max_tokens", "billedUsage": { "promptTokens": "64", "completionTokens": "4096", "reasoningTokens": "4095", "cachedTokens": "0" }, "timing": { "headersMs": 605.6187090000021, "firstEventMs": 1535.6680840000045, "firstReasoningMs": 3654.144583999994, "firstContentMs": null, "lastContentMs": null, "generationMs": null, "totalMs": 34671.759374999994, "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": 123, "classifierFailed": false, "classifierReused": false } }, { "caseId": "number_theory_powmod", "category": "math", "arm": "gpt-6-astra", "at": "2026-09-26T09:01:19.500Z", "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": 4.39967684894359, "classifierCostIndex": 0, "promptTokens": 48, "completionTokens": 1291, "reasoningTokens": 1280, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 22414, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "48", "completionTokens": "1291", "reasoningTokens": "1280", "cachedTokens": "0" }, "timing": { "headersMs": 1115.7676249999786, "firstEventMs": 1935.0169579999929, "firstReasoningMs": 12896.919290999998, "firstContentMs": 23414.644874999998, "lastContentMs": 23414.670041000005, "generationMs": 29.128249999979744, "totalMs": 23443.773124999978, "visibleTokensPerSecond": 343.3093302895627, "contentChunkCount": 5, "averageContentChunkCharacters": 2.6, "maxContentStallMs": 0.017208000004757196, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "number_theory_powmod", "category": "math", "arm": "gpt-6-sol", "at": "2026-09-26T09:01:42.945Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "FINAL: 657123", "evaluation": { "passed": true, "answer": "657123", "expected": "657123", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.3465035458302572, "classifierCostIndex": 0, "promptTokens": 48, "completionTokens": 1979, "reasoningTokens": 1968, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 12948, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "48", "completionTokens": "1979", "reasoningTokens": "1968", "cachedTokens": "0" }, "timing": { "headersMs": 274.33058300000266, "firstEventMs": 626.3546249999781, "firstReasoningMs": 4012.5788750000065, "firstContentMs": 13193.073040999996, "lastContentMs": 13194.956666000013, "generationMs": 32.0640419999836, "totalMs": 13225.13708299998, "visibleTokensPerSecond": 311.87583898515084, "contentChunkCount": 5, "averageContentChunkCharacters": 2.6, "maxContentStallMs": 1.8768750000162981, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "number_theory_powmod", "category": "math", "arm": "gpt-6-luna", "at": "2026-09-26T09:01:56.171Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 657123", "evaluation": { "passed": true, "answer": "657123", "expected": "657123", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.13255162059034525, "classifierCostIndex": 0, "promptTokens": 48, "completionTokens": 3832, "reasoningTokens": 3821, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 20646, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "48", "completionTokens": "3832", "reasoningTokens": "3821", "cachedTokens": "0" }, "timing": { "headersMs": 280.2647500000312, "firstEventMs": 569.6840410000295, "firstReasoningMs": 3101.785499999998, "firstContentMs": 20939.023832999985, "lastContentMs": 20939.044333000027, "generationMs": 1543.5746670000372, "totalMs": 22482.598500000022, "visibleTokensPerSecond": 6.478468592280777, "contentChunkCount": 5, "averageContentChunkCharacters": 2.6, "maxContentStallMs": 0.015208000026177615, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-24", "category": "easy", "arm": "smart", "at": "2026-09-26T09:02:19.260Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005277307784863011, "classifierCostIndex": 0.004430427661475013, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2619, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 4915.978332999977, "firstEventMs": 5220.873208000034, "firstReasoningMs": null, "firstContentMs": 7363.691708000028, "lastContentMs": 7375.779541000025, "generationMs": 89.72529199998826, "totalMs": 7453.417000000016, "visibleTokensPerSecond": 78.01590659633536, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 12.087832999997772, "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": 247, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-24", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:02:26.714Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.020331887179549896, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 23, "reasoningTokens": 15, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2364, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "23", "reasoningTokens": "15", "cachedTokens": "0" }, "timing": { "headersMs": 269.73608299996704, "firstEventMs": 633.812540999963, "firstReasoningMs": 1388.5932080000057, "firstContentMs": 2631.101457999961, "lastContentMs": 2631.129874999984, "generationMs": 12.788500000024214, "totalMs": 2643.889957999985, "visibleTokensPerSecond": 547.366774835731, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.02841700002318248, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-24", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:02:29.359Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.043995151841277017, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1753, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 214.91137499996694, "firstEventMs": 488.29658299998846, "firstReasoningMs": null, "firstContentMs": 1877.1987920000101, "lastContentMs": 1877.2070419999654, "generationMs": 102.36591599998064, "totalMs": 1979.5647079999908, "visibleTokensPerSecond": 48.844382929186565, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.008249999955296516, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-24", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:02:31.339Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0008813776364014077, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 18, "reasoningTokens": 10, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2021, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "18", "reasoningTokens": "10", "cachedTokens": "0" }, "timing": { "headersMs": 215.30812499998137, "firstEventMs": 618.1131249999744, "firstReasoningMs": null, "firstContentMs": 2136.91754200001, "lastContentMs": 2137.1009579999954, "generationMs": 118.54987499996787, "totalMs": 2255.467416999978, "visibleTokensPerSecond": 59.04687794906487, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.1834159999853, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-12", "category": "easy", "arm": "smart", "at": "2026-09-26T09:02:34.119Z", "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": 0.005035554625039631, "classifierCostIndex": 0.004405805907088971, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1183, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 3502.3109169999952, "firstEventMs": 4026.446458999999, "firstReasoningMs": null, "firstContentMs": 4552.168166999996, "lastContentMs": 4552.273166999978, "generationMs": 0.3427500000107102, "totalMs": 4552.510917000007, "visibleTokensPerSecond": 32093.362508114584, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.04037499998230487, "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": 408, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-12", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:02:38.672Z", "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": 0.06022927561229297, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2346, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 464.6558330000262, "firstEventMs": 1065.0396670000046, "firstReasoningMs": null, "firstContentMs": 2755.203582999995, "lastContentMs": 2756.4810830000206, "generationMs": 131.4067919999943, "totalMs": 2886.6103749999893, "visibleTokensPerSecond": 83.70952393389587, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 1.262916999985464, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-12", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:02:41.559Z", "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": 0.012068041758278983, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 804, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 203.1759589999565, "firstEventMs": 753.3511669999571, "firstReasoningMs": null, "firstContentMs": 912.8859999999986, "lastContentMs": 913.3474999999744, "generationMs": 110.86195900000166, "totalMs": 1023.7479590000003, "visibleTokensPerSecond": 99.22249344339869, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.387791000015568, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-12", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:02:42.583Z", "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": 0.001837161673419972, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 47, "reasoningTokens": 33, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3996, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "47", "reasoningTokens": "33", "cachedTokens": "0" }, "timing": { "headersMs": 259.77391599997645, "firstEventMs": 1153.2812910000212, "firstReasoningMs": 3227.2751249999856, "firstContentMs": 4251.246915999975, "lastContentMs": 4251.271332999982, "generationMs": 43.27862500003539, "totalMs": 4294.52554100001, "visibleTokensPerSecond": 300.3792287760845, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.016500000027008355, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-0", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:02:47.191Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "26", "evaluation": { "passed": true, "answer": "26", "expected": "26" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028424597879401346, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1210, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2095.4247500000056, "firstEventMs": 2465.171166999964, "firstReasoningMs": null, "firstContentMs": 3144.8913750000065, "lastContentMs": 3144.8913750000065, "generationMs": 172.10020899999654, "totalMs": 3316.991584000003, "visibleTokensPerSecond": 23.242272762144527, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-0", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:02:50.509Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "26", "evaluation": { "passed": true, "answer": "26", "expected": "26" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005696824599979014, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 813, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 678.2295830000076, "firstEventMs": 905.1105410000309, "firstReasoningMs": null, "firstContentMs": 1264.2907499999856, "lastContentMs": 1264.2907499999856, "generationMs": 146.92195799999172, "totalMs": 1411.2127079999773, "visibleTokensPerSecond": 27.225338230247555, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-0", "category": "easy", "arm": "smart", "at": "2026-09-26T09:02:51.920Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "26", "evaluation": { "passed": true, "answer": "26", "expected": "26" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004648506057465661, "classifierCostIndex": 0.00434952761134945, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1792, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1552.280625000014, "firstEventMs": 2411.8607499999925, "firstReasoningMs": null, "firstContentMs": 3340.9738329999964, "lastContentMs": 3340.9738329999964, "generationMs": 23.11416699999245, "totalMs": 3364.087999999989, "visibleTokensPerSecond": 173.05404084003143, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "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": 676, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-0", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:02:55.285Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "26", "evaluation": { "passed": true, "answer": "26", "expected": "26" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.000816441141317344, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 20, "reasoningTokens": 13, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1742, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "20", "reasoningTokens": "13", "cachedTokens": "0" }, "timing": { "headersMs": 653.6698750000214, "firstEventMs": 1240.688291999977, "firstReasoningMs": null, "firstContentMs": 2392.7420000000275, "lastContentMs": 2392.7420000000275, "generationMs": 241.82420899998397, "totalMs": 2634.5662090000114, "visibleTokensPerSecond": 24.81141166474527, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "boolean_constraints", "category": "logic", "arm": "gpt-6-sol", "at": "2026-09-26T09:02:59.231Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/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": 0.2492479136309983, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 340, "reasoningTokens": 325, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4057, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "340", "reasoningTokens": "325", "cachedTokens": "0" }, "timing": { "headersMs": 304.9735000000219, "firstEventMs": 563.9536669999943, "firstReasoningMs": null, "firstContentMs": 4036.003584000049, "lastContentMs": 4045.5598340000142, "generationMs": 345.77041599998483, "totalMs": 4381.774000000034, "visibleTokensPerSecond": 40.489293913452144, "contentChunkCount": 9, "averageContentChunkCharacters": 2, "maxContentStallMs": 6.652874999970663, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "boolean_constraints", "category": "logic", "arm": "smart", "at": "2026-09-26T09:03:03.613Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 2, 01010100", "evaluation": { "passed": true, "answer": "2,01010100", "expected": "2,01010100", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.49010494982221736, "classifierCostIndex": 0.004789201796814465, "promptTokens": 198, "completionTokens": 677, "reasoningTokens": 663, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7076, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "198", "completionTokens": "677", "reasoningTokens": "663", "cachedTokens": "0" }, "timing": { "headersMs": 550.6468749999767, "firstEventMs": 1316.7031669999706, "firstReasoningMs": 3106.625958999968, "firstContentMs": 7626.807124999992, "lastContentMs": 7626.813083999965, "generationMs": 5.432541999965906, "totalMs": 7632.239666999958, "visibleTokensPerSecond": 2392.986561370641, "contentChunkCount": 3, "averageContentChunkCharacters": 6, "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": 189, "classifierFailed": false, "classifierReused": false } }, { "caseId": "boolean_constraints", "category": "logic", "arm": "gpt-6-astra", "at": "2026-09-26T09:03:11.246Z", "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": 0.9269589974194778, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 246, "reasoningTokens": 232, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6978, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "246", "reasoningTokens": "232", "cachedTokens": "0" }, "timing": { "headersMs": 1623.9398330000113, "firstEventMs": 2321.76449999999, "firstReasoningMs": null, "firstContentMs": 8434.67616600002, "lastContentMs": 8498.83791599999, "generationMs": 170.48529199999757, "totalMs": 8605.161458000017, "visibleTokensPerSecond": 76.25291218670162, "contentChunkCount": 8, "averageContentChunkCharacters": 2.125, "maxContentStallMs": 27.923875000036787, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "boolean_constraints", "category": "logic", "arm": "gpt-6-luna", "at": "2026-09-26T09:03:19.851Z", "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": 0.016565570464674197, "classifierCostIndex": 0, "promptTokens": 140, "completionTokens": 450, "reasoningTokens": 435, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5803, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "140", "completionTokens": "450", "reasoningTokens": "435", "cachedTokens": "0" }, "timing": { "headersMs": 337.8108329999959, "firstEventMs": 1053.320000000007, "firstReasoningMs": 3365.4877080000006, "firstContentMs": 6098.81124999997, "lastContentMs": 6100.000999999989, "generationMs": 47.538500000024214, "totalMs": 6146.349749999994, "visibleTokensPerSecond": 294.49814360976615, "contentChunkCount": 9, "averageContentChunkCharacters": 2, "maxContentStallMs": 1.0841670000227168, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-1", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:03:27.518Z", "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": 0.053466410218017256, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1241, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 332.10945899999933, "firstEventMs": 784.1099169999943, "firstReasoningMs": null, "firstContentMs": 1398.4840420000255, "lastContentMs": 1407.6397920000018, "generationMs": 181.64662499999395, "totalMs": 1580.1306670000195, "visibleTokensPerSecond": 44.041555960647585, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 6.466749999963213, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-1", "category": "easy", "arm": "smart", "at": "2026-09-26T09:03:29.098Z", "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": 0.004981170310406728, "classifierCostIndex": 0.0044177109311877155, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1173, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1064.6486659999937, "firstEventMs": 1673.2496249999967, "firstReasoningMs": null, "firstContentMs": 2138.857291000022, "lastContentMs": 2148.286124999984, "generationMs": 107.25016699999105, "totalMs": 2246.107458000013, "visibleTokensPerSecond": 74.59195844422943, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 7.823082999966573, "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": 196, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-1", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:03:31.345Z", "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": 0.0014258972045542346, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 34, "reasoningTokens": 23, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1726, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "34", "reasoningTokens": "23", "cachedTokens": "0" }, "timing": { "headersMs": 262.25854200002505, "firstEventMs": 725.7659170000115, "firstReasoningMs": null, "firstContentMs": 1940.0420840000152, "lastContentMs": 1940.15625, "generationMs": 62.65329099999508, "totalMs": 2002.6953750000102, "visibleTokensPerSecond": 159.60853516858015, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.042000000015832484, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-1", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:03:33.348Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "ORD-24-12", "evaluation": { "passed": true, "answer": "ORD-24-12", "expected": "ORD-24-12" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010716550954341904, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1727, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 438.5379580000299, "firstEventMs": 1207.1125420000171, "firstReasoningMs": null, "firstContentMs": 2164.2739170000423, "lastContentMs": 2164.3387499999953, "generationMs": 38.15870799997356, "totalMs": 2202.432625000016, "visibleTokensPerSecond": 209.65070410679377, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.0232079999987036, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-21", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:03:35.747Z", "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": 0.053466410218017256, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2230, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 423.0866249999963, "firstEventMs": 1757.4827499999665, "firstReasoningMs": null, "firstContentMs": 2061.372583999997, "lastContentMs": 2083.82916699996, "generationMs": 606.867499999993, "totalMs": 2668.24008399999, "visibleTokensPerSecond": 13.182449216674302, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 19.414624999975786, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-21", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:03:38.416Z", "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": 0.0005634593792190121, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1328, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2118.006374999997, "firstEventMs": 2559.812750000041, "firstReasoningMs": null, "firstContentMs": 3379.0152920000255, "lastContentMs": 3379.0500000000466, "generationMs": 93.71520799997961, "totalMs": 3472.730500000005, "visibleTokensPerSecond": 85.3650135418975, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.0293330000131391, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-21", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:03:41.889Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "ORD-164-72", "evaluation": { "passed": true, "answer": "ORD-164-72", "expected": "ORD-164-72" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010716550954341904, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 792, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 192.15104199998314, "firstEventMs": 520.3272920000018, "firstReasoningMs": null, "firstContentMs": 931.3172079999931, "lastContentMs": 931.3530000000028, "generationMs": 56.804624999989755, "totalMs": 988.1218329999829, "visibleTokensPerSecond": 140.83360289767677, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 0.012458999990485609, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-21", "category": "easy", "arm": "smart", "at": "2026-09-26T09:03:42.877Z", "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": 0.004984687703890448, "classifierCostIndex": 0.004421228324671437, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1276, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1582.5086670000455, "firstEventMs": 1886.8297500000335, "firstReasoningMs": null, "firstContentMs": 2655.798999999999, "lastContentMs": 2682.044958000013, "generationMs": 182.12670800002525, "totalMs": 2837.9257080000243, "visibleTokensPerSecond": 43.925463145135694, "contentChunkCount": 5, "averageContentChunkCharacters": 2, "maxContentStallMs": 17.147750000003725, "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": 231, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1686", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:03:46.447Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/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* (50 minutes)\n\n**Central question:** Can Mia and Sebastian achieve their dreams without giving up their relationship?\n\n### 1. Opening: What do musicals make possible? (5 minutes)\n- Ask students: “Why might a film have characters sing or dance instead of simply speaking?”\n- Introduce *La La Land* (2016), directed by Damien Chazelle, as a film that uses musical fantasy to explore ambition, love, and disappointment.\n\n### 2. The story and its setting (5 minutes)\n- Summarize Mia’s pursuit of acting and Sebastian’s ambition to open a jazz club.\n- Discuss Los Angeles as both a place of opportunity and a place where rejection is routine.\n- Note the film’s seasonal chapter titles. Ask: “What do seasons suggest about the course of a relationship?”\n\n### 3. How the film tells its story (15 minutes)\nUse short clips, if available, and have students look for:\n- **Color and costumes:** How do bright colors shape the mood, especially when events are uncertain?\n- **Camera movement and choreography:** How do group numbers and dances make ordinary spaces feel extraordinary?\n- **Music:** What do recurring songs and melodies tell us as Mia and Sebastian’s goals change?\n\nA useful contrast is the opening traffic-jam number, “Another Day of Sun,” and the quieter audition song, “Audition (The Fools Who Dream).” Ask: “What does each performance reveal about pursuing a dream?”\n\n### 4. Dreams, compromise, and the ending (15 minutes)\n- Explore how Mia and Sebastian encourage one another—and how their ambitions pull them in different directions.\n- Discuss Sebastian’s choice to join a successful band: Is it a practical step, a compromise, or both?\n- Examine the final fantasy sequence. **Spoiler warning:** It imagines a life in which the couple stays together, while the film’s reality shows their dreams achieved separately.\n- Ask: “Does the ending feel happy, sad, or both? What does the imagined alternative add?”\n\n### 5. Closing discussion (10 minutes)\nInvite students to choose one claim and support it with a specific scene:\n1. The film celebrates following your dreams.\n2. The film questions what it costs to follow your dreams.\n3. The film is primarily about the people who help us become who we are.\n\n**Takeaway:** *La La Land* uses the pleasures of a musical—song, dance, color, and fantasy—to ask a difficult question: when a dream comes true, what might still be lost?", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.48809245961207043, "classifierCostIndex": 0, "promptTokens": 74, "completionTokens": 706, "reasoningTokens": 144, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7302, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "74", "completionTokens": "706", "reasoningTokens": "144", "cachedTokens": "0" }, "timing": { "headersMs": 273.72574999998324, "firstEventMs": 672.6294579999521, "firstReasoningMs": null, "firstContentMs": 2235.725665999984, "lastContentMs": 7653.94524999999, "generationMs": 5614.036250000005, "totalMs": 7849.761915999989, "visibleTokensPerSecond": 99.92810431175958, "contentChunkCount": 127, "averageContentChunkCharacters": 20.141732283464567, "maxContentStallMs": 1038.105082999973, "finalContentBurstRatio": 0.03127443315089914, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1686", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:03:54.297Z", "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, Love, and the Language of Movies\n\n**Suggested length:** 45–60 minutes \n**Audience:** Students \n**Note:** This outline includes spoilers.\n\n### 1. Opening: Set the Scene (5 minutes)\n- Play a short excerpt from “Another Day of Sun” or show the film’s opening image.\n- Ask students: **What makes a movie feel like a musical—even before anyone starts singing?**\n- Introduce *La La Land* (2016), written and directed by Damien Chazelle, starring Emma Stone and Ryan Gosling.\n\n### 2. A Quick Story Overview (5 minutes)\n- Mia is an aspiring actor working in a coffee shop while auditioning for roles.\n- Sebastian is a jazz pianist who dreams of opening his own club.\n- They meet in Los Angeles and encourage each other’s ambitions as their relationship develops.\n- The film follows both their romance and their pursuit of careers.\n\n### 3. Hollywood and the Musical Tradition (8 minutes)\n- Explain how the film draws on classic Hollywood musicals, including their expressive choreography, vivid color, and heightened emotion.\n- Compare its old-fashioned musical style with its contemporary setting.\n- Discuss how Los Angeles functions as more than a backdrop: it represents opportunity, competition, and reinvention.\n- Ask: **Does the film celebrate Hollywood, criticize it, or do both?**\n\n### 4. Film Form: Color, Music, and Movement (10 minutes)\n- **Color:** Consider how costumes, lighting, and set design shape mood and character.\n- **Music:** Explore how recurring melodies connect different moments in the story.\n- **Choreography and camera movement:** Notice how long takes and sweeping camera moves create a sense of flow.\n- **Visual storytelling:** Discuss how the film communicates emotion through images and movement, sometimes with little dialogue.\n- Invite students to choose one scene and identify how at least two of these elements work together.\n\n### 5. Dreams, Work, and Ambition (8 minutes)\n- Examine the sacrifices each character makes in pursuing a creative career.\n- Discuss the difference between holding onto an artistic ideal and adapting to practical realities.\n- Consider whether success in the film is presented as fulfilling, costly, or both.\n- Ask: **What does the film suggest artists owe to their dreams—and to the people who support them?**\n\n### 6. The Relationship and the Ending (8 minutes)\n- Track how Mia and Sebastian’s ambitions bring them together and eventually pull them in different directions.\n- Analyze the final imagined sequence: What does it show about memory, regret, and roads not taken?\n- Ask: **Is the ending happy, sad, or deliberately unresolved? What makes you think so?**\n\n### 7. Small-Group Activity (5–8 minutes)\nAsk groups to select a scene and discuss:\n1. What does each character want?\n2. How do music, color, or camera work shape our understanding?\n3. What idea about love, ambition, or success does the scene communicate?\n\nHave each group share one observation with the class.\n\n### 8. Closing Reflection (3 minutes)\n- Return to the opening question about what makes a movie feel like a musical.\n- Summarize the film’s central tension: pursuing a dream can transform a life, but it may also involve difficult choices and lasting compromises.\n- **Exit question:** “Which scene best captures the film’s message for you, and why?”", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.030459951147192472, "classifierCostIndex": 0, "promptTokens": 74, "completionTokens": 867, "reasoningTokens": 124, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6113, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "74", "completionTokens": "867", "reasoningTokens": "124", "cachedTokens": "0" }, "timing": { "headersMs": 1641.6522910000058, "firstEventMs": 2213.896999999997, "firstReasoningMs": null, "firstContentMs": 4193.875124999962, "lastContentMs": 7751.571624999982, "generationMs": 3585.7204580000252, "totalMs": 7779.5955829999875, "visibleTokensPerSecond": 206.93191471313372, "contentChunkCount": 129, "averageContentChunkCharacters": 26.906976744186046, "maxContentStallMs": 595.6190829999978, "finalContentBurstRatio": 0.15672716796312303, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1686", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:04:02.078Z", "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 Movies\n\n**Suggested length:** 50–60 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 updates the Hollywood musical.\n- Analyze how color, music, choreography, and cinematography communicate meaning.\n- Discuss the film’s treatment of ambition, romantic love, nostalgia, and artistic authenticity.\n\n### 1. Opening Hook: What Does Success Cost? (5 minutes)\nAsk students:\n> “If achieving your greatest ambition meant giving up an important relationship, would you still pursue it?”\n\nTake a few responses, then introduce this tension as a central question of the film.\n\n**Brief introduction:**\n- Released in 2016; written and directed by Damien Chazelle.\n- Stars Emma Stone as Mia, an aspiring actress, and Ryan Gosling as Sebastian, a jazz pianist.\n- Set in Los Angeles, where the characters’ romance develops alongside their artistic ambitions.\n- Won six Academy Awards, including Best Director and Best Actress.\n\n### 2. Story and Structure: A Romance Told Through Seasons (7 minutes)\n**Plot overview:** \nMia and Sebastian fall in love while pursuing careers in the arts. They encourage each other, but professional pressures and conflicting priorities strain their relationship.\n\n**Key teaching points:**\n- Seasonal chapter headings organize the relationship’s development.\n- The film moves between everyday disappointments and heightened musical fantasy.\n- Its ending complicates the expectation that professional achievement and romantic fulfillment must arrive together.\n\n**Discussion prompt:** \n“How do the seasons shape our expectations about the relationship?”\n\n### 3. The Musical Tradition: Looking Back, Moving Forward (8 minutes)\nExplain that musical numbers can reveal emotions that ordinary dialogue cannot fully express.\n\n**Influences and comparisons:**\n- *Singin’ in the Rain* (1952): Hollywood ambition, romance, and the pleasures of musical performance.\n- *The Umbrellas of Cherbourg* (1964): vivid color, romantic longing, and separation.\n- *The Young Girls of Rochefort* (1967): colorful design and movement through shared public spaces.\n\n**Suggested clip:** “Another Day of Sun,” the opening freeway number.\n\nAsk students:\n- Why turn a traffic jam into a musical performance?\n- How does the sequence introduce optimism and frustration at the same time?\n- What changes when many aspiring artists, rather than just the protagonists, take center stage?\n\n### 4. Visual Storytelling: Color, Space, and Movement (10 minutes)\n**Color and costume**\n- Bright costumes help characters stand out and give scenes a heightened, theatrical quality.\n- Invite students to interpret color in context rather than assume every color has one fixed meaning.\n\n**Camera movement and choreography**\n- Extended shots and mobile camerawork connect viewers to performers’ bodies and surrounding spaces.\n- Dance can express flirtation, resistance, and growing intimacy.\n\n**Los Angeles as a setting**\n- Freeways, studio lots, clubs, and landmarks connect ordinary working life with Hollywood fantasy.\n- The Griffith Observatory sequence makes romantic attraction feel literally weightless.\n\n**Mini-activity:** \nShow the “A Lovely Night” sequence. Ask students to identify one visual choice and explain how it communicates the relationship before the characters openly acknowledge their feelings.\n\n### 5. Music, Ambition, and Artistic Authenticity (10 minutes)\n**Music as storytelling**\n- Justin Hurwitz’s score uses recurring melodies to connect moments across the film.\n- “City of Stars” combines hope with uncertainty.\n- “Audition (The Fools Who Dream)” turns Mia’s vulnerability into a declaration of artistic purpose.\n\n**Sebastian’s conflict**\n- He wants to preserve the jazz he loves and open his own club.\n- His work with Keith’s band raises questions about commercial success, innovation, and compromise.\n- Keith challenges the idea that honoring jazz requires keeping it unchanged.\n\n**Critical perspective**\n- Some critics argue that the film centers a white protagonist as a defender of jazz while giving limited attention to the genre’s Black origins and communities.\n- Use this criticism to examine whose expertise and artistic ambitions the story foregrounds.\n\n**Discussion prompt:** \n“Is Sebastian protecting an artistic tradition, resisting change, or doing both?”\n\n### 6. The Ending: Happiness and Loss Together (8 minutes)\n**Suggested clip:** The final fantasy montage and exchange of looks.\n\n**Key questions:**\n- What does the imagined alternative life reveal about the characters’ desires?\n- How does the montage use musical fantasy to revisit earlier choices?\n- Does the ending suggest that the relationship failed, or that a meaningful relationship can end?\n- How do Mia and Sebastian contribute to each other’s eventual achievements?\n\n**Interpretive takeaway:** \nThe ending can be read as holding fulfillment and regret together: their love mattered, even though it did not become a shared future.\n\n### 7. Conclusion and Exit Ticket (2 minutes)\nReturn to the opening question about the cost of success.\n\n**Closing idea:** \n*La La Land* uses the beauty of the movie musical not simply to celebrate dreams, but also to explore what pursuing them can demand.\n\n**Exit ticket:** \n“In two or three sentences, explain how one scene uses music or visual style to communicate an idea about love or ambition.”\n\n### Optional Follow-Up Assignment\nWrite a 500-word analysis of one musical sequence. Make an argument about its meaning and support it with specific observations about sound, color, framing, editing, or performance.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 4.200783128719339, "classifierCostIndex": 0, "promptTokens": 74, "completionTokens": 1227, "reasoningTokens": 60, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 23566, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "74", "completionTokens": "1227", "reasoningTokens": "60", "cachedTokens": "0" }, "timing": { "headersMs": 3066.965749999974, "firstEventMs": 3308.9718329999596, "firstReasoningMs": null, "firstContentMs": 5423.8597079999745, "lastContentMs": 26469.006374999997, "generationMs": 21086.81579199998, "totalMs": 26510.675499999954, "visibleTokensPerSecond": 55.29521438900049, "contentChunkCount": 252, "averageContentChunkCharacters": 23.321428571428573, "maxContentStallMs": 815.5123749999912, "finalContentBurstRatio": 0.11723668538369916, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1686", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:04:28.589Z", "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: Play the opening \"Another Day of Sun\" sequence or ask students about their favorite movie musicals\n- Brief overview of the film (2016, directed by Damien Chazelle, starring Ryan Gosling and Emma Stone)\n- Preview of what the lecture will cover\n\n**II. Context and Background**\n- Chazelle's inspiration: classic Hollywood musicals (Singin' in the Rain, The Umbrellas of Cherbourg)\n- The film's place in the \"neo-musical\" revival\n- Production background (shot in CinemaScope, real locations in LA)\n\n**III. Themes and Narrative Structure**\n- Dreams vs. reality/practicality\n- Compromise in relationships and career\n- The \"epilogue\" fantasy sequence and its narrative function\n- Nostalgia for a bygone era of jazz and Hollywood glamour\n\n**IV. Visual and Cinematic Techniques**\n- Use of color (especially Mia's dress progression)\n- Long takes and choreography (e.g., the freeway opening number)\n- Lighting and how it reflects emotional states\n- Homages to classic film techniques (rear projection, technicolor palette)\n\n**V. Music and Sound**\n- Justin Hurwitz's score and songs (\"City of Stars,\" \"Audition\")\n- How music functions as storytelling, not just decoration\n- Jazz as a thematic element (Sebastian's passion)\n\n**VI. Character Analysis**\n- Mia and Sebastian's arcs\n- Supporting characters and their narrative purposes\n- Symbolism in character choices (career paths, relationship decisions)\n\n**VII. Critical Reception and Cultural Impact**\n- Awards and controversies (the Oscars mix-up moment could be a fun aside)\n- Critical debates: nostalgia vs. innovation, diversity critiques\n- Its influence on later films/musicals\n\n**VIII. Discussion Questions/Activities**\n- Was the ending happy, sad, or bittersweet? Why?\n- Compare a scene with its classic Hollywood inspiration\n- Small group discussion: what does the film say about pursuing dreams?\n\n**IX. Conclusion**\n- Recap main takeaways\n- Connect to broader themes in film studies (genre revival, homage vs. originality)\n\nWould you like me to expand any section, suggest specific film clips to include, or tailor this for a particular course level (intro to film vs. advanced film studies)?", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6176534840350651, "classifierCostIndex": 0.004553536433405217, "promptTokens": 102, "completionTokens": 885, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10371, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "102", "completionTokens": "885", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 803.5181660000235, "firstEventMs": 1497.758415999997, "firstReasoningMs": null, "firstContentMs": 1497.779833000037, "lastContentMs": 11164.389208000037, "generationMs": 9680.965417, "totalMs": 11178.745250000036, "visibleTokensPerSecond": 91.31320709478783, "contentChunkCount": 211, "averageContentChunkCharacters": 11.246445497630331, "maxContentStallMs": 652.4477910000132, "finalContentBurstRatio": 0.12515802781289506, "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": 183, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2752", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:04:41.077Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "The opposite of youth is not age, but *the loss of curiosity* and *the surrender of possibility*.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01876597065747065, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 536, "reasoningTokens": 508, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6241, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "536", "reasoningTokens": "508", "cachedTokens": "0" }, "timing": { "headersMs": 7217.5773340000305, "firstEventMs": 7640.605792000017, "firstReasoningMs": 10077.241917000036, "firstContentMs": 13425.809624999994, "lastContentMs": 13459.70437500003, "generationMs": 828.2821669999976, "totalMs": 14254.091791999992, "visibleTokensPerSecond": 32.597587000807756, "contentChunkCount": 22, "averageContentChunkCharacters": 4.409090909090909, "maxContentStallMs": 33.74908300000243, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2752", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:04:55.330Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "**The opposite of youth is not age, but cynicism.** In this saying, *youth* means staying open to possibility, regardless of how old you are.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.17836769998127122, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 256, "reasoningTokens": 215, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2679, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "256", "reasoningTokens": "215", "cachedTokens": "0" }, "timing": { "headersMs": 1876.1956670000218, "firstEventMs": 2339.4313340000226, "firstReasoningMs": null, "firstContentMs": 4315.769625000015, "lastContentMs": 4546.903417000023, "generationMs": 245.3654169999645, "totalMs": 4561.13504199998, "visibleTokensPerSecond": 163.02215890516382, "contentChunkCount": 34, "averageContentChunkCharacters": 4.147058823529412, "maxContentStallMs": 153.8777500000433, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2752", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:04:59.882Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "…*stagnation*.\n\nYouth is not merely a matter of years, but of *curiosity, openness, and the willingness to grow*. We can age without losing those qualities—and lose them while still young.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.667781887837032, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 190, "reasoningTokens": 140, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5552, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "190", "reasoningTokens": "140", "cachedTokens": "0" }, "timing": { "headersMs": 830.5215000000317, "firstEventMs": 1159.8160420000204, "firstReasoningMs": 5052.857000000018, "firstContentMs": 6195.386375000002, "lastContentMs": 6354.3513750000275, "generationMs": 189.5779999999795, "totalMs": 6384.964374999981, "visibleTokensPerSecond": 258.4688096720363, "contentChunkCount": 38, "averageContentChunkCharacters": 4.947368421052632, "maxContentStallMs": 156.58166699996218, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2752", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:05:06.258Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "The opposite of youth is not age, but *the loss of curiosity and openness*.", "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": 0.010842771266661555, "classifierCostIndex": 0.004426910267991292, "promptTokens": 37, "completionTokens": 178, "reasoningTokens": 155, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3780, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "178", "reasoningTokens": "155", "cachedTokens": "0" }, "timing": { "headersMs": 918.9185000000289, "firstEventMs": 1653.825583000027, "firstReasoningMs": 3274.3017080000136, "firstContentMs": 4661.989915999991, "lastContentMs": 4662.375666000007, "generationMs": 388.1110420000041, "totalMs": 5050.100957999995, "visibleTokensPerSecond": 56.68480826165149, "contentChunkCount": 17, "averageContentChunkCharacters": 4.411764705882353, "maxContentStallMs": 0.34583299997029826, "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": 258, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-5", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:05:11.551Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "76", "evaluation": { "passed": true, "answer": "76", "expected": "76" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028424597879401346, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1672, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 197.01641699997708, "firstEventMs": 945.2095419999678, "firstReasoningMs": null, "firstContentMs": 1857.7404579999857, "lastContentMs": 1857.7404579999857, "generationMs": 243.67525000002934, "totalMs": 2101.415708000015, "visibleTokensPerSecond": 16.41529043265378, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-5", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:05:13.652Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "76", "evaluation": { "passed": true, "answer": "76", "expected": "76" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005696824599979014, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3246, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 325.9745000000112, "firstEventMs": 2121.0774160000146, "firstReasoningMs": null, "firstContentMs": 2632.374125000031, "lastContentMs": 2632.374125000031, "generationMs": 1230.8763329999638, "totalMs": 3863.250457999995, "visibleTokensPerSecond": 3.249717207780709, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 0, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-5", "category": "easy", "arm": "smart", "at": "2026-09-26T09:05:17.513Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "76", "evaluation": { "passed": true, "answer": "76", "expected": "76" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004652023450949379, "classifierCostIndex": 0.004353045004833169, "promptTokens": 17, "completionTokens": 5, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1447, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "5", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1532.4474169999594, "firstEventMs": 1929.6569169999566, "firstReasoningMs": null, "firstContentMs": 2968.510707999987, "lastContentMs": 2968.510707999987, "generationMs": 0.39779199997428805, "totalMs": 2968.9084999999614, "visibleTokensPerSecond": 10055.506395952023, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "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": 189, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-5", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:05:20.481Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "76", "evaluation": { "passed": true, "answer": "76", "expected": "76" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.000816441141317344, "classifierCostIndex": 0, "promptTokens": 17, "completionTokens": 20, "reasoningTokens": 13, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3014, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "17", "completionTokens": "20", "reasoningTokens": "13", "cachedTokens": "0" }, "timing": { "headersMs": 646.7899580000085, "firstEventMs": 1027.8859999999986, "firstReasoningMs": 2967.529416000005, "firstContentMs": 3685.008375000034, "lastContentMs": 3685.008375000034, "generationMs": 0.20520799997029826, "totalMs": 3685.2135830000043, "visibleTokensPerSecond": 29238.626178650138, "contentChunkCount": 1, "averageContentChunkCharacters": 2, "maxContentStallMs": null, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "constrained_strings", "category": "combinatorics", "arm": "gpt-6-astra", "at": "2026-09-26T09:05:24.471Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Let \\(k\\) be the number of A’s. Since no two A’s are adjacent, \\(0\\le k\\le7\\).\n\nThe number of ways to choose \\(k\\) nonadjacent positions among 14 is\n\\[\n\\binom{15-k}{k}.\n\\]\nFrom the remaining \\(14-k\\) positions, choose exactly four for C; all others must be 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": 1.8003514741910172, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 520, "reasoningTokens": 367, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 9300, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "520", "reasoningTokens": "367", "cachedTokens": "0" }, "timing": { "headersMs": 203.11758299998473, "firstEventMs": 1023.3340420000022, "firstReasoningMs": 7870.198458000028, "firstContentMs": 9144.047625000007, "lastContentMs": 9473.697916999983, "generationMs": 367.0234170000185, "totalMs": 9511.071042000025, "visibleTokensPerSecond": 414.1425123291039, "contentChunkCount": 72, "averageContentChunkCharacters": 5.402777777777778, "maxContentStallMs": 228.7058749999851, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "constrained_strings", "category": "combinatorics", "arm": "smart", "at": "2026-09-26T09:05:33.980Z", "model": "anthropic/claude-fable-5-1", "loggedModel": "anthropic/claude-fable-5-1", "content": "We need strings of length 14 over {A,B,C} with exactly 4 C's and no \"AA\" substring.\n\nChoose positions of the 4 C's: they split the remaining 10 positions (A/B) into 5 blocks (possibly empty) of lengths summing to 10. The C's separate blocks, so AA restriction applies within each block. Number of A/B strings of length n with no AA is F(n+2) (Fibonacci): f(0)=1, f(1)=2, f(2)=3, f(3)=5, f(4)=8, f(5)=13, f(6)=21, f(7)=34, f(8)=55, f(9)=89, f(10)=144.\n\nTotal = sum over compositions (n1,...,n5) of 10 into nonnegative parts of ∏ f(ni) = coefficient of x^10 in F(x)^5 where F(x) = 1/(1−x−x²).\n\n1/(1−x−x²)^5: coefficient of x^10. Use formula: coefficient of x^n in (1−x−x²)^{-5} = Σ_k C(n−k+4, 4)·C(n−k, k) where we choose j = n−k terms... Let's do it: (1−(x+x²))^{-5} = Σ_m C(m+4,4)(x+x²)^m. (x+x²)^m = Σ_k C(m,k) x^{m+k}. Need m+k=10, so m=10−k, k ≤ m.\nk=0: m=10: C(14,4)·1 = 1001\nk=1: m=9: C(13,4)·9 = 715·9 = 6435\nk=2: m=8: C(12,4)·28 = 495·28 = 13860\nk=3: m=7: C(11,4)·35 = 330·35 = 11550\nk=4: m=6: C(10,4)·15 = 210·15 = 3150\nk=5: m=5: C(9,4)·1 = 126\n\nSum: 1001+6435=7436; +13860=21296; +11550=32846; +3150=35996; +126=36122.\n\nFINAL: 36122", "evaluation": { "passed": false, "answer": "36122", "expected": "229433", "detail": "36122 != 229433" }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 2.3691103478307123, "classifierCostIndex": 0.0044972581376656945, "promptTokens": 85, "completionTokens": 682, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 9660, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "85", "completionTokens": "682", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1312.1978750000126, "firstEventMs": 3286.8005410000333, "firstReasoningMs": null, "firstContentMs": 3286.836707999988, "lastContentMs": 11070.585415999987, "generationMs": 7783.900625000009, "totalMs": 11070.737332999997, "visibleTokensPerSecond": 87.48827005997384, "contentChunkCount": 107, "averageContentChunkCharacters": 10.663551401869158, "maxContentStallMs": 1536.8904169999878, "finalContentBurstRatio": 0.09815950920245399, "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": 453, "classifierFailed": false, "classifierReused": false } }, { "caseId": "constrained_strings", "category": "combinatorics", "arm": "gpt-6-sol", "at": "2026-09-26T09:05:45.050Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Let \\(k\\) be the number of A’s. The other \\(14-k\\) positions contain four C’s, which can be chosen in \\(\\binom{14-k}{4}\\) ways. To avoid AA, place the \\(k\\) A’s in distinct gaps before, between, or after those other characters, giving \\(\\binom{15-k}{k}\\) choices. 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": 0.365801481666831, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 528, "reasoningTokens": 398, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7272, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "528", "reasoningTokens": "398", "cachedTokens": "0" }, "timing": { "headersMs": 2865.910125000053, "firstEventMs": 3479.6473750000005, "firstReasoningMs": 6422.086583000026, "firstContentMs": 9811.034125000006, "lastContentMs": 10074.035625000019, "generationMs": 271.8379169999971, "totalMs": 10082.872042000003, "visibleTokensPerSecond": 474.5474855886325, "contentChunkCount": 66, "averageContentChunkCharacters": 5.378787878787879, "maxContentStallMs": 156.2900410000002, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "constrained_strings", "category": "combinatorics", "arm": "gpt-6-luna", "at": "2026-09-26T09:05:55.133Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 229433", "evaluation": { "passed": true, "answer": "229433", "expected": "229433", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.05082024804334164, "classifierCostIndex": 0, "promptTokens": 61, "completionTokens": 1460, "reasoningTokens": 1449, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 8796, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "61", "completionTokens": "1460", "reasoningTokens": "1449", "cachedTokens": "0" }, "timing": { "headersMs": 667.82483399997, "firstEventMs": 1385.7189590000198, "firstReasoningMs": null, "firstContentMs": 9474.570791999984, "lastContentMs": 9474.60941699997, "generationMs": 0.24183300003642216, "totalMs": 9474.81262500002, "visibleTokensPerSecond": 41350.84954697627, "contentChunkCount": 5, "averageContentChunkCharacters": 2.6, "maxContentStallMs": 0.017042000021319836, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2273", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:06:04.823Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "The sixth result **cannot be uniquely determined**—the number-goblins have left too many wiggle-slots.\n\nLet the results be \\(x_1,\\ldots,x_{11}\\). Then\n\\[\n\\sum_{i=1}^{11}x_i=11(51)=561,\n\\qquad\n\\sum_{i=1}^{5}x_i=5(49)=245.\n\\]\nSo, by subtraction-sorcery,\n\\[\nx_6+x_7+\\cdots+x_{11}=561-245=316.\n\\]\n\nThe last nine give\n\\[\nx_3+\\cdots+x_{11}=9(52)=468,\n\\]\nhence\n\\[\nx_3+x_4+x_5=468-316=152.\n\\]\nBut this does not pluck \\(x_6\\) from the algebraic soup.\n\nFor example, both lists satisfy **all** the given averages:\n\\[\n(46,47,50,51,51,\\boxed{51},53,53,53,53,53),\n\\]\n\\[\n(46,47,50,51,51,\\boxed{56},52,52,52,52,52).\n\\]\n\nThus, \\(\\boxed{\\text{insufficient information}}\\).\n\nP.P.S The sixth number remains a slippery math-noodle; another condition is needed.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.6339205901342093, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 470, "reasoningTokens": 179, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 8317, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "470", "reasoningTokens": "179", "cachedTokens": "0" }, "timing": { "headersMs": 1580.0694169999915, "firstEventMs": 2137.6737500000163, "firstReasoningMs": null, "firstContentMs": 6544.850166999968, "lastContentMs": 9862.497791999951, "generationMs": 3338.1000420000637, "totalMs": 9882.950209000031, "visibleTokensPerSecond": 86.87576655918404, "contentChunkCount": 96, "averageContentChunkCharacters": 7.697916666666667, "maxContentStallMs": 394.4546669999836, "finalContentBurstRatio": 0.2543978349120433, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2273", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:06:14.706Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# The Curious Case of the Sixth Result\n\nYo, let's summon ye olde notation and wrangle this beast, shall we? 🎩✨\n\n**The Sacred Totals:**\n\nBehold! The grand total of all eleven mystical results:\n$$S_{11} = 11 \\times 51 = 561$$\n\nNow conjure the sum of the first five wee lads:\n$$S_5 = 5 \\times 49 = 245$$\n\nAnd summon the sum of the mighty last nine:\n$$S_9 = 9 \\times 52 = 468$$\n\n**The Overlap Conundrum:**\n\nHere's the twist, dear reader — the first five and the last nine *overlap* at the sixth result! Together, they cover all 11 spots, but the sixth one gets counted **twice** (once as the last of the \"first five,\" and once... wait, actually the sixth is the *first* of the \"last nine\"). So:\n\n$$S_5 + S_9 = S_{11} + x_6$$\n\nwhere $x_6$ be our mysterious sixth result, counted double in this reckoning.\n\n**Solving the Riddle:**\n\n$$245 + 468 = 561 + x_6$$\n\n$$713 = 561 + x_6$$\n\n$$x_6 = 713 - 561$$\n\n$$x_6 = 152$$\n\n**Behold, the sixth result is 152!** 🎉\n\n---\n\nP.P.S. Yes, I skipped straight to P.P.S. because P.S. felt too mainstream for such a glorious overlap-based derivation. Also, double-check your data if 152 seems mad compared to averages of 49-52 — but mathematically, the notation doth not lie!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.37779985197725946, "classifierCostIndex": 0.004539466859470336, "promptTokens": 81, "completionTokens": 535, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7236, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "81", "completionTokens": "535", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1368.520583000034, "firstEventMs": 2211.6685829999624, "firstReasoningMs": null, "firstContentMs": 2211.691041999962, "lastContentMs": 8461.974208, "generationMs": 6316.944750000024, "totalMs": 8528.635791999986, "visibleTokensPerSecond": 84.534537048151, "contentChunkCount": 136, "averageContentChunkCharacters": 8.830882352941176, "maxContentStallMs": 994.8966249999357, "finalContentBurstRatio": 0.13072439633638636, "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": "ifeval-2273", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:06:23.235Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "The sixth result is a **slippery number-goblin**: the averages don’t pin it down.\n\nThe first five sum to \\(5(49)=245\\), while all eleven sum to \\(11(51)=561\\). So results 6 through 11 must satisfy\n\n\\[\nx_6+x_7+\\cdots+x_{11}=561-245=316.\n\\]\n\nThat tells us their *combined* value, not \\(x_6\\) alone. The last-nine average adds no clue that isolates it. Thus the sixth result **cannot be determined**.\n\nP.P.S. The sum-goblin knows \\(316\\), but refuses to reveal its six ingredients.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3825956827079471, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 552, "reasoningTokens": 403, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5228, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "552", "reasoningTokens": "403", "cachedTokens": "0" }, "timing": { "headersMs": 2273.992542000022, "firstEventMs": 2387.8747079999885, "firstReasoningMs": null, "firstContentMs": 6460.180916999932, "lastContentMs": 7688.932999999961, "generationMs": 1228.8824580000946, "totalMs": 7689.063375000027, "visibleTokensPerSecond": 120.43462662886235, "contentChunkCount": 71, "averageContentChunkCharacters": 6.732394366197183, "maxContentStallMs": 765.1420830000425, "finalContentBurstRatio": 0.33472803347280333, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2273", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:06:30.925Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "The sixth result is **not uniquely determined**—the arithmetic cauldron has too many unknown ingredients.\n\n\\[\n\\sum_{1}^{11}x_i=11(51)=561,\\qquad\n\\sum_{1}^{5}x_i=5(49)=245,\\qquad\n\\sum_{3}^{11}x_i=9(52)=468.\n\\]\n\nThe overlapping trio, results 3–5, therefore sums to\n\n\\[\n245+468-561=152.\n\\]\n\nBut that only tells us the combined sum of results 6–11 is \\(468-152=316\\), not the sixth result by itself. For instance, \\(x_6\\) could be \\(50\\) or \\(60\\), with the other five results adjusted to keep their sum at \\(316\\).\n\n**P.P.S.** The sixth result remains a mathematical chameleon until more information arrives.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.026908736572282734, "classifierCostIndex": 0, "promptTokens": 65, "completionTokens": 766, "reasoningTokens": 571, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5916, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "65", "completionTokens": "766", "reasoningTokens": "571", "cachedTokens": "0" }, "timing": { "headersMs": 283.60841599991545, "firstEventMs": 638.1166249999078, "firstReasoningMs": null, "firstContentMs": 5526.867915999959, "lastContentMs": 6170.9213329999475, "generationMs": 682.3995420000283, "totalMs": 6209.2674579999875, "visibleTokensPerSecond": 284.2909293746155, "contentChunkCount": 80, "averageContentChunkCharacters": 7.5625, "maxContentStallMs": 129.2057499999646, "finalContentBurstRatio": 0.8231404958677686, "buffered": true }, "error": null, "routing": null }, { "caseId": "assignment", "category": "algorithms", "arm": "gpt-6-sol", "at": "2026-09-26T09:06:37.366Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "The minimum total cost is **21**. One optimal assignment is workers 1–6 to jobs **2, 1, 3, 5, 4, 6**, respectively, costing \\(5+2+3+1+3+7=21\\).\n\nThe sum of the six row minima is 18, but workers 3 and 6 both have their minimum in job 3. Resolving that conflict while keeping all jobs distinct adds at least 3, so 21 is optimal.\n\nFINAL: 21", "evaluation": { "passed": true, "answer": "21", "expected": "21", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6070277088894761, "classifierCostIndex": 0, "promptTokens": 142, "completionTokens": 868, "reasoningTokens": 753, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6841, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "142", "completionTokens": "868", "reasoningTokens": "753", "cachedTokens": "0" }, "timing": { "headersMs": 315.862208000035, "firstEventMs": 725.7155829999829, "firstReasoningMs": null, "firstContentMs": 6872.415166000021, "lastContentMs": 7178.0625, "generationMs": 305.7992920000106, "totalMs": 7178.214458000031, "visibleTokensPerSecond": 372.7935380569686, "contentChunkCount": 64, "averageContentChunkCharacters": 5.265625, "maxContentStallMs": 305.2393329999177, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "assignment", "category": "algorithms", "arm": "gpt-6-luna", "at": "2026-09-26T09:06:44.544Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Assign workers 1–6 to jobs 2, 1, 3, 5, 4, 6, respectively. The costs sum to \\(5+2+3+1+3+7=21\\), which is the minimum by the assignment method.\n\nFINAL: 21", "evaluation": { "passed": true, "answer": "21", "expected": "21", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.06235865151359123, "classifierCostIndex": 0, "promptTokens": 142, "completionTokens": 1777, "reasoningTokens": 1710, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10819, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "142", "completionTokens": "1777", "reasoningTokens": "1710", "cachedTokens": "0" }, "timing": { "headersMs": 256.8499169999268, "firstEventMs": 715.1284169999417, "firstReasoningMs": 2657.6134590000147, "firstContentMs": 10715.585834000027, "lastContentMs": 11082.336833999958, "generationMs": 381.3692909999518, "totalMs": 11096.955124999979, "visibleTokensPerSecond": 173.06060439986592, "contentChunkCount": 47, "averageContentChunkCharacters": 3.25531914893617, "maxContentStallMs": 358.95241699996404, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "assignment", "category": "algorithms", "arm": "gpt-6-astra", "at": "2026-09-26T09:06:55.642Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Assign workers 1–6 to jobs **2, 1, 3, 5, 4, 6**, respectively. The total cost is\n\\(5+2+3+1+3+7=21\\), which is minimal.\n\nFINAL: 21", "evaluation": { "passed": true, "answer": "21", "expected": "21", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.9296177139832031, "classifierCostIndex": 0, "promptTokens": 142, "completionTokens": 542, "reasoningTokens": 479, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 11431, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "142", "completionTokens": "542", "reasoningTokens": "479", "cachedTokens": "0" }, "timing": { "headersMs": 1214.2218329999596, "firstEventMs": 1543.360166999977, "firstReasoningMs": 11839.633333000005, "firstContentMs": 12539.818749999977, "lastContentMs": 12660.105417000013, "generationMs": 128.54195800004527, "totalMs": 12668.360708000022, "visibleTokensPerSecond": 482.332780398274, "contentChunkCount": 45, "averageContentChunkCharacters": 2.8666666666666667, "maxContentStallMs": 116.36262499995064, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "assignment", "category": "algorithms", "arm": "smart", "at": "2026-09-26T09:07:08.310Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "FINAL: 21", "evaluation": { "passed": true, "answer": "21", "expected": "21", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.7303448187414084, "classifierCostIndex": 0.004803271370749345, "promptTokens": 182, "completionTokens": 1035, "reasoningTokens": 1026, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10695, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "182", "completionTokens": "1035", "reasoningTokens": "1026", "cachedTokens": "0" }, "timing": { "headersMs": 988.1947090000613, "firstEventMs": 1933.9780840000603, "firstReasoningMs": 4353.933792000054, "firstContentMs": 11680.232542000012, "lastContentMs": 11680.238374999957, "generationMs": 14.737083000014536, "totalMs": 11694.969625000027, "visibleTokensPerSecond": 542.8482692261493, "contentChunkCount": 2, "averageContentChunkCharacters": 4.5, "maxContentStallMs": 0.00583299994468689, "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": 164, "classifierFailed": false, "classifierReused": false } }, { "caseId": "number_theory_crt", "category": "math", "arm": "gpt-6-luna", "at": "2026-09-26T09:07:20.230Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "FINAL: 17401", "evaluation": { "passed": true, "answer": "17401", "expected": "17401", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.019977442143882713, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 564, "reasoningTokens": 553, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 11639, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "564", "reasoningTokens": "553", "cachedTokens": "0" }, "timing": { "headersMs": 7321.463542000041, "firstEventMs": 7615.584249999956, "firstReasoningMs": 12251.98762499995, "firstContentMs": 18920.884416999994, "lastContentMs": 18920.906583999982, "generationMs": 127.51925000001211, "totalMs": 19048.403667000006, "visibleTokensPerSecond": 78.41953273720674, "contentChunkCount": 5, "averageContentChunkCharacters": 2.4, "maxContentStallMs": 0.016333000035956502, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "number_theory_crt", "category": "math", "arm": "smart", "at": "2026-09-26T09:07:39.279Z", "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": 0.2915551224531839, "classifierCostIndex": 0.004550019039921496, "promptTokens": 94, "completionTokens": 405, "reasoningTokens": 395, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5858, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "94", "completionTokens": "405", "reasoningTokens": "395", "cachedTokens": "0" }, "timing": { "headersMs": 940.6770419999957, "firstEventMs": 1527.3384589999914, "firstReasoningMs": 4238.732792000053, "firstContentMs": 6690.746000000043, "lastContentMs": 6690.75229199999, "generationMs": 750.6499169999734, "totalMs": 7441.395917000016, "visibleTokensPerSecond": 11.989610331230235, "contentChunkCount": 2, "averageContentChunkCharacters": 6, "maxContentStallMs": 0.006291999947279692, "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": 308, "classifierFailed": false, "classifierReused": false } }, { "caseId": "number_theory_crt", "category": "math", "arm": "gpt-6-astra", "at": "2026-09-26T09:07:46.721Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Write \\(x=11+37a\\). Modulo \\(41\\),\n\\[\n11-4a\\equiv17\\pmod{41},\n\\]\nso \\(a\\equiv19\\pmod{41}\\). Thus \\(x=714+1517b\\).\n\nModulo \\(43\\),\n\\[\n26+12b\\equiv29\\pmod{43},\n\\]\nso \\(12b\\equiv3\\), giving \\(b\\equiv11\\pmod{43}\\).\n\nTherefore\n\\[\nx=714+1517(11)+37\\cdot41\\cdot43\\,k\n=17401+65231k.\n\\]\nThe smallest nonnegative value occurs at \\(k=0\\).\n\nFINAL: 17401", "evaluation": { "passed": true, "answer": "17401", "expected": "17401", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.1468021779483994, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 325, "reasoningTokens": 160, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5809, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "325", "reasoningTokens": "160", "cachedTokens": "0" }, "timing": { "headersMs": 1686.6053339999635, "firstEventMs": 2294.0955420000246, "firstReasoningMs": null, "firstContentMs": 5919.70770899998, "lastContentMs": 7460.82349999994, "generationMs": 1581.2388329999521, "totalMs": 7500.946541999932, "visibleTokensPerSecond": 103.71614747713761, "contentChunkCount": 75, "averageContentChunkCharacters": 4.546666666666667, "maxContentStallMs": 340.7710000000661, "finalContentBurstRatio": 0.31085043988269795, "buffered": false }, "error": null, "routing": null }, { "caseId": "number_theory_crt", "category": "math", "arm": "gpt-6-sol", "at": "2026-09-26T09:07:54.223Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Write \\(x=11+37a\\). The condition modulo \\(41\\) gives \\(a\\equiv19\\pmod{41}\\), so \\(x=714+1517b\\). Modulo \\(43\\), this becomes \\(12b\\equiv3\\pmod{43}\\), giving \\(b\\equiv11\\pmod{43}\\). Taking \\(b=11\\) yields the smallest nonnegative solution.\n\nFINAL: 17401", "evaluation": { "passed": true, "answer": "17401", "expected": "17401", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.24243905155270468, "classifierCostIndex": 0, "promptTokens": 70, "completionTokens": 344, "reasoningTokens": 241, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3289, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "70", "completionTokens": "344", "reasoningTokens": "241", "cachedTokens": "0" }, "timing": { "headersMs": 288.06487500004005, "firstEventMs": 868.0239160000347, "firstReasoningMs": null, "firstContentMs": 3521.2345830000704, "lastContentMs": 3568.3150000000605, "generationMs": 70.35429199994542, "totalMs": 3591.588875000016, "visibleTokensPerSecond": 1449.804938696265, "contentChunkCount": 60, "averageContentChunkCharacters": 4.216666666666667, "maxContentStallMs": 40.330125000094995, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-13", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:07:58.012Z", "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": 0.000447114825526731, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1635, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 977.0062080000062, "firstEventMs": 1285.1217080000788, "firstReasoningMs": null, "firstContentMs": 2282.0331250000745, "lastContentMs": 2282.1321250000037, "generationMs": 333.00533299997915, "totalMs": 2615.0384580000537, "visibleTokensPerSecond": 21.020684374446454, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 0.05266699998173863, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-13", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:08:00.628Z", "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": 0.046018329516239895, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1132, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 614.2535829999251, "firstEventMs": 893.6499159999657, "firstReasoningMs": null, "firstContentMs": 1561.2500829999335, "lastContentMs": 1616.2422500000102, "generationMs": 191.6674580000108, "totalMs": 1752.9175409999443, "visibleTokensPerSecond": 41.73895810732539, "contentChunkCount": 5, "averageContentChunkCharacters": 3.6, "maxContentStallMs": 54.008917000028305, "finalContentBurstRatio": 0.05555555555555555, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-13", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:08:02.381Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "gateway-108-ready", "evaluation": { "passed": true, "answer": "gateway-108-ready", "expected": "gateway-108-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008543884056320937, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 711, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 222.29791700001806, "firstEventMs": 600.0773749999935, "firstReasoningMs": null, "firstContentMs": 817.2887089999858, "lastContentMs": 832.3228750000708, "generationMs": 120.76600000006147, "totalMs": 938.0547090000473, "visibleTokensPerSecond": 57.963334050945114, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 8.98383299994748, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-13", "category": "easy", "arm": "smart", "at": "2026-09-26T09:08:03.319Z", "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": 0.004828298978229661, "classifierCostIndex": 0.00438118415270293, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1377, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2733.7912090000464, "firstEventMs": 3083.6169590000063, "firstReasoningMs": null, "firstContentMs": 3861.554791999981, "lastContentMs": 3861.60854200006, "generationMs": 175.77175000007264, "totalMs": 4037.3265420000535, "visibleTokensPerSecond": 39.82437450840142, "contentChunkCount": 4, "averageContentChunkCharacters": 4.25, "maxContentStallMs": 0.020417000050656497, "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": 219, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2691", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:08:07.573Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"Dear Darius,\n\nI’m excited to apply for the [Position] role at [Company] in Ventura. I bring [relevant experience or skill], a reputation for getting things done, and the ability to stay calm when a to-do list starts reproducing overnight.\n\nI’m especially interested in joining a team where I can contribute, keep learning, and help make good work happen. Ventura’s ocean views are a lovely bonus; I promise not to mistake the office for a beach picnic.\n\nI’d welcome the chance to talk about how my experience could help [Company]. Thanks for considering my application—and for reading a cover letter that made it all the way to the end without mentioning my passion for synergy.\n\nBest, \n[Your Name]\"\n", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.014354482807061824, "classifierCostIndex": 0.004419875481023851, "promptTokens": 37, "completionTokens": 280, "reasoningTokens": 125, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3462, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "280", "reasoningTokens": "125", "cachedTokens": "0" }, "timing": { "headersMs": 2577.579083999968, "firstEventMs": 2885.364249999984, "firstReasoningMs": null, "firstContentMs": 4830.420500000007, "lastContentMs": 5983.911124999984, "generationMs": 1209.292291999911, "totalMs": 6039.712791999918, "visibleTokensPerSecond": 127.34721044596829, "contentChunkCount": 73, "averageContentChunkCharacters": 9.616438356164384, "maxContentStallMs": 745.5350000000326, "finalContentBurstRatio": 0.2336182336182336, "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": 265, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2691", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:08:13.613Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "\"Dear Darius,\n\nI’m excited to apply for the [Job Title] position at [Company Name] in Ventura. I bring a practical approach to problem-solving, a willingness to learn, and the ability to stay calm when plans change—which, I understand, can happen even on a day that starts with perfect beach weather.\n\nI’d love to help your team do great work, keep customers happy, and make the occasional Monday feel a little less like a Monday. I’m dependable, easy to work with, and ready to pitch in wherever I’m needed. I also know that showing up on time in Ventura traffic deserves at least a small round of applause.\n\nThank you for considering my application. I’d welcome the chance to talk about how I can contribute to [Company Name].\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": 0.21222261226207742, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 306, "reasoningTokens": 137, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4957, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "306", "reasoningTokens": "137", "cachedTokens": "0" }, "timing": { "headersMs": 427.76345899992157, "firstEventMs": 1664.1008750000037, "firstReasoningMs": null, "firstContentMs": 4902.305124999955, "lastContentMs": 5358.510958999977, "generationMs": 485.5432499999879, "totalMs": 5387.848374999943, "visibleTokensPerSecond": 346.00419221151606, "contentChunkCount": 76, "averageContentChunkCharacters": 9.842105263157896, "maxContentStallMs": 176.37162500002887, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2691", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:08:19.002Z", "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 in Ventura. I bring [relevant experience or skill] and a talent for [another relevant strength]—the sort of combination that helps a team get things done without requiring a motivational speech from a seagull.\n\nI’m especially interested in joining [Company Name] because [specific reason]. I’d bring a dependable work ethic, a collaborative attitude, and the ability to stay focused even when my coffee has clearly called in sick.\n\nVentura’s a wonderful place to work, and I’d love the chance to contribute to your team there. Darius, if this letter has reached you, please know I’ve put my best foot forward—and checked that it wasn’t wearing two different shoes.\n\nThank you for considering my application. I’d welcome the opportunity to discuss how I can contribute to [Company Name].\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": 0.012418428263003413, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 352, "reasoningTokens": 159, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3189, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "352", "reasoningTokens": "159", "cachedTokens": "0" }, "timing": { "headersMs": 256.96570800000336, "firstEventMs": 672.5608749999665, "firstReasoningMs": null, "firstContentMs": 2558.2206669999287, "lastContentMs": 3439.728999999934, "generationMs": 889.1549580000574, "totalMs": 3447.375624999986, "visibleTokensPerSecond": 215.93536455316894, "contentChunkCount": 80, "averageContentChunkCharacters": 11.075, "maxContentStallMs": 130.20920799998567, "finalContentBurstRatio": 0.3115124153498871, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2691", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:08:22.449Z", "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—and work somewhere with a significantly better view than most desktop wallpapers—is hard to resist.\n\nI bring a practical approach to problem-solving, a willingness to learn, and the belief that being dependable never goes out of style. I aim to make my coworkers’ lives easier, communicate clearly, and leave things better than I found them, whether that’s a project, a process, or the break room.\n\nWhat draws me to this role is the chance to put my experience in [relevant skill or field] to work for your team. At [previous company or project], I [specific accomplishment]. I’d welcome the opportunity to bring that same focus and initiative to [Company Name], along with a sense of humor calibrated carefully for meetings before 9 a.m.\n\nThank you for considering my application. I’d love to discuss what your team needs and how I could help. I’m happy to meet at your convenience, and I promise my interview answers will contain fewer ocean metaphors than you might expect from a Ventura applicant.\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": 1.0601850105681438, "classifierCostIndex": 0, "promptTokens": 37, "completionTokens": 306, "reasoningTokens": 50, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6889, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "37", "completionTokens": "306", "reasoningTokens": "50", "cachedTokens": "0" }, "timing": { "headersMs": 514.7545829999726, "firstEventMs": 901.5248750000028, "firstReasoningMs": 3555.6234580000164, "firstContentMs": 4158.572583000059, "lastContentMs": 7400.547499999986, "generationMs": 3255.768792000017, "totalMs": 7414.341375000076, "visibleTokensPerSecond": 78.3225149852713, "contentChunkCount": 97, "averageContentChunkCharacters": 12.350515463917526, "maxContentStallMs": 521.0672079999931, "finalContentBurstRatio": 0.18530884808013356, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1658", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:08:31.032Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"YOUR NAME \nCollege Student \nCity, State | email@example.com | (000) 000-0000\n\nSUMMARY \nMotivated 20-year-old college student seeking an opportunity to build professional experience and contribute strong communication, organization, and problem-solving skills. Eager to learn and take on new responsibilities.\n\nEDUCATION \n[College or University], [City, State] \n[Degree or Program], Expected [Month Year] \nRelevant coursework: [Course], [Course], [Course]\n\nSKILLS \n• Programming: Python, Java \n• Communication and teamwork \n• Organization and time management \n• Research and problem-solving \n• Microsoft Office or Google Workspace\n\nPROJECTS & ACTIVITIES \n[Class or Personal Project] — [Dates] \n• Describe a project, assignment, or accomplishment and your contribution. \n• Note any tools or skills you used.\n\n[Club, Volunteer Activity, or Campus Organization] — [Dates] \n• Describe how you participated or supported the group.\n\nEXPERIENCE \nNo formal work experience yet; ready to apply classroom learning and develop practical skills.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.015057285081982057, "classifierCostIndex": 0.004437462448442452, "promptTokens": 41, "completionTokens": 299, "reasoningTokens": 71, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2830, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "299", "reasoningTokens": "71", "cachedTokens": "0" }, "timing": { "headersMs": 6151.699541000067, "firstEventMs": 6458.89629100007, "firstReasoningMs": null, "firstContentMs": 7812.396791000036, "lastContentMs": 8919.055249999976, "generationMs": 1121.3982919999398, "totalMs": 8933.795082999975, "visibleTokensPerSecond": 202.42584781822742, "contentChunkCount": 85, "averageContentChunkCharacters": 12.352941176470589, "maxContentStallMs": 138.35833299998194, "finalContentBurstRatio": 0.6438095238095238, "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": 187, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1658", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:08:39.967Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "\"[Your Name]\n[City, State] | [Email] | [Phone] | [LinkedIn or GitHub]\n\nSUMMARY\nCollege student seeking an entry-level opportunity to apply programming, problem-solving, and teamwork skills. Eager to learn and contribute in a professional setting.\n\nEDUCATION\n[College or University], [City, State]\n[Degree and Major] | Expected graduation: [Month Year]\nRelevant coursework: [List relevant courses]\n\nTECHNICAL SKILLS\nProgramming: Python, Java\nTools: [Add tools you have used, such as Git or Excel]\n\nACADEMIC PROJECTS\n[Project Name] | [Course or personal project]\n- [Describe what you built, the tools you used, and the result.]\n\n[Project Name] | [Course or personal project]\n- [Describe your contribution and a problem you solved.]\n\nACTIVITIES\n[Club, volunteer activity, or campus organization]\n- [Describe your involvement or an accomplishment.]\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.2418816799698998, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 349, "reasoningTokens": 146, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3516, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "349", "reasoningTokens": "146", "cachedTokens": "0" }, "timing": { "headersMs": 902.9106669999892, "firstEventMs": 1313.500875000027, "firstReasoningMs": null, "firstContentMs": 3361.484875000082, "lastContentMs": 4404.343709000037, "generationMs": 1073.8482089999598, "totalMs": 4435.333084000042, "visibleTokensPerSecond": 188.1085225146635, "contentChunkCount": 82, "averageContentChunkCharacters": 10.304878048780488, "maxContentStallMs": 433.30837500002235, "finalContentBurstRatio": 0.336094674556213, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1658", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:08:44.403Z", "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 apply classroom learning, develop professional skills, and contribute to a collaborative team. Interested in programming, problem-solving, and continuous learning.\n\n## EDUCATION\n**[College or University Name]** — [City, State] \n[Degree Program or Major] | Expected Graduation: [Month, Year] \nRelevant Coursework: [List completed or current courses] \nHonors: [Include academic awards or GPA, if applicable]\n\n## SKILLS\n- **Programming:** Python and Java — [indicate your actual proficiency]\n- **Technology:** [List software and tools you have used]\n- **Communication:** [Include a skill demonstrated through coursework or activities]\n- **Organization:** [Include a skill demonstrated through managing assignments or projects]\n\n## ACADEMIC & PERSONAL PROJECTS\n**[Project Name]** | [Course or Personal Project] | [Date]\n- Created [describe what you built or researched] using [tools or methods].\n- Applied [specific skill] to solve [problem or challenge].\n- Achieved [result, finding, or completed deliverable].\n\n**[Project Name]** | [Course or Personal Project] | [Date]\n- Collaborated with [number] classmates to complete [assignment or presentation].\n- Contributed by [describe your specific responsibilities].\n- Presented [findings or final product] to [audience].\n\n## CAMPUS INVOLVEMENT & VOLUNTEERING\n**[Club, Organization, or Volunteer Activity]** | [Dates]\n- Participated in [activity, event, or service].\n- Supported [goal or task] through [specific contribution].\n\n## ADDITIONAL LEARNING\n- [Completed certification, online course, or workshop]\n- [Relevant independent study or ongoing training]\n\n*Replace bracketed text with accurate details and remove any sections or skills that do not apply. Formal work experience is not required, and your age does not need to appear on your resume.*\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.5229522370974296, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 442, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7635, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "442", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 3122.987167000072, "firstEventMs": 3319.7854170000646, "firstReasoningMs": null, "firstContentMs": 4061.049333999981, "lastContentMs": 10701.728250000044, "generationMs": 6691.175208000001, "totalMs": 10752.224541999982, "visibleTokensPerSecond": 65.90770474411406, "contentChunkCount": 127, "averageContentChunkCharacters": 15.716535433070867, "maxContentStallMs": 508.0274999999674, "finalContentBurstRatio": 0.12274549098196393, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1658", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:08:55.156Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"YOUR NAME \nCity, State | Phone | Email | LinkedIn\n\nCOLLEGE STUDENT\n\nSUMMARY \nMotivated college student seeking an opportunity to build practical skills and contribute to a team. Strong foundation in programming, communication, and organization, with a willingness to learn.\n\nEDUCATION \n[College Name], [City, State] \n[Degree or Program], Expected [Month Year] \nRelevant coursework: [Course], [Course], [Course]\n\nSKILLS \nProgramming: Python, Java \nOther: Problem-solving, teamwork, written communication, time management\n\nACADEMIC PROJECTS \n[Project Name] | [Month Year] \n- Describe a class or personal project you completed and the goal it addressed. \n- Note the tools or programming languages you used, such as Python or Java. \n- Summarize your contribution and what you learned.\n\n[Project Name] | [Month Year] \n- Describe another relevant academic or personal project. \n- Highlight a specific result, feature, or challenge you handled.\n\nACTIVITIES & ACHIEVEMENTS \n[Club, volunteer activity, or campus organization] | [Dates] \n- Describe your involvement or a contribution.\n\n[Honor, award, or relevant achievement] | [Date]\n\nADDITIONAL INFORMATION \nAvailability: [Days and hours] \nInterests: [Relevant interests]\"\n", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.015863444611577755, "classifierCostIndex": 0, "promptTokens": 41, "completionTokens": 451, "reasoningTokens": 172, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4193, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "41", "completionTokens": "451", "reasoningTokens": "172", "cachedTokens": "0" }, "timing": { "headersMs": 1809.9020830000518, "firstEventMs": 2100.1505830000388, "firstReasoningMs": null, "firstContentMs": 4658.539250000031, "lastContentMs": 6000.091208000085, "generationMs": 2121.5517080000136, "totalMs": 6780.090958000044, "visibleTokensPerSecond": 131.03616515765745, "contentChunkCount": 92, "averageContentChunkCharacters": 13.402173913043478, "maxContentStallMs": 514.7157499999739, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1746", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:09:02.831Z", "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 revolutionary, he helped shape both the institutions and the identity of the United States. His achievements grew not from wealth or extensive formal schooling but from curiosity, ambition, and a belief that knowledge should serve the public good.\n\nFranklin was born in Boston on January 17, 1706, into a large family supported by his father’s candle- and soap-making business. His formal education ended when he was about ten, but he remained an eager reader. At twelve, he became an apprentice to his older brother James, a printer. Working in the print shop taught him a trade and introduced him to public debate. While still a teenager, Franklin secretly contributed witty essays to his brother’s newspaper under the name Silence Dogood, adopting the voice of a fictional widow.\n\nAfter conflicts with James, Franklin left Boston in 1723 and settled in Philadelphia. He eventually established a successful printing business and became the publisher of the *Pennsylvania Gazette*. In 1732, he began publishing *Poor Richard’s Almanack*, which mixed calendars, practical information, humor, and memorable sayings about thrift and hard work. These publications made him prosperous and helped establish his reputation as an insightful observer of human behavior.\n\nFranklin’s ambition extended beyond personal success. In 1727, he organized the Junto, a discussion group whose members explored ideas for self-improvement and civic reform. He helped establish the Library Company of Philadelphia, a subscription library, and promoted volunteer firefighting, education, and medical care. He also helped found the academy that developed into the University of Pennsylvania. These projects reflected his conviction that ordinary people, working together, could improve their communities.\n\nScience offered another outlet for Franklin’s practical curiosity. His investigations of electricity earned international recognition. His famous 1752 kite experiment helped demonstrate the electrical nature of lightning, and his development of the lightning rod provided a way to protect buildings from strikes. He also invented bifocal glasses and developed the Franklin stove. Rather than patenting his inventions, he believed that useful discoveries should benefit others freely.\n\nFranklin’s personal life was more complicated than his public image of cheerful wisdom might suggest. He formed a common-law marriage with Deborah Read in 1730, and their household included his son William, whose mother’s identity remains uncertain. Benjamin and Deborah had two children together, Francis and Sarah; Francis died of smallpox at the age of four. Franklin’s long absences overseas placed strains on family life. The American Revolution later caused a lasting rupture between Franklin and William, who remained loyal to Britain.\n\nFor much of his political career, Franklin sought cooperation within the British Empire. He served in the Pennsylvania Assembly and worked as a colonial representative in London. Over time, however, disputes over taxation and British authority persuaded him that reconciliation was no longer possible. Returning to Philadelphia in 1775, he joined the Continental Congress. The following year, he served on the committee responsible for drafting the Declaration of Independence and signed the completed document.\n\nFranklin’s diplomatic work in France proved especially important to American independence. His scientific fame, conversational skill, and carefully cultivated image of plain American simplicity helped him win influential supporters. He played a central role in securing the French alliance of 1778, which brought vital military and financial assistance to the American cause. He later helped negotiate the Treaty of Paris of 1783, in which Britain recognized United States independence.\n\nIn his final years, Franklin continued to participate in public affairs. He attended the Constitutional Convention in 1787, encouraging compromise despite his age and declining health. His moral outlook also changed over his lifetime. Earlier, he had enslaved people and printed advertisements connected to slavery. He later became president of the Pennsylvania Abolition Society and, in 1790, petitioned Congress to act against slavery and the slave trade. This evolution does not erase his earlier participation, but it is an essential part of understanding his legacy.\n\nFranklin died in Philadelphia on April 17, 1790, at the age of eighty-four. His life left an enduring mark on science, journalism, education, diplomacy, and government. He was neither flawless nor consistent in every conviction, yet he repeatedly demonstrated the power of learning and the possibility of change. His most lasting achievement may be the example he offered of curiosity turned outward: a restless search for knowledge joined to the practical work of improving society.\n\n******\nFrom Boston’s shop, where ink met eager hands,\nHe sought a wider world than birth commands.\nWith borrowed books and wit beneath a name,\nA printer’s boy began his climb to fame.\n\nIn Philadelphia, presses spread his words,\nWhile plans for common good took root like seeds:\nA library, a school, a watch against the flames—\nHe joined inventive thought to public needs.\n\nHe studied lightning racing through the sky\nAnd gave its force a safer path to ground;\nThrough glass and heat and questions asking why,\nHe sought the useful truths still to be found.\n\nFrom Britain’s hope to independence won,\nHe crossed the sea to gain a nation’s friend.\nYet freedom split him from his loyal son,\nAnd public triumph could not wholly mend.\n\nComplicit once in slavery’s cruel wrong,\nHe later urged the nation toward release.\nHis life reminds us growth can take us long,\nAnd wisdom asks that conscience never cease.\n\nWhen finally his busy hands lay still,\nHis works outlived the reach of wealth or fame:\nTo learn, to change, to serve with thought and skill—\nThese keep a living light around his name.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 3.8692620286604793, "classifierCostIndex": 0, "promptTokens": 59, "completionTokens": 1132, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 25219, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "59", "completionTokens": "1132", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 2726.01087499992, "firstEventMs": 3147.7191669999156, "firstReasoningMs": null, "firstContentMs": 4312.118750000023, "lastContentMs": 27847.867582999985, "generationMs": 23646.60154199996, "totalMs": 27958.720291999984, "visibleTokensPerSecond": 47.82928312092425, "contentChunkCount": 260, "averageContentChunkCharacters": 23.51153846153846, "maxContentStallMs": 895.1485000000102, "finalContentBurstRatio": 0.07557663994765254, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1746", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:09:30.791Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# The Life of Benjamin Franklin\n\nBenjamin Franklin, born on January 17, 1706, in Boston, Massachusetts, stands as one of the most remarkable figures in American history—a testament to what curiosity, discipline, and ambition could achieve in the eighteenth century. The fifteenth of seventeen children born to a candle and soap maker, Franklin's origins were humble, yet his intellect and drive propelled him to extraordinary heights across multiple fields.\n\nFranklin's formal education ended at age ten, but this proved no barrier to his insatiable appetite for learning. Apprenticed to his brother James as a printer, young Benjamin devoured books and taught himself writing through careful study and imitation of great essayists. At seventeen, seeking independence from his brother's strict oversight, he ran away to Philadelphia, the city that would become his lifelong home and the stage for his greatest achievements.\n\nIn Philadelphia, Franklin built a successful printing business, eventually publishing the famous \"Poor Richard's Almanack,\" filled with witty aphorisms that still resonate today: \"Early to bed and early to rise, makes a man healthy, wealthy, and wise.\" His business acumen allowed him to retire from active printing at age 42, freeing him to pursue his true passions: science, invention, and public service.\n\nAs a scientist, Franklin's contributions were revolutionary. His famous kite experiment demonstrated the electrical nature of lightning, leading to his invention of the lightning rod. He also invented bifocal glasses, the Franklin stove, and made significant discoveries about the Gulf Stream. His scientific reputation earned him international acclaim and membership in prestigious scientific societies across Europe.\n\nFranklin's civic contributions to Philadelphia were equally impressive. He founded the city's first public library, organized its first fire department, helped establish the University of Pennsylvania, and created the American Philosophical Society. These institutions reflected his belief in community improvement through practical innovation and collective effort.\n\nPerhaps most significantly, Franklin became a pivotal figure in American independence. He served as a diplomat, securing crucial French support during the Revolutionary War—support that proved decisive in America's victory over Britain. He was the only person to sign all four major documents establishing the United States: the Declaration of Independence, the Treaty of Alliance with France, the Treaty of Paris, and the Constitution. His diplomatic skills, combined with his charm and wit, made him beloved in French society and effective in securing vital resources for the fledgling nation.\n\nIn his later years, Franklin continued serving his country, participating in the Constitutional Convention of 1787 despite failing health. He also became an advocate for the abolition of slavery, presiding over the Pennsylvania Abolition Society—a notable evolution given that he had owned slaves earlier in his life.\n\nFranklin died on April 17, 1790, at age 84, having lived a life of extraordinary breadth. He was simultaneously a printer, author, scientist, inventor, diplomat, and statesman—embodying the Enlightenment ideal of the versatile, rational individual dedicated to both personal improvement and public good. His autobiography, left unfinished at his death, remains a classic of American literature, chronicling his journey from humble beginnings to international renown while offering timeless wisdom on self-improvement and civic virtue.\n\nFranklin's legacy endures not merely in the institutions he founded or the inventions he created, but in the American ideal he embodied: that through hard work, curiosity, and dedication to the common good, an individual could rise to shape the course of history.\n\n******\n\n**Franklin's Journey**\n\nFrom Boston born, the fifteenth child,\nA printer's hands, a mind that wild\nWith curiosity roamed free—\nHe fled to find Philadelphia's key.\n\nPoor Richard's words of wit and wage,\nMade him renowned upon the page.\nThen science called—electric fire,\nHe tamed the lightning's fierce desire.\n\nBifocals, stoves, and libraries too,\nFire brigades and schools he grew.\nA city shaped by his own hand,\nA vision built across the land.\n\nTo France he sailed with charm and grace,\nSecuring aid for freedom's race.\nHis signature on documents four,\nMarked founding papers, nothing more precious wore.\n\nFrom slavery's grip, in age, he turned,\nTo justice's cause his heart had learned.\nAt eighty-four, his journey done,\nA life of many battles won.\n\nPrinter, scientist, diplomat, sage—\nFranklin's spirit fills history's page.\nNot born to power, but rose so high,\nBeneath the electric, self-made sky.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.0475499920371623, "classifierCostIndex": 0.004500775531149415, "promptTokens": 87, "completionTokens": 1523, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 20067, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "87", "completionTokens": "1523", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 657.4758339999244, "firstEventMs": 1383.2547090000007, "firstReasoningMs": null, "firstContentMs": 1383.2801669999026, "lastContentMs": 20718.151041999925, "generationMs": 19348.231667000102, "totalMs": 20731.511834000004, "visibleTokensPerSecond": 78.66351955025885, "contentChunkCount": 423, "averageContentChunkCharacters": 11.22695035460993, "maxContentStallMs": 1202.9823330000509, "finalContentBurstRatio": 0.10739102969046115, "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": 261, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1746", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:09:51.523Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Benjamin Franklin was born in Boston in 1706, the fifteenth child of a soap and candle maker. He had little formal schooling, but he read widely and trained as a printer. At seventeen, he left Boston for Philadelphia, where he built a printing business. His newspaper, the *Pennsylvania Gazette*, and his witty *Poor Richard’s Almanack* made him one of colonial America’s best-known writers.\n\nFranklin believed useful ideas should be put to work. He helped establish a lending library, a volunteer fire company, and educational and medical institutions in Philadelphia. His experiments with electricity showed that lightning was electrical, leading him to develop the lightning rod. He also designed a more efficient stove and is credited with inventing bifocal glasses.\n\nAs tensions grew between Britain and its American colonies, Franklin became a leading advocate for independence. He helped draft the Declaration of Independence and, as a diplomat in France, secured vital support for the American cause. He later helped negotiate the treaty that ended the Revolutionary War and took part in the Constitutional Convention.\n\nFranklin’s life also held contradictions. He once enslaved people, but in his later years he became an outspoken opponent of slavery. When he died in 1790, he left a legacy of invention, public service, and belief in learning—along with a reminder that people can change.\n\n******\n\nA printer’s apprentice, curious and bold, \nMade words and wisdom worth more than gold. \nHe studied the storm and gave rooftops a shield, \nThen sought France’s aid on a faraway field. \nHe helped shape a nation with treaty and pen, \nAnd questioned his choices late in life again. \nFrom books shared with neighbors to freedom’s bright spark, \nFranklin kept learning and lighting the dark.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3567272829006569, "classifierCostIndex": 0, "promptTokens": 59, "completionTokens": 515, "reasoningTokens": 152, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5953, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "59", "completionTokens": "515", "reasoningTokens": "152", "cachedTokens": "0" }, "timing": { "headersMs": 387.97662500001024, "firstEventMs": 726.854583999957, "firstReasoningMs": null, "firstContentMs": 4190.7036249999655, "lastContentMs": 6301.441791999969, "generationMs": 2200.753250000067, "totalMs": 6391.456875000033, "visibleTokensPerSecond": 164.48913570841663, "contentChunkCount": 105, "averageContentChunkCharacters": 17.152380952380952, "maxContentStallMs": 517.7294170000823, "finalContentBurstRatio": 0.07218212104386452, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1746", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:09:57.915Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Benjamin Franklin was born in Boston, Massachusetts, in 1706, the fifteenth child in a large family. His father hoped he would become a clergyman, but Franklin’s formal schooling ended when he was still young. At twelve, he became an apprentice to his brother James, a printer. Franklin loved reading and writing, and he secretly sent essays to his brother’s newspaper under the name “Silence Dogood.” After a difficult apprenticeship, he left Boston and made his way to Philadelphia, where he would build his home and career.\n\nFranklin became a successful printer, publisher, and writer. His newspaper, the *Pennsylvania Gazette*, and his annual *Poor Richard’s Almanack* brought him wide recognition. The almanac was filled with practical advice and memorable sayings about work, thrift, and character. Franklin also helped establish institutions that served his community, including a library, a fire company, and an academy that later became the University of Pennsylvania. His life reflected a belief that people could improve themselves—and their communities—through curiosity, cooperation, and effort.\n\nScience became another of Franklin’s great pursuits. He investigated electricity, described positive and negative electrical charges, and introduced terms such as “battery” and “conductor.” His experiments helped advance the study of electricity, though the famous kite experiment is best understood as part of a broader series of investigations. Franklin also invented useful devices, including bifocal glasses and an efficient stove. He did not patent many of his inventions, believing that useful ideas should benefit everyone.\n\nAs tensions grew between Britain and its American colonies, Franklin turned increasingly to public service. He first sought reconciliation, but eventually supported independence. He helped draft and signed the Declaration of Independence in 1776, then traveled to France to win support for the revolutionary cause. His diplomatic skill helped secure French assistance, which proved vital to the American victory. He later helped negotiate the peace treaty with Britain and returned to the United States, where he took part in the Constitutional Convention of 1787.\n\nIn his later years, Franklin spoke out against slavery and served as president of the Pennsylvania Society for Promoting the Abolition of Slavery. He died in Philadelphia in 1790, at the age of eighty-four. Remembered as a printer, scientist, inventor, diplomat, and statesman, Franklin’s life joined practical ingenuity with public service. His many roles helped shape both the young United States and the idea that knowledge is most valuable when it is put to work for others.\n\n******\nFrom Boston’s streets, a curious mind \nSet out for wider shores, \nWith ink and wit, he shaped his age \nAnd opened many doors.\n\nHe studied sparks and lightning’s flash, \nMade useful wonders new; \nHe built for learning, served the town, \nAnd shared what knowledge grew.\n\nAcross the sea, he sought an ally, \nHelped freedom’s cause take flight; \nHe worked to make a nation’s peace \nAnd shape its laws aright.\n\nA life of questions, craft, and care \nStill offers this insight: \nLet knowledge serve the common good, \nAnd put your gifts to light.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.028554470869569477, "classifierCostIndex": 0, "promptTokens": 59, "completionTokens": 815, "reasoningTokens": 177, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6345, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "59", "completionTokens": "815", "reasoningTokens": "177", "cachedTokens": "0" }, "timing": { "headersMs": 848.6941670000087, "firstEventMs": 1151.5512500000186, "firstReasoningMs": null, "firstContentMs": 4476.029500000062, "lastContentMs": 7231.925667000003, "generationMs": 2756.1013329999987, "totalMs": 7232.130833000061, "visibleTokensPerSecond": 231.12357748712728, "contentChunkCount": 127, "averageContentChunkCharacters": 25.551181102362204, "maxContentStallMs": 313.13737499993294, "finalContentBurstRatio": 0.11494607087827427, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1546", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:10:05.392Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Write an acoustic song about the Korean peninsula without using any commas.\n\n**One Sky Over the Peninsula**\n\n[Verse 1] \nA guitar rings soft by the eastern sea \nMorning climbs the hills and finds me \nFrom Seoul’s bright streets to a northern town \nThe same warm sunlight settles down \n\n[Chorus] \nOne sky over the peninsula \nOne moon above the pines \nAcross the quiet miles between us \nI hope your stars look like mine \n\n[Verse 2] \nThe Han flows on through summer rain \nThe Taedong carries its own refrain \nOld songs travel where feet cannot \nAnd keep a place for those we’ve lost \n\n[Chorus] \nOne sky over the peninsula \nOne moon above the pines \nAcross the quiet miles between us \nI hope your stars look like mine \n\n[Outro] \nWhen the last chord fades into the night \nMay every window hold a light", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.17552875758681485, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 250, "reasoningTokens": 59, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3371, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "250", "reasoningTokens": "59", "cachedTokens": "0" }, "timing": { "headersMs": 2990.891917000059, "firstEventMs": 3316.2586669999873, "firstReasoningMs": 4876.11404200003, "firstContentMs": 6003.208584000007, "lastContentMs": 6359.969083999982, "generationMs": 434.28370799997356, "totalMs": 6437.492291999981, "visibleTokensPerSecond": 437.50202114423223, "contentChunkCount": 79, "averageContentChunkCharacters": 10.341772151898734, "maxContentStallMs": 355.45812500000466, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1546", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:10:11.830Z", "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**Between Two Shores**\n\n*Verse 1* \nMorning lifts above the mountains \nSoft light spills across the fields \nA river carries old reflections \nThrough the stories time reveals \n\n*Chorus* \nOh peninsula of hills and sea \nMay every road run gentle and free \nFrom northern pines to southern sand \nA shared sky stretches over the land \n\n*Verse 2* \nThe wind moves through the silver grasses \nPast the villages and stone \nEach small song that crosses valleys \nSays no heart should stand alone \n\n*Chorus* \nOh peninsula of hills and sea \nMay every road run gentle and free \nFrom northern pines to southern sand \nA shared sky stretches over the land \n\n*Bridge* \nWhen the evening stars awaken \nThey shine on every home \nAnd the moon lays down a bright path \nFor the weary walking home \n\n*Final Chorus* \nOh peninsula of hills and sea \nMay every road run gentle and free \nFrom northern pines to southern sand \nA shared sky stretches over the land", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012416398997532037, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 350, "reasoningTokens": 122, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3188, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "350", "reasoningTokens": "122", "cachedTokens": "0" }, "timing": { "headersMs": 272.1685829999624, "firstEventMs": 689.8828330000397, "firstReasoningMs": null, "firstContentMs": 2387.7691249999916, "lastContentMs": 3448.85170800006, "generationMs": 1075.5867080000462, "totalMs": 3463.355833000038, "visibleTokensPerSecond": 211.0476062149238, "contentChunkCount": 85, "averageContentChunkCharacters": 12.188235294117646, "maxContentStallMs": 560.269290999975, "finalContentBurstRatio": 0.6747104247104247, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1546", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:10:15.294Z", "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*[Verse 1]* \nAn old guitar beneath the pine \nThe mountain wind keeps gentle time \nFrom Baekdu snow to Jeju rain \nThe sea brings every note again \n\n*[Verse 2]* \nIn Seoul the morning markets rise \nWarm kitchen windows greet the skies \nBeyond the fields where fences run \nAnother kettle meets the sun \n\n*[Chorus]* \nOh peninsula beneath one moon \nLet the tide hold on to this tune \nFor every home along your shore \nMay peace come knocking at the door \n\n*[Verse 3]* \nThe Han flows onward toward the foam \nA grandmother hums a song of home \nShe keeps a name beside her bed \nAnd sings the words she left unsaid \n\n*[Bridge]* \nNo string can mend what years have torn \nBut still a song can greet the morn \nOne quiet voice across the blue \nSays I remember you \n\n*[Chorus]* \nOh peninsula beneath one moon \nLet the tide hold on to this tune \nFor every home along your shore \nMay peace come knocking at the door", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.0595133236971181, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 304, "reasoningTokens": 66, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 8137, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "304", "reasoningTokens": "66", "cachedTokens": "0" }, "timing": { "headersMs": 1108.9168330000248, "firstEventMs": 1411.5011670000385, "firstReasoningMs": 4034.979750000057, "firstContentMs": 5201.178833000013, "lastContentMs": 9275.719458000036, "generationMs": 4492.268666999997, "totalMs": 9693.44750000001, "visibleTokensPerSecond": 52.757307625207574, "contentChunkCount": 94, "averageContentChunkCharacters": 10.882978723404255, "maxContentStallMs": 729.9614590000128, "finalContentBurstRatio": 0.2785923753665689, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1546", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:10:24.988Z", "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 rising where the rivers bend\nAncient stories that will never end\nMorning mist upon the rice fields grows\nA single land where the wild wind blows\n\n**Chorus**\nOh peninsula beneath the same moon's light\nDivided hearts still dream of one bright night\nFrom Baekdu peak down to the southern sea\nOne people bound by blood and memory\n\n**Verse 2**\nFences stand where families once walked free\nGrandmothers pray beside the ancient tree\nChildren draw a bridge across the line\nHoping one day all the stars will align\n\n**Chorus**\nOh peninsula beneath the same moon's light\nDivided hearts still dream of one bright night\nFrom Baekdu peak down to the southern sea\nOne people bound by blood and memory\n\n**Bridge**\nHan river flows where sorrow used to sleep\nSeeds of hope are planted deep\nEvery generation learns to sing\nOf the healing that the springtime brings\n\n**Final Chorus**\nOh peninsula beneath the same moon's light\nTwo halves of a heart still burning bright\nFrom Baekdu peak down to the southern sea\nWe are one story waiting to be free", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.30769427660013937, "classifierCostIndex": 0.004455049415861053, "promptTokens": 64, "completionTokens": 435, "reasoningTokens": 29, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6186, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "64", "completionTokens": "435", "reasoningTokens": "29", "cachedTokens": "0" }, "timing": { "headersMs": 959.7772089999635, "firstEventMs": 1765.4036250000354, "firstReasoningMs": 3196.481374999974, "firstContentMs": 3196.540042000008, "lastContentMs": 6732.393917000038, "generationMs": 4141.028624999919, "totalMs": 7337.568666999927, "visibleTokensPerSecond": 97.80178711032406, "contentChunkCount": 109, "averageContentChunkCharacters": 10.330275229357799, "maxContentStallMs": 390.98970799997915, "finalContentBurstRatio": 0.07371225577264653, "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": 214, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-17", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:10:32.576Z", "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": 0.06022927561229297, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1379, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1133.9547089999542, "firstEventMs": 1457.185708999983, "firstReasoningMs": null, "firstContentMs": 2333.682291999925, "lastContentMs": 2377.3501669999678, "generationMs": 191.5192500000121, "totalMs": 2525.201541999937, "visibleTokensPerSecond": 57.435479723314, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 36.463082999922335, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-17", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:10:35.101Z", "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": 0.0013196989782188384, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 32, "reasoningTokens": 18, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2400, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "32", "reasoningTokens": "18", "cachedTokens": "0" }, "timing": { "headersMs": 424.40962500008754, "firstEventMs": 716.0203340000007, "firstReasoningMs": 1892.7713750000112, "firstContentMs": 2917.440459000063, "lastContentMs": 2917.4940840000054, "generationMs": 0.26058300002478063, "totalMs": 2917.701042000088, "visibleTokensPerSecond": 49888.13544538109, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 0.02083299995865673, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-17", "category": "easy", "arm": "smart", "at": "2026-09-26T09:10:38.020Z", "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": 0.00572550488530781, "classifierCostIndex": 0.004405805907088971, "promptTokens": 29, "completionTokens": 32, "reasoningTokens": 18, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2995, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "32", "reasoningTokens": "18", "cachedTokens": "0" }, "timing": { "headersMs": 918.965041999938, "firstEventMs": 1328.3349589999998, "firstReasoningMs": 2424.6912089999532, "firstContentMs": 3810.773041999899, "lastContentMs": 3812.025249999948, "generationMs": 31.380750000011176, "totalMs": 3842.15379199991, "visibleTokensPerSecond": 414.2667080931899, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 1.2400420000776649, "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": 271, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-17", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:10:41.862Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/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": 0.02425581017936921, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 30, "reasoningTokens": 16, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3490, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "30", "reasoningTokens": "16", "cachedTokens": "0" }, "timing": { "headersMs": 1219.2119170000078, "firstEventMs": 1889.1947919999948, "firstReasoningMs": 2810.985166999977, "firstContentMs": 4706.850666999933, "lastContentMs": 4707.892874999903, "generationMs": 61.177207999979146, "totalMs": 4768.0278749999125, "visibleTokensPerSecond": 212.4974385886396, "contentChunkCount": 8, "averageContentChunkCharacters": 1.5, "maxContentStallMs": 1.0223750000586733, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2798", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:10:47.321Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "1. The United Kingdom is a sovereign country in northwestern Europe.\n2. The UK consists of England Scotland Wales and Northern Ireland.\n3. London is the capital of the UK.\n4. Great Britain is the island containing England Scotland and Wales.\n5. The UK is a constitutional monarchy.\n6. The UK Parliament meets at the Palace of Westminster in London.\n7. The currency is the pound sterling.\n8. People in the UK drive on the left side of the road.\n9. Ben Nevis in Scotland is the UK’s highest mountain.\n10. The River Severn is the longest river in the UK.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012030838557970406, "classifierCostIndex": 0, "promptTokens": 22, "completionTokens": 344, "reasoningTokens": 213, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6990, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "22", "completionTokens": "344", "reasoningTokens": "213", "cachedTokens": "0" }, "timing": { "headersMs": 801.4882499999367, "firstEventMs": 1555.0520000000251, "firstReasoningMs": 5265.777000000002, "firstContentMs": 7390.285082999966, "lastContentMs": 7700.180166999926, "generationMs": 422.8831670000218, "totalMs": 7813.168249999988, "visibleTokensPerSecond": 307.4135131039475, "contentChunkCount": 67, "averageContentChunkCharacters": 8.223880597014926, "maxContentStallMs": 208.2085420000367, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2798", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:10:55.134Z", "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 United Kingdom.\n3. The UK is a constitutional monarchy.\n4. The monarch is the UK’s head of state.\n5. The UK Parliament meets at the Palace of Westminster in London.\n6. The pound sterling is the UK’s official currency.\n7. The UK left the European Union in 2020.\n8. The UK has coastlines along the Atlantic Ocean the North Sea the English Channel and the Irish Sea.\n9. Ben Nevis in Scotland is the highest mountain in the UK.\n10. The UK’s national languages include English Welsh Scottish Gaelic and Irish.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.011088853526157206, "classifierCostIndex": 0.00437063197225177, "promptTokens": 22, "completionTokens": 190, "reasoningTokens": 45, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3916, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "22", "completionTokens": "190", "reasoningTokens": "45", "cachedTokens": "0" }, "timing": { "headersMs": 1212.2619589999085, "firstEventMs": 1569.9175839999225, "firstReasoningMs": 3560.3120839999756, "firstContentMs": 4623.8414169999305, "lastContentMs": 5064.667749999906, "generationMs": 472.09445800003596, "totalMs": 5095.9358749999665, "visibleTokensPerSecond": 305.0237035402543, "contentChunkCount": 71, "averageContentChunkCharacters": 8.690140845070422, "maxContentStallMs": 333.14858299994376, "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": 686, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2798", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:11:00.231Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "1. The United Kingdom consists of England and Scotland along with Wales and Northern Ireland.\n2. London is the UK’s capital and largest city.\n3. The UK is a constitutional monarchy with a parliamentary democracy.\n4. The pound sterling is the UK’s official currency.\n5. The UK Parliament meets at the Palace of Westminster in London.\n6. The National Health Service was established in 1948.\n7. London opened the world’s first underground railway in 1863.\n8. Ben Nevis in Scotland is the UK’s highest mountain at 1345 metres.\n9. William Shakespeare was born in Stratford-upon-Avon in 1564.\n10. The Channel Tunnel links England and France beneath the English Channel.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.897803187548557, "classifierCostIndex": 0, "promptTokens": 22, "completionTokens": 261, "reasoningTokens": 108, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6903, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "22", "completionTokens": "261", "reasoningTokens": "108", "cachedTokens": "0" }, "timing": { "headersMs": 997.0162080000155, "firstEventMs": 1704.5083749999758, "firstReasoningMs": null, "firstContentMs": 6264.597916000057, "lastContentMs": 7832.975625000079, "generationMs": 1583.8222090000054, "totalMs": 7848.420125000062, "visibleTokensPerSecond": 95.97036784575073, "contentChunkCount": 73, "averageContentChunkCharacters": 9.082191780821917, "maxContentStallMs": 202.07924999995157, "finalContentBurstRatio": 0.42232277526395173, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2798", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:11:08.080Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "1. The UK’s full name is the United Kingdom of Great Britain and Northern Ireland.\n2. It consists of England and Scotland and Wales and Northern Ireland.\n3. Its capital is London.\n4. England and Scotland and Wales make up the island of Great Britain.\n5. Northern Ireland shares a land border with the Republic of Ireland.\n6. The UK is a constitutional monarchy.\n7. Its currency is the pound sterling.\n8. People drive on the left side of the road.\n9. The Prime Meridian passes through Greenwich in London.\n10. The National Health Service was established in 1948.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.18580766362116308, "classifierCostIndex": 0, "promptTokens": 22, "completionTokens": 270, "reasoningTokens": 142, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5198, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "22", "completionTokens": "270", "reasoningTokens": "142", "cachedTokens": "0" }, "timing": { "headersMs": 680.0527909999946, "firstEventMs": 1628.156791000045, "firstReasoningMs": 3752.4044579999754, "firstContentMs": 5873.49450000003, "lastContentMs": 5880.731374999974, "generationMs": 156.8358330000192, "totalMs": 6030.330333000049, "visibleTokensPerSecond": 809.7639268443485, "contentChunkCount": 66, "averageContentChunkCharacters": 8.5, "maxContentStallMs": 3.509334000060335, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "instruction_cipher", "category": "instruction", "arm": "gpt-6-astra", "at": "2026-09-26T09:11:14.981Z", "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": 0.37756107507346076, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 96, "reasoningTokens": 81, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2999, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "96", "reasoningTokens": "81", "cachedTokens": "0" }, "timing": { "headersMs": 1256.4741670000367, "firstEventMs": 1541.3812499999767, "firstReasoningMs": null, "firstContentMs": 4032.675249999971, "lastContentMs": 4052.0993340000277, "generationMs": 240.88454200001433, "totalMs": 4273.5597919999855, "visibleTokensPerSecond": 58.11912995230374, "contentChunkCount": 9, "averageContentChunkCharacters": 2.111111111111111, "maxContentStallMs": 7.411833000020124, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "instruction_cipher", "category": "instruction", "arm": "smart", "at": "2026-09-26T09:11:19.255Z", "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": 0.0862700277002854, "classifierCostIndex": 0.004553536433405217, "promptTokens": 108, "completionTokens": 99, "reasoningTokens": 79, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3523, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "108", "completionTokens": "99", "reasoningTokens": "79", "cachedTokens": "0" }, "timing": { "headersMs": 849.403207999887, "firstEventMs": 1864.0464999999385, "firstReasoningMs": 4321.2630419998895, "firstContentMs": 4321.379791999934, "lastContentMs": 4321.386749999947, "generationMs": 56.53979099995922, "totalMs": 4377.9195829998935, "visibleTokensPerSecond": 336.0465198750682, "contentChunkCount": 3, "averageContentChunkCharacters": 6.333333333333333, "maxContentStallMs": 0.005708000040613115, "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": 189, "classifierFailed": false, "classifierReused": false } }, { "caseId": "instruction_cipher", "category": "instruction", "arm": "gpt-6-luna", "at": "2026-09-26T09:11:23.633Z", "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": 0.006651932215173787, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 176, "reasoningTokens": 161, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2479, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "176", "reasoningTokens": "161", "cachedTokens": "0" }, "timing": { "headersMs": 277.1777920000022, "firstEventMs": 669.7515840000706, "firstReasoningMs": null, "firstContentMs": 2570.6449169999687, "lastContentMs": 2609.0995840000687, "generationMs": 190.83600000001024, "totalMs": 2761.480916999979, "visibleTokensPerSecond": 73.36142027709262, "contentChunkCount": 9, "averageContentChunkCharacters": 2.111111111111111, "maxContentStallMs": 14.532334000105038, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "instruction_cipher", "category": "instruction", "arm": "gpt-6-sol", "at": "2026-09-26T09:11:26.395Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "FINAL: TZGLQDOMYZWQ", "evaluation": { "passed": true, "answer": "tzglqdomyzwq", "expected": "tzglqdomyzwq", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.13519101854678292, "classifierCostIndex": 0, "promptTokens": 78, "completionTokens": 184, "reasoningTokens": 169, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3996, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "78", "completionTokens": "184", "reasoningTokens": "169", "cachedTokens": "0" }, "timing": { "headersMs": 5109.40850000002, "firstEventMs": 6093.112209000043, "firstReasoningMs": null, "firstContentMs": 9036.38979200006, "lastContentMs": 9037.024667000049, "generationMs": 17.116832999978215, "totalMs": 9053.506625000038, "visibleTokensPerSecond": 817.9083128297051, "contentChunkCount": 9, "averageContentChunkCharacters": 2.111111111111111, "maxContentStallMs": 0.402083000051789, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3294", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:11:35.693Z", "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 formula for water?\nA: H₂O.\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": 0.5372236823614026, "classifierCostIndex": 0, "promptTokens": 69, "completionTokens": 145, "reasoningTokens": 25, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3377, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "69", "completionTokens": "145", "reasoningTokens": "25", "cachedTokens": "0" }, "timing": { "headersMs": 218.2762090000324, "firstEventMs": 516.4347919999855, "firstReasoningMs": null, "firstContentMs": 2872.653500000015, "lastContentMs": 3609.835583999986, "generationMs": 738.4464999999618, "totalMs": 3611.0999999999767, "visibleTokensPerSecond": 161.14911506792455, "contentChunkCount": 64, "averageContentChunkCharacters": 5.015625, "maxContentStallMs": 329.5865829999093, "finalContentBurstRatio": 0.19937694704049844, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3294", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:11:39.304Z", "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 sides does a triangle have?\nA: Three.\n***\nQ & A # 3\nQ: Which 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: How many days are in a leap year?\nA: 366.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008137354540221745, "classifierCostIndex": 0, "promptTokens": 69, "completionTokens": 221, "reasoningTokens": 106, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2513, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "69", "completionTokens": "221", "reasoningTokens": "106", "cachedTokens": "0" }, "timing": { "headersMs": 6494.2474999999395, "firstEventMs": 7488.441624999978, "firstReasoningMs": null, "firstContentMs": 8559.909749999992, "lastContentMs": 8955.152166999993, "generationMs": 421.91116699995473, "totalMs": 8981.820916999946, "visibleTokensPerSecond": 270.1990582771473, "contentChunkCount": 63, "averageContentChunkCharacters": 4.619047619047619, "maxContentStallMs": 181.35462500003632, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3294", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:11:48.286Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "\"Q & A # 1\nQ: What is the largest planet in our solar system?\nA: Jupiter.\n***\nQ & A # 2\nQ: How many sides does a hexagon have?\nA: Six.\n***\nQ & A # 3\nQ: What gas do plants absorb from the atmosphere?\nA: Carbon dioxide.\n***\nQ & A # 4\nQ: Who wrote *Romeo and Juliet*?\nA: William Shakespeare.\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": 0.12651929076576524, "classifierCostIndex": 0, "promptTokens": 69, "completionTokens": 173, "reasoningTokens": 51, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2807, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "69", "completionTokens": "173", "reasoningTokens": "51", "cachedTokens": "0" }, "timing": { "headersMs": 2790.704291999922, "firstEventMs": 3463.7019579999615, "firstReasoningMs": null, "firstContentMs": 5089.9058749999385, "lastContentMs": 5613.012624999974, "generationMs": 558.7604170000413, "totalMs": 5648.66629199998, "visibleTokensPerSecond": 216.55077260061364, "contentChunkCount": 64, "averageContentChunkCharacters": 5.40625, "maxContentStallMs": 499.80870799999684, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3294", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:11:53.936Z", "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 week? \nA: Seven. \n*** \nQ & A # 3 \nQ: What planet is known as the Red Planet? \nA: Mars. \n*** \nQ & A # 4 \nQ: What is the largest ocean on Earth? \nA: The Pacific Ocean. \n*** \nQ & A # 5 \nQ: What gas do plants absorb from the atmosphere? \nA: Carbon dioxide.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01146940844422277, "classifierCostIndex": 0.004539466859470336, "promptTokens": 69, "completionTokens": 186, "reasoningTokens": 53, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2904, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "69", "completionTokens": "186", "reasoningTokens": "53", "cachedTokens": "0" }, "timing": { "headersMs": 7374.396999999997, "firstEventMs": 7644.045500000007, "firstReasoningMs": 9241.19533300004, "firstContentMs": 10247.334625000018, "lastContentMs": 10268.696083000046, "generationMs": 252.81050000002142, "totalMs": 10500.14512500004, "visibleTokensPerSecond": 522.1302121549097, "contentChunkCount": 67, "averageContentChunkCharacters": 5.537313432835821, "maxContentStallMs": 10.34154200006742, "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-1591", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:12:04.962Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "A mom, with a broom in her hand, \nYelled, “Clean up this mess—I command!” \nHer kids only shrugged, \nLeft dishes and mugs, \nAnd she roared, “Do chores as I planned!”\n\n******\n\nA mom shouted, “Pick up the floor!” \nHer kids disappeared out the door. \nShe fumed, “This is unfair! \nYou leave mess everywhere!” \nThen she thundered, “No screens anymore!”", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.03077042876431315, "classifierCostIndex": 0.004451532022377332, "promptTokens": 46, "completionTokens": 753, "reasoningTokens": 653, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 9065, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "753", "reasoningTokens": "653", "cachedTokens": "0" }, "timing": { "headersMs": 961.9326250000158, "firstEventMs": 1241.5940420000115, "firstReasoningMs": 6480.738417000044, "firstContentMs": 10024.594833999989, "lastContentMs": 10029.994792000041, "generationMs": 22.135624999995343, "totalMs": 10046.730458999984, "visibleTokensPerSecond": 4472.4284947915785, "contentChunkCount": 59, "averageContentChunkCharacters": 6, "maxContentStallMs": 2.522499999962747, "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": 348, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1591", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:12:15.010Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "There once was a mom from the shore\nWhose kids never swept up the floor.\n“You lazy young slobs!\nNow finish your jobs!\nI’m not your damn maid anymore!”\n\n******\n\nA mother was mad as could be\nAt dishes stacked high as a tree.\n“That sink’s not a shrine!\nThose plates aren’t all mine!\nGo wash them right now—no TV!”", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3285529610960588, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 476, "reasoningTokens": 392, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7064, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "476", "reasoningTokens": "392", "cachedTokens": "0" }, "timing": { "headersMs": 1933.1074589999625, "firstEventMs": 2235.404291999992, "firstReasoningMs": 5470.58279200003, "firstContentMs": 8391.640250000055, "lastContentMs": 9097.891708999989, "generationMs": 706.3788749999367, "totalMs": 9098.019124999992, "visibleTokensPerSecond": 117.50068261881053, "contentChunkCount": 53, "averageContentChunkCharacters": 5.849056603773585, "maxContentStallMs": 704.2779580000788, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1591", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:12:24.108Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "A mom found a mess in her den, \nAnd barked, “Pick it up—count to ten!” \nHer kids wouldn’t care, \nLeft toys everywhere, \nSo she roared, “I won’t ask again!”\n\n******\n\nA mother, enraged by the floor, \nYelled, “Sweep it! I’ve asked you before!” \nHer kids only grinned, \nAs dust swirled within, \nShe slammed down the broom with a roar!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.04539602143835095, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 1306, "reasoningTokens": 1202, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 9765, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "1306", "reasoningTokens": "1202", "cachedTokens": "0" }, "timing": { "headersMs": 760.5819999999367, "firstEventMs": 1225.2201659999555, "firstReasoningMs": 4020.8518329999642, "firstContentMs": 10545.281541000004, "lastContentMs": 10545.473624999984, "generationMs": 407.9403339999262, "totalMs": 10953.22187499993, "visibleTokensPerSecond": 252.4879042728308, "contentChunkCount": 60, "averageContentChunkCharacters": 5.633333333333334, "maxContentStallMs": 0.015583000029437244, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1591", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:12:35.062Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "A mother was ready to roar\nAt socks piled in heaps on the floor.\n“Get moving, you brats!\nPick up socks, shoes, and hats!\nI’m your mom, not your maid anymore!”\n\n******\n\nA mom yelled, “Get off of that screen!\nThose dishes won’t wash themselves clean!”\nThey said, “Just one more!”\nShe slammed shut the door:\n“Do your damn chores—you know what I mean!”", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 2.5344078194795743, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 740, "reasoningTokens": 645, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 20437, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "740", "reasoningTokens": "645", "cachedTokens": "0" }, "timing": { "headersMs": 5554.205791000044, "firstEventMs": 6487.597874999978, "firstReasoningMs": 13261.574291000026, "firstContentMs": 24929.121207999997, "lastContentMs": 26010.173375000013, "generationMs": 1387.8318750000326, "totalMs": 26316.95308300003, "visibleTokensPerSecond": 67.73154709391423, "contentChunkCount": 57, "averageContentChunkCharacters": 6.105263157894737, "maxContentStallMs": 512.8730000000214, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-3", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:13:02.303Z", "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": 0.046018329516239895, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2258, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 212.8057920000283, "firstEventMs": 1355.9577500000596, "firstReasoningMs": null, "firstContentMs": 2256.0620000000345, "lastContentMs": 2403.692708000075, "generationMs": 221.25820799998473, "totalMs": 2477.320208000019, "visibleTokensPerSecond": 36.15685073251859, "contentChunkCount": 5, "averageContentChunkCharacters": 3.4, "maxContentStallMs": 142.95204100001138, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-3", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:13:04.781Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "gateway-38-ready", "evaluation": { "passed": true, "answer": "gateway-38-ready", "expected": "gateway-38-ready" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008543884056320937, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2392, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1001.137166999979, "firstEventMs": 1307.751667000004, "firstReasoningMs": null, "firstContentMs": 3009.3070420000004, "lastContentMs": 3009.345042000059, "generationMs": 347.9632500000298, "totalMs": 3357.27029200003, "visibleTokensPerSecond": 20.11706696037412, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.03366700001060963, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-3", "category": "easy", "arm": "smart", "at": "2026-09-26T09:13:08.139Z", "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": 0.004824781584745941, "classifierCostIndex": 0.00437766675921921, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3299, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1440.7903749999823, "firstEventMs": 2559.01012500003, "firstReasoningMs": null, "firstContentMs": 4736.203291999991, "lastContentMs": 4737.975291999988, "generationMs": 67.74045799998567, "totalMs": 4803.943749999977, "visibleTokensPerSecond": 103.33558713171796, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 1.6320830000331625, "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": 481, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-3", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:13:12.943Z", "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": 0.000447114825526731, "classifierCostIndex": 0, "promptTokens": 23, "completionTokens": 8, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1465, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "23", "completionTokens": "8", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1239.5478750000475, "firstEventMs": 1645.3664580000332, "firstReasoningMs": null, "firstContentMs": 2383.9110420000507, "lastContentMs": 2383.9311669999734, "generationMs": 384.75741600000765, "totalMs": 2768.6684580000583, "visibleTokensPerSecond": 18.19328155587743, "contentChunkCount": 4, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.016874999972060323, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2070", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:13:16.728Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Juvenile detention can protect people in some circumstances, but it also carries substantial risks for young people. Its effects depend on the facility, length of stay, and support available afterward.\n\n| Potential pros | Potential cons |\n|---|---|\n| Can protect the public when a young person poses an immediate, serious risk. | Separates young people from family, school, and supportive relationships. |\n| Provides a structured setting while a court case is pending or a sentence is served. | Can expose them to violence, stress, or worsening mental health. |\n| May provide access to education, counseling, and other services. | Services vary widely and may be inadequate. |\n| Creates an opportunity to plan treatment and reentry support. | Disruption to education and a detention record can make returning to the community harder. |\n\nP.S. For young people who do not pose a serious safety risk, community-based programs are often worth considering before detention.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.16306365621796975, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 234, "reasoningTokens": 38, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2839, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "234", "reasoningTokens": "38", "cachedTokens": "0" }, "timing": { "headersMs": 207.34724999999162, "firstEventMs": 626.2837920000311, "firstReasoningMs": 1822.7332500000484, "firstContentMs": 2369.0296670000535, "lastContentMs": 3041.401792000048, "generationMs": 681.404749999987, "totalMs": 3050.4344170000404, "visibleTokensPerSecond": 286.1735260871071, "contentChunkCount": 81, "averageContentChunkCharacters": 11.950617283950617, "maxContentStallMs": 357.7017080000369, "finalContentBurstRatio": 0.1921487603305785, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2070", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:13:19.779Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Juvenile detention is the confinement of young people accused of or found responsible for offenses. Its effects depend on facility conditions, length of stay, available services, and the young person’s needs.\n\n| Aspect | Potential pros | Potential cons |\n|---|---|---|\n| Public safety | Can temporarily prevent serious harm when a young person poses an immediate safety risk. | Confinement alone does not address the causes of offending or guarantee long-term safety. |\n| Court attendance | Helps ensure attendance at hearings while a case is pending. | May unnecessarily confine young people who could attend court with reminders, transportation, or supervision. |\n| Structure and supervision | Can provide predictable routines and close supervision. | Restricts autonomy and may expose young people to punitive or unsafe conditions. |\n| Education and treatment | Well-resourced facilities may offer schooling, counseling, and substance-use treatment. | Service quality varies; detention can interrupt existing education and healthcare. |\n| Rehabilitation | Individualized, developmentally appropriate programs may support positive change. | Isolation, trauma, and exposure to delinquent peers can undermine rehabilitation and increase reoffending risk. |\n| Family and community ties | May offer short-term separation from an immediately dangerous environment. | Can weaken supportive relationships and disrupt school, employment, and community connections. |\n| Cost and equity | Concentrates supervision and services for cases requiring secure care. | Is expensive and can disproportionately affect disadvantaged youth, including through unequal access to legal support and alternatives. |\n\nFor young people who do not require secure confinement, diversion, family-based treatment, and community supervision may provide accountability with fewer disruptions.\n\nP.S. Detention before a court decision is not a finding of guilt, and secure detention should not be confused with community-based rehabilitation programs.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.2306757784113536, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 357, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 8629, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "357", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 205.2891669999808, "firstEventMs": 543.0517920000711, "firstReasoningMs": null, "firstContentMs": 1277.3497500000522, "lastContentMs": 8831.90066699998, "generationMs": 7600.1244579999475, "totalMs": 8877.474208, "visibleTokensPerSecond": 46.841338186938735, "contentChunkCount": 124, "averageContentChunkCharacters": 16.266129032258064, "maxContentStallMs": 591.3569170000264, "finalContentBurstRatio": 0.2518591968269707, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2070", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:13:28.657Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "| Pros | Cons |\n|---|---|\n| Can provide immediate separation from situations where a young person may pose a serious, imminent safety risk. | Secure confinement can harm mental health and disrupt education, family relationships, and development. |\n| May ensure a young person appears in court when there is a substantial risk they will not otherwise attend. | Detention can expose youth to violence, trauma, or harmful peer influences. |\n| Can offer access to education, counseling, health care, and structured support—when those services are well funded and appropriate. | Services may be limited or inconsistent, and detention alone does not address the causes of harmful behavior. |\n| May give victims and communities a sense of safety in cases involving serious conduct. | Detention can disproportionately affect marginalized youth and deepen involvement in the justice system. |\n| In some cases, short-term placement can provide time to arrange a safer, more suitable plan. | Alternatives such as supervised release, community programs, or family-based support may achieve safety with less disruption. |\n\n**P.S.** Detention is generally most defensible when it is necessary, proportionate, and as brief as possible, with regular review and access to appropriate support.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.014290628586895827, "classifierCostIndex": 0.004412840694056412, "promptTokens": 34, "completionTokens": 279, "reasoningTokens": 31, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4221, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "279", "reasoningTokens": "31", "cachedTokens": "0" }, "timing": { "headersMs": 1320.0827079999726, "firstEventMs": 3540.053249999997, "firstReasoningMs": 4384.257582999999, "firstContentMs": 5210.22887500003, "lastContentMs": 5528.9675419999985, "generationMs": 330.20758299995214, "totalMs": 5540.436457999982, "visibleTokensPerSecond": 748.0143180116969, "contentChunkCount": 88, "averageContentChunkCharacters": 14.488636363636363, "maxContentStallMs": 126.54874999995809, "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": 198, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2070", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:13:34.198Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "| Potential pros | Potential cons |\n|---|---|\n| **Can address immediate safety risks:** Temporarily separates a young person from situations where they may pose a serious risk to others or themselves. | **Can harm development:** Confinement and separation from family, school, and community can worsen stress, trauma, or mental health challenges. |\n| **Provides structure and supervision:** Some facilities offer routines, education, counseling, or substance-use services. | **Services may be limited or inconsistent:** Programs vary widely, and detention may not provide the individualized support a young person needs. |\n| **Can support accountability:** A court response may help a young person recognize the impact of their actions, particularly when paired with restorative or rehabilitative work. | **May disrupt progress:** Time in detention can interrupt schooling, relationships, and access to community-based care. |\n| **May give time to assess needs and risks:** Short-term detention can allow courts and professionals to make safety and placement decisions. | **Can increase future justice-system involvement:** Research links detention with poorer outcomes for many youth, though effects vary and are difficult to separate from other factors. |\n| **May protect a young person in an unsafe home or community situation:** In some cases, temporary placement can prevent immediate harm while a safer plan is arranged. | **Can be applied inequitably:** Racial and socioeconomic disparities affect who is detained, and youth with disabilities or trauma histories may be especially vulnerable. |\n| **Can offer a secure setting for urgent care:** A facility may be able to respond to an immediate crisis when suitable community options are unavailable. | **Can be costly and restrictive:** Detention uses substantial public resources and limits liberty; community-based alternatives may be more effective for 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; community-based supports and carefully planned alternatives can often address needs with less disruption.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01688078303456142, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 482, "reasoningTokens": 81, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 18146, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "482", "reasoningTokens": "81", "cachedTokens": "0" }, "timing": { "headersMs": 1509.5210000000661, "firstEventMs": 7463.341542000067, "firstReasoningMs": 15822.998499999987, "firstContentMs": 19046.113208000083, "lastContentMs": 19714.53029200004, "generationMs": 668.6002089999383, "totalMs": 19714.71341700002, "visibleTokensPerSecond": 598.2648443952803, "contentChunkCount": 107, "averageContentChunkCharacters": 20.214953271028037, "maxContentStallMs": 460.88341700006276, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-11", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:13:54.155Z", "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": 0.0012189121264737813, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 28, "reasoningTokens": 17, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1974, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "28", "reasoningTokens": "17", "cachedTokens": "0" }, "timing": { "headersMs": 370.1977499999339, "firstEventMs": 881.8136669999221, "firstReasoningMs": null, "firstContentMs": 2301.3039589999244, "lastContentMs": 2302.3022499999497, "generationMs": 436.01104100001976, "totalMs": 2737.314999999944, "visibleTokensPerSecond": 22.93519901942012, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.9589579999446869, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-11", "category": "easy", "arm": "smart", "at": "2026-09-26T09:13:56.893Z", "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": 0.004981170310406728, "classifierCostIndex": 0.0044177109311877155, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1517, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 5384.736916999915, "firstEventMs": 5920.356625000015, "firstReasoningMs": null, "firstContentMs": 6748.990708999918, "lastContentMs": 6749.038291999954, "generationMs": 165.59845800010953, "totalMs": 6914.589167000027, "visibleTokensPerSecond": 48.309628583586864, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.012916000094264746, "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": 656, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-11", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:14:03.808Z", "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": 0.053466410218017256, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1275, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 650.5069590000203, "firstEventMs": 1008.8865839999635, "firstReasoningMs": null, "firstContentMs": 1774.7702499999432, "lastContentMs": 1774.8123749999795, "generationMs": 48.1232500000624, "totalMs": 1822.8935000000056, "visibleTokensPerSecond": 166.2398113175986, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.014207999920472503, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-11", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:14:05.631Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "ORD-94-42", "evaluation": { "passed": true, "answer": "ORD-94-42", "expected": "ORD-94-42" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010716550954341904, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1036, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1799.1705000000075, "firstEventMs": 2207.5989579999587, "firstReasoningMs": null, "firstContentMs": 2745.465415999992, "lastContentMs": 2745.4762909999117, "generationMs": 103.83862499997485, "totalMs": 2849.3040409999667, "visibleTokensPerSecond": 77.04262262719617, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.005459000007249415, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-19", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:14:08.654Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.043995151841277017, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1479, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 252.80412500002421, "firstEventMs": 700.5152920000255, "firstReasoningMs": null, "firstContentMs": 1398.4740000000456, "lastContentMs": 1398.4897920000367, "generationMs": 350.7750829999568, "totalMs": 1749.2490830000024, "visibleTokensPerSecond": 14.254148148831357, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.015791999991051853, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-19", "category": "easy", "arm": "smart", "at": "2026-09-26T09:14:10.403Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005277307784863011, "classifierCostIndex": 0.004430427661475013, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1569, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 1929.9591669999063, "firstEventMs": 2216.509166999953, "firstReasoningMs": null, "firstContentMs": 3496.7749169999734, "lastContentMs": 3496.7772920000134, "generationMs": 171.79716700001154, "totalMs": 3668.572083999985, "visibleTokensPerSecond": 40.74572428775574, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.0023750000400468707, "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": 202, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-19", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:14:14.072Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.015592199460237032, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 16, "reasoningTokens": 8, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1148, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "16", "reasoningTokens": "8", "cachedTokens": "0" }, "timing": { "headersMs": 421.2169170000125, "firstEventMs": 580.5528329999652, "firstReasoningMs": null, "firstContentMs": 1549.5120419999585, "lastContentMs": 1549.5251249999274, "generationMs": 510.3863330000313, "totalMs": 2059.8983749999898, "visibleTokensPerSecond": 13.715100792088746, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.013082999968901277, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-19", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:14:16.133Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0009158751494148166, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 19, "reasoningTokens": 11, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2490, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "19", "reasoningTokens": "11", "cachedTokens": "0" }, "timing": { "headersMs": 3570.28920800006, "firstEventMs": 4091.0305420000805, "firstReasoningMs": 4917.07500000007, "firstContentMs": 6058.2514170000795, "lastContentMs": 6058.254167000065, "generationMs": 11.198832999914885, "totalMs": 6069.450249999994, "visibleTokensPerSecond": 625.0651295588748, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.002749999985098839, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-9", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:14:22.423Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0009158751494148166, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 19, "reasoningTokens": 11, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1423, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "19", "reasoningTokens": "11", "cachedTokens": "0" }, "timing": { "headersMs": 1652.8593330000294, "firstEventMs": 2100.1256660000654, "firstReasoningMs": null, "firstContentMs": 2984.216708000051, "lastContentMs": 3003.414583000005, "generationMs": 102.02254199993331, "totalMs": 3086.239249999984, "visibleTokensPerSecond": 68.61228766486308, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 19.197874999954365, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-9", "category": "easy", "arm": "smart", "at": "2026-09-26T09:14:25.510Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005273790391379291, "classifierCostIndex": 0.004426910267991292, "promptTokens": 35, "completionTokens": 17, "reasoningTokens": 9, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1591, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "17", "reasoningTokens": "9", "cachedTokens": "0" }, "timing": { "headersMs": 1578.8072499999544, "firstEventMs": 1885.8778339999262, "firstReasoningMs": null, "firstContentMs": 3013.615333999973, "lastContentMs": 3013.628083999967, "generationMs": 65.7570410000626, "totalMs": 3079.3723750000354, "visibleTokensPerSecond": 106.45247860215206, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.012749999994412065, "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": 495, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-9", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:14:28.589Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008821217004075793, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 732, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 623.1929579999996, "firstEventMs": 958.2487500000279, "firstReasoningMs": null, "firstContentMs": 1245.0100830000592, "lastContentMs": 1245.019250000012, "generationMs": 122.18504199991003, "totalMs": 1367.1951249999693, "visibleTokensPerSecond": 40.9215393157837, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.009166999952867627, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-9", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:14:29.957Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "POSITIVE", "evaluation": { "passed": true, "answer": "POSITIVE", "expected": "POSITIVE" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.043995151841277017, "classifierCostIndex": 0, "promptTokens": 35, "completionTokens": 6, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1225, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "35", "completionTokens": "6", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1010.6555830000434, "firstEventMs": 1333.3700830000453, "firstReasoningMs": null, "firstContentMs": 2058.776000000071, "lastContentMs": 2058.812125000055, "generationMs": 193.96545799996238, "totalMs": 2252.741458000033, "visibleTokensPerSecond": 25.777785650891357, "contentChunkCount": 2, "averageContentChunkCharacters": 4, "maxContentStallMs": 0.036124999984167516, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2605", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:14:33.335Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "\"Major trends shaping the technology industry:\n\n- **Artificial intelligence and generative AI:** More capable models are transforming software, services, and everyday workflows.\n- **AI agents and automation:** Systems are moving beyond recommendations toward completing multi-step tasks with human oversight.\n- **Cloud and edge computing:** Organizations are balancing centralized cloud platforms with faster, more local processing.\n- **Cybersecurity and digital trust:** Growing threats are driving stronger identity protection, privacy controls, and resilient security operations.\n- **Data infrastructure and governance:** Companies are investing in high-quality data, responsible use, and tools for managing information.\n- **Semiconductors and specialized computing:** Demand is rising for more powerful, energy-efficient chips for AI, devices, and scientific work.\n- **Robotics and autonomous systems:** Advances in sensors and software are expanding automation across factories, logistics, and other settings.\n- **Connected devices and the Internet of Things:** More products and infrastructure are collecting data and communicating across networks.\n- **Spatial computing and immersive interfaces:** Augmented and virtual reality are opening new options for work, training, and entertainment.\n- **Climate and energy technology:** Innovation is accelerating in batteries, grid modernization, efficient data centers, and low-carbon power.\n- **Digital health and biotechnology:** Connected care, AI-assisted research, and precision medicine are reshaping health services.\n- **Quantum technology:** Research is progressing in quantum computing, communications, and sensing, though broad commercial use remains emerging.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.016962630075240293, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 482, "reasoningTokens": 185, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4655, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "482", "reasoningTokens": "185", "cachedTokens": "0" }, "timing": { "headersMs": 2286.1242499999935, "firstEventMs": 2808.8760000000475, "firstReasoningMs": null, "firstContentMs": 5735.847415999975, "lastContentMs": 6964.404290999984, "generationMs": 1228.7660840000026, "totalMs": 6964.613499999978, "visibleTokensPerSecond": 240.89206550723725, "contentChunkCount": 95, "averageContentChunkCharacters": 18.11578947368421, "maxContentStallMs": 331.25545799999963, "finalContentBurstRatio": 0.23300406740267288, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2605", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:14:40.301Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "\"Here are 12 mega trends shaping the tech industry:\n\n1. Artificial intelligence and autonomous agents — Generative models and AI copilots are transforming software development, office workflows, customer support, and content production.\n\n2. Cloud and edge computing — Organizations are combining cloud platforms with local processing to improve response times, control costs, and support connected operations.\n\n3. Cybersecurity and digital trust — Growing threats are accelerating adoption of zero-trust architectures, identity protection, automated monitoring, and stronger data governance.\n\n4. Robotics and automation — More capable robots are moving into warehouses, factories, hospitals, and homes, supported by advances in perception and motion control.\n\n5. Semiconductors and specialized computing — Demand for AI processors, advanced memory, and efficient chip designs is reshaping global technology supply chains.\n\n6. Connected devices and industrial IoT — Sensors and connected equipment are enabling remote monitoring, predictive maintenance, and optimization across transportation, production, and infrastructure.\n\n7. Spatial computing and immersive interfaces — Augmented reality, virtual reality, and digital twins are creating new tools for collaboration, simulation, training, and product design.\n\n8. Quantum technologies — Quantum computing, sensing, and communication are progressing, while organizations prepare for future security implications through post-quantum cryptography.\n\n9. Sustainable technology and energy innovation — Efficient data centers, smarter power grids, improved batteries, and carbon monitoring are becoming more important as computing demand grows.\n\n10. Biotechnology and computational health — AI-supported drug discovery, genomic analysis, remote diagnostics, and personalized treatment are bringing biology and computing closer together.\n\n11. Digital sovereignty and technology regulation — Governments are placing more emphasis on data protection, domestic production, AI oversight, and control over critical digital infrastructure.\n\n12. Open ecosystems and composable software — Open-source models, interoperable platforms, APIs, and modular applications are helping organizations build and adapt technology more quickly.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.3125451410104108, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 379, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 8334, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "379", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1022.4222910000244, "firstEventMs": 1533.6557909999974, "firstReasoningMs": null, "firstContentMs": 2252.1077499999665, "lastContentMs": 9317.559707999928, "generationMs": 7065.626333000022, "totalMs": 9317.734082999988, "visibleTokensPerSecond": 53.49844191937383, "contentChunkCount": 125, "averageContentChunkCharacters": 18.152, "maxContentStallMs": 615.6188340000808, "finalContentBurstRatio": 0.15954164830321726, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2605", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:14:49.619Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "\"Here is a list of mega trends shaping the tech industry today:\n\n1. Artificial Intelligence and automation are transforming how corporations operate, boosting productivity across most sectors.\n2. Cloud computing continues to grow, offering flexible solutions for organizations of all sizes, from small shops to global corporations.\n3. The Internet of Things connects more objects, tools, and homes, forming networks of smart devices controlled through apps.\n4. Cybersecurity remains a top priority, protecting information and online platforms from growing threats and unauthorized access.\n5. Robotics and autonomous vehicles are progressing, opening new opportunities in transport, logistics, and factory operations.\n6. Blockchain technology promotes transparency, offering secure protocols for financial and non-financial transactions worldwide.\n7. Quantum computing holds enormous potential, promising to solve problems too complex for conventional computers.\n8. Sustainability-focused innovations are booming, as companies look toward eco-conscious solutions for a better tomorrow.\n9. Extended reality, encompassing virtual and augmented environments, is opening new doors for immersive storytelling and remote collaboration.\n10. The growth of 5G and future network protocols is boosting connectivity, powering everything from smartphones to smart cities.\n\nThese mega trends show how technology continuously reshapes our world, opening countless opportunities for growth, innovation, and transformation across every industry sector.\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.35210732184415533, "classifierCostIndex": 0.004451532022377332, "promptTokens": 62, "completionTokens": 501, "reasoningTokens": 28, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7264, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "62", "completionTokens": "501", "reasoningTokens": "28", "cachedTokens": "0" }, "timing": { "headersMs": 1022.20404099999, "firstEventMs": 2352.9904159998987, "firstReasoningMs": 3173.837957999902, "firstContentMs": 3173.9705829999875, "lastContentMs": 8102.307166000013, "generationMs": 4962.725250000018, "totalMs": 8136.695833000005, "visibleTokensPerSecond": 95.10903308620567, "contentChunkCount": 123, "averageContentChunkCharacters": 12.487804878048781, "maxContentStallMs": 528.6428749999031, "finalContentBurstRatio": 0.11002604166666667, "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": 229, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2605", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:14:57.756Z", "model": "openai/gpt-6-sol", "loggedModel": "openai/gpt-6-sol", "content": "\"1. AI copilots and autonomous agents\n2. Cloud computing and sovereign clouds\n3. Robotics and industrial automation\n4. Cybersecurity and zero-trust protection\n5. Edge computing and connected devices\n6. Quantum computing and post-quantum cryptography\n7. Open-source models and on-device AI\n8. Spatial computing and immersive collaboration\n9. Sustainable computing and low-carbon data centers\n10. Computational biology and drug discovery\n11. Digital identity and tokenization\n12. Semiconductor innovation and custom chips\"", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.25935297925663187, "classifierCostIndex": 0, "promptTokens": 45, "completionTokens": 374, "reasoningTokens": 261, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6336, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "45", "completionTokens": "374", "reasoningTokens": "261", "cachedTokens": "0" }, "timing": { "headersMs": 667.3277500001714, "firstEventMs": 974.9122500000522, "firstReasoningMs": 4764.487042000052, "firstContentMs": 6669.5348750001285, "lastContentMs": 7040.937292000046, "generationMs": 450.92145899985917, "totalMs": 7120.456333999988, "visibleTokensPerSecond": 248.38028389337526, "contentChunkCount": 107, "averageContentChunkCharacters": 4.859813084112149, "maxContentStallMs": 328.60525000002235, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "hypergeometric", "category": "probability", "arm": "gpt-6-luna", "at": "2026-09-26T09:15:05.158Z", "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": 0.006802097860055685, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 181, "reasoningTokens": 121, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2324, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "181", "reasoningTokens": "121", "cachedTokens": "0" }, "timing": { "headersMs": 216.1184999998659, "firstEventMs": 535.8781669999007, "firstReasoningMs": null, "firstContentMs": 2196.561499999836, "lastContentMs": 2538.9775829999708, "generationMs": 362.4057080000639, "totalMs": 2558.9672079999, "visibleTokensPerSecond": 162.8009678037124, "contentChunkCount": 43, "averageContentChunkCharacters": 2.86046511627907, "maxContentStallMs": 317.0832909999881, "finalContentBurstRatio": 0.6422764227642277, "buffered": false }, "error": null, "routing": null }, { "caseId": "hypergeometric", "category": "probability", "arm": "gpt-6-sol", "at": "2026-09-26T09:15:07.717Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "\\[\nP(\\text{exactly 2 red})=\\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": 0.10973050109923958, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 147, "reasoningTokens": 81, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3834, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "147", "reasoningTokens": "81", "cachedTokens": "0" }, "timing": { "headersMs": 248.25708399992436, "firstEventMs": 529.7315419998486, "firstReasoningMs": 1869.3122089998797, "firstContentMs": 3744.7431249998044, "lastContentMs": 4096.0251669997815, "generationMs": 361.04262500000186, "totalMs": 4105.785749999806, "visibleTokensPerSecond": 180.03414416787953, "contentChunkCount": 46, "averageContentChunkCharacters": 2.782608695652174, "maxContentStallMs": 333.30254199984483, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "hypergeometric", "category": "probability", "arm": "gpt-6-astra", "at": "2026-09-26T09:15:11.823Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "FINAL: 140/429", "evaluation": { "passed": true, "answer": "140/429", "expected": "140/429", "detail": "Exact answer matched" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3180224261432598, "classifierCostIndex": 0, "promptTokens": 75, "completionTokens": 79, "reasoningTokens": 67, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6945, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "75", "completionTokens": "79", "reasoningTokens": "67", "cachedTokens": "0" }, "timing": { "headersMs": 285.8174590000417, "firstEventMs": 3653.7280419999734, "firstReasoningMs": 5781.557250000071, "firstContentMs": 7290.50549999997, "lastContentMs": 7290.526749999961, "generationMs": 0.15350000001490116, "totalMs": 7290.658999999985, "visibleTokensPerSecond": 71661.2377780597, "contentChunkCount": 6, "averageContentChunkCharacters": 2.3333333333333335, "maxContentStallMs": 0.013915999792516232, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "hypergeometric", "category": "probability", "arm": "smart", "at": "2026-09-26T09:15:19.114Z", "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": 0.08152249348781654, "classifierCostIndex": 0.004542984252954056, "promptTokens": 113, "completionTokens": 91, "reasoningTokens": 80, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3365, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "113", "completionTokens": "91", "reasoningTokens": "80", "cachedTokens": "0" }, "timing": { "headersMs": 3083.4615829999093, "firstEventMs": 4012.6409999998286, "firstReasoningMs": 6447.0504580000415, "firstContentMs": 6447.141667000018, "lastContentMs": 6447.144249999896, "generationMs": 19.017624999862164, "totalMs": 6466.15929199988, "visibleTokensPerSecond": 525.8280148058697, "contentChunkCount": 2, "averageContentChunkCharacters": 7, "maxContentStallMs": 0.0025829998776316643, "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": 180, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2622", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:15:26.482Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "How about **The Herald Fun**? It’s a playful nod to the *Herald Sun* and could cover Melbourne news, music, sport and stories that matter to teens.\n\nP.S. A 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": 0.17349746284996645, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 247, "reasoningTokens": 190, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5701, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "247", "reasoningTokens": "190", "cachedTokens": "0" }, "timing": { "headersMs": 475.10537499981, "firstEventMs": 819.7364589998033, "firstReasoningMs": 4450.912624999881, "firstContentMs": 5727.77570899995, "lastContentMs": 6192.078125, "generationMs": 495.85570800001733, "totalMs": 6223.631416999968, "visibleTokensPerSecond": 112.93608018725892, "contentChunkCount": 42, "averageContentChunkCharacters": 4.761904761904762, "maxContentStallMs": 458.86254100012593, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2622", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:15:32.706Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "**The Melbourne Pulse** — a newspaper with its finger on the pulse of teen life, covering music, sport, local news, and issues that matter to young Melburnians.\n\nP.S. A fitting tagline could be: *“Your city. Your voice. Your news.”*", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.35927671675453027, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 97, "reasoningTokens": 34, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3976, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "97", "reasoningTokens": "34", "cachedTokens": "0" }, "timing": { "headersMs": 326.07970899995416, "firstEventMs": 582.3462090000976, "firstReasoningMs": 3197.782000000123, "firstContentMs": 3994.855125000002, "lastContentMs": 4235.85233400017, "generationMs": 244.92758400016464, "totalMs": 4239.7827090001665, "visibleTokensPerSecond": 253.136045305368, "contentChunkCount": 45, "averageContentChunkCharacters": 5.155555555555556, "maxContentStallMs": 194.88850000011735, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2622", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:15:36.947Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "**Melbourne Next** — a newspaper with news, ideas, and stories for the city’s teenagers.\n\nP.S. “Next” hints at the next generation shaping Melbourne’s future.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.008243552766557142, "classifierCostIndex": 0.004451532022377332, "promptTokens": 46, "completionTokens": 100, "reasoningTokens": 57, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2843, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "100", "reasoningTokens": "57", "cachedTokens": "0" }, "timing": { "headersMs": 4588.083417000016, "firstEventMs": 4770.905333000002, "firstReasoningMs": 6433.946791999973, "firstContentMs": 7347.1224169998895, "lastContentMs": 7350.40304200002, "generationMs": 6.806791000068188, "totalMs": 7353.929207999958, "visibleTokensPerSecond": 6170.308446311817, "contentChunkCount": 35, "averageContentChunkCharacters": 4.514285714285714, "maxContentStallMs": 1.2004589999560267, "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": 178, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2622", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:15:44.301Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "**The Melbourne Beat** — a lively name that feels local and teen-focused.\n\nP.S. It could cover music, sport, school life, events and stories from young Melburnians.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.004550966030474805, "classifierCostIndex": 0, "promptTokens": 46, "completionTokens": 122, "reasoningTokens": 78, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3778, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "46", "completionTokens": "122", "reasoningTokens": "78", "cachedTokens": "0" }, "timing": { "headersMs": 3993.4549999998417, "firstEventMs": 4231.809582999907, "firstReasoningMs": 6758.038291999837, "firstContentMs": 7679.953499999829, "lastContentMs": 7680.040458000032, "generationMs": 12.26070800004527, "totalMs": 7692.214207999874, "visibleTokensPerSecond": 3507.138413201035, "contentChunkCount": 35, "averageContentChunkCharacters": 4.685714285714286, "maxContentStallMs": 0.013457999797537923, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3631", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:15:52.596Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "**The PB&J Song**\n\nTake two slices of bread \nSet them side by side \nGrab the peanut butter \nAnd the jelly for the ride \n\nSpread the peanut butter \nOn one slice nice and slow \nSpread the jelly on the other \nEdge to edge it goes \n\nPut the slices together \nWith the fillings tucked inside \nPress them gently in the middle \nNow your sandwich is your pride \n\nCut it into halves \nOr enjoy it as a square \nTake a bite and sing along \nThere’s PB&J to share!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.006141910160034369, "classifierCostIndex": 0, "promptTokens": 28, "completionTokens": 172, "reasoningTokens": 58, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3247, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "28", "completionTokens": "172", "reasoningTokens": "58", "cachedTokens": "0" }, "timing": { "headersMs": 1274.908500000136, "firstEventMs": 1635.862625000067, "firstReasoningMs": 3072.5067910000216, "firstContentMs": 4410.358541000169, "lastContentMs": 4521.960582999978, "generationMs": 120.39937499980442, "totalMs": 4530.757915999973, "visibleTokensPerSecond": 938.5430779867716, "contentChunkCount": 62, "averageContentChunkCharacters": 7.483870967741935, "maxContentStallMs": 103.85054100002162, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3631", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:15:57.127Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "### The PB&J 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 sunshine guaranteed to make you smile \n\n**Chorus** \nSpread spread spread it all around \nPeanut butter goodness from the top edge down \nJelly on the other slice bright and sweet \nPut the fillings face to face and now it’s time to eat \n\n**Verse 2** \nPick a little strawberry or reach for grape \nSmooth it to the edges in a sandwich shape \nPress the bread together with a gentle little pat \nCut it into triangles and how about that \n\n**Chorus** \nSpread spread spread it all around \nPeanut butter goodness from the top edge down \nJelly on the other slice bright and sweet \nPut the fillings face to face and now it’s time to eat \n\n**Outro** \nClose the jars and wipe your space \nTake a bite with a happy face \nTwo kinds of delicious in a handheld treat \nThat’s the PB&J beat!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8545067794512574, "classifierCostIndex": 0, "promptTokens": 28, "completionTokens": 247, "reasoningTokens": 15, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 6251, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "28", "completionTokens": "247", "reasoningTokens": "15", "cachedTokens": "0" }, "timing": { "headersMs": 254.5388329999987, "firstEventMs": 587.9772920000833, "firstReasoningMs": 1726.4787920000963, "firstContentMs": 2791.370707999915, "lastContentMs": 6497.906292000087, "generationMs": 3717.1490840001497, "totalMs": 6508.519792000065, "visibleTokensPerSecond": 62.14440012489709, "contentChunkCount": 95, "averageContentChunkCharacters": 10.263157894736842, "maxContentStallMs": 494.83299999986775, "finalContentBurstRatio": 0.09435897435897436, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-3631", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:16:03.636Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "**Peanut Butter and Jelly Song**\n\nWash your hands and grab two slices \nLay them on a plate \nGet your peanut butter ready \nLunch is gonna taste great\n\nSpread it on the first slice \nSmooth from edge to edge \nSpoon some jelly on the other \nMake a fruity little bed\n\n**Peanut butter and jelly** \n**Press the slices tight** \n**Cut it into triangles** \n**Take a happy bite**\n\nPut the peanut butter away \nClose the jelly too \nWipe the crumbs up from the table \nNow your tasty work is through!", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.11485101430534753, "classifierCostIndex": 0, "promptTokens": 28, "completionTokens": 164, "reasoningTokens": 42, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2896, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "28", "completionTokens": "164", "reasoningTokens": "42", "cachedTokens": "0" }, "timing": { "headersMs": 529.1909590000287, "firstEventMs": 1093.6463750000112, "firstReasoningMs": 2168.733375000069, "firstContentMs": 3397.561292000115, "lastContentMs": 3397.7768749999814, "generationMs": 0.3324999997857958, "totalMs": 3397.8937919999007, "visibleTokensPerSecond": 363909.7746705293, "contentChunkCount": 64, "averageContentChunkCharacters": 7.765625, "maxContentStallMs": 0.019041999941691756, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-3631", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:16:07.035Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "**The PB&J Song**\n\nGrab two slices of bread \nSet them side by side \nSpread peanut butter on one \nLet the jelly take a ride \n\nScoop it from the jar \nSpread it nice and slow \nCover up the bread \nFrom the middle to the row \n\n**Peanut butter and jelly \nA tasty little team \nPut the slices together \nFor a lunchtime dream**\n\nPress the pieces gently \nKeep the filling tucked inside \nCut it down the middle \nTake a happy bite \n\nPeanut butter and jelly \nSweet and smooth and bright \nA sandwich made with love \nMakes the day just right", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009702188787382925, "classifierCostIndex": 0.004388218939670371, "promptTokens": 28, "completionTokens": 148, "reasoningTokens": 18, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2441, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "28", "completionTokens": "148", "reasoningTokens": "18", "cachedTokens": "0" }, "timing": { "headersMs": 1123.9979580000509, "firstEventMs": 1558.860375000164, "firstReasoningMs": null, "firstContentMs": 2945.4745410000905, "lastContentMs": 3479.2317500000354, "generationMs": 558.890374999959, "totalMs": 3504.3649160000496, "visibleTokensPerSecond": 230.8144955976554, "contentChunkCount": 67, "averageContentChunkCharacters": 8.119402985074627, "maxContentStallMs": 509.97849999996834, "finalContentBurstRatio": 0.23713235294117646, "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": 432, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2432", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:16:11.129Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "I’m so sorry about your best friend. Yesterday is so recent; you may still be in shock. You don’t have to make sense of what you’re feeling right now. If you want, you can tell me about them, or I can just stay with you in this conversation.\n\nI can’t share a personal experience, but here’s a brief fictional story about a similar loss: After her closest friend was lost in a lake accident, Maya kept reaching for her phone to send him little things she knew he’d find funny. Each time, the realization hurt all over again. One evening, she wrote the message anyway and saved it. It didn’t make the grief smaller, but it gave her a way to say what she still wanted him to know.\n\nIf someone you trust is nearby, it’s okay to ask them to sit with you, even if neither of you knows what to say.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.24527258257257073, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 352, "reasoningTokens": 165, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4492, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "352", "reasoningTokens": "165", "cachedTokens": "0" }, "timing": { "headersMs": 197.87937500001863, "firstEventMs": 791.7283749999478, "firstReasoningMs": null, "firstContentMs": 3305.6862909998745, "lastContentMs": 4686.904875000007, "generationMs": 1400.3048340000678, "totalMs": 4705.991124999942, "visibleTokensPerSecond": 132.82822103004395, "contentChunkCount": 79, "averageContentChunkCharacters": 10.012658227848101, "maxContentStallMs": 233.81279200012796, "finalContentBurstRatio": 0.20986093552465235, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2432", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:16:15.835Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "I’m so, so sorry. Losing your best friend so suddenly is devastating, and you don’t have to find the right words or make sense of it today.\n\nI can’t honestly share a personal experience, because I don’t have one. But here’s a small, fictional moment that reflects something many people experience: someone keeps reaching for their phone to send their friend a message, then remembers. The ache comes in waves—sometimes sharp, sometimes quiet—and even a small memory can bring both tears and comfort. There’s no correct way to grieve.\n\nI can stay with you here, listen to a story about your friend, or help you find words for a message to someone close. Is there someone you trust who can be with you today?", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.021112477964206244, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 601, "reasoningTokens": 444, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5487, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "601", "reasoningTokens": "444", "cachedTokens": "0" }, "timing": { "headersMs": 329.8743339998182, "firstEventMs": 743.9897499999497, "firstReasoningMs": null, "firstContentMs": 4792.056249999907, "lastContentMs": 5811.848874999909, "generationMs": 1120.0992499999702, "totalMs": 5912.155499999877, "visibleTokensPerSecond": 139.27337242659894, "contentChunkCount": 73, "averageContentChunkCharacters": 9.67123287671233, "maxContentStallMs": 687.8735420000739, "finalContentBurstRatio": 0.13739376770538245, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2432", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:16:21.748Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "I’m so sorry for your loss. Losing your best friend so suddenly can feel unreal and unbearably painful. You don’t have to find the right words or make sense of it right now.\n\nI don’t have personal experiences, so I can’t honestly tell you a story from my own life. But I can offer a small fictional one: After a sudden loss, someone kept a note on their phone of the little things they missed—their friend’s laugh, the way they checked in, a favorite shared joke. Some days they wrote a lot; some days they only added one line. It didn’t take away the hurt, but it gave their love somewhere to go.\n\nI can stay with you here, help you write a message or a tribute, or just listen while you tell me about your friend. Is there someone you trust who can be with you today?", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.01903762166190565, "classifierCostIndex": 0.004479671170247094, "promptTokens": 51, "completionTokens": 411, "reasoningTokens": 230, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4400, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "411", "reasoningTokens": "230", "cachedTokens": "0" }, "timing": { "headersMs": 2107.294375000056, "firstEventMs": 2522.1871670000255, "firstReasoningMs": 5200.494249999989, "firstContentMs": 6212.311500000069, "lastContentMs": 6505.264250000007, "generationMs": 325.247791999951, "totalMs": 6537.55929200002, "visibleTokensPerSecond": 553.4242027998982, "contentChunkCount": 78, "averageContentChunkCharacters": 9.85897435897436, "maxContentStallMs": 194.75662499992177, "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": 193, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2432", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:16:28.286Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "I’m so sorry about your best friend. Losing someone so close, so suddenly, can be overwhelming. You don’t have to make sense of it or find the right words right now. Whatever you’re feeling—sadness, numbness, anger, or all of those at once—there’s no right way to get through this first day.\n\nFor now, try to take things in small pieces: a sip of water, something easy to eat, someone you trust sitting beside you. If reaching out feels hard, you could text: “I’m having a really rough time. Can you stay with me or call?”\n\nI don’t have personal experiences, but I can share a short, imagined story about a similar loss:\n\nA person lost their closest friend unexpectedly. The next morning, they reached for their phone to send that friend something funny, then remembered. They sat holding the phone for a long time. Eventually, they wrote the message in a notebook instead. Over time, that notebook became a place for memories, jokes, and everything left unsaid. It didn’t erase the pain; it gave their love somewhere to go.\n\nIf you’d like, tell me something about your friend. I can listen, help you write a tribute, or help you work out what you need for the next hour.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 1.363966728055104, "classifierCostIndex": 0, "promptTokens": 51, "completionTokens": 393, "reasoningTokens": 124, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 8383, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "51", "completionTokens": "393", "reasoningTokens": "124", "cachedTokens": "0" }, "timing": { "headersMs": 684.3230830000248, "firstEventMs": 1563.388290999923, "firstReasoningMs": 5216.055332999909, "firstContentMs": 5831.356499999994, "lastContentMs": 9142.528249999974, "generationMs": 3311.309165999992, "totalMs": 9142.665665999986, "visibleTokensPerSecond": 80.93475618398377, "contentChunkCount": 97, "averageContentChunkCharacters": 12.072164948453608, "maxContentStallMs": 851.843542000046, "finalContentBurstRatio": 0.18531169940222034, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1393", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:16:37.652Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "### Pros\n- **Clarity for different audiences:** Different names or synonyms may be familiar to different groups.\n- **Useful distinctions:** Two names can highlight different aspects, uses, or contexts of the same thing.\n- **Variety in writing:** Using synonyms can make text less repetitive.\n\n### Cons\n- **Confusion:** Readers may think the names refer to different things.\n- **Inconsistent communication:** Teams may use different synonyms, making instructions or searches harder to follow.\n- **Extra learning:** People may need to remember which synonyms mean the same thing.\n\nUsing multiple names can be helpful when the context is clear, but choosing one standard name usually reduces confusion.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010446929215378282, "classifierCostIndex": 0.004405805907088971, "promptTokens": 33, "completionTokens": 168, "reasoningTokens": 28, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3094, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "168", "reasoningTokens": "28", "cachedTokens": "0" }, "timing": { "headersMs": 572.4620000000577, "firstEventMs": 1443.6120420000516, "firstReasoningMs": 2812.222499999916, "firstContentMs": 3447.224292000057, "lastContentMs": 3666.5901249998715, "generationMs": 228.4989999998361, "totalMs": 3675.7232919998933, "visibleTokensPerSecond": 608.3177606908552, "contentChunkCount": 69, "averageContentChunkCharacters": 10.130434782608695, "maxContentStallMs": 123.68795799999498, "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": 200, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1393", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:16:41.328Z", "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 create confusion.\n\n### Pros\n- **Adds variety:** Synonyms reduce repetition and make writing or speech more engaging.\n- **Fits different audiences:** An everyday name may be clearer to the public, while a technical term suits specialists.\n- **Improves searchability:** Including synonyms helps people find information using different terms.\n- **Offers nuance:** Different names can emphasize different qualities or associations.\n\n### Cons\n- **Can confuse people:** Readers may assume the two names refer to different things.\n- **Reduces consistency:** Switching names can make instructions, documentation, or labels harder to follow.\n- **Creates extra work:** Teams may need to maintain glossaries, alternate labels, or search mappings.\n- **May change the meaning:** Synonyms are not always perfectly interchangeable; tone and context can differ.\n\n**Rule of thumb:** Use varied names when flexibility helps, but choose one standard 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": 0.7327292056702763, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 210, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5019, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "210", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 3963.9948749998584, "firstEventMs": 4515.518167000031, "firstReasoningMs": null, "firstContentMs": 5210.667041999986, "lastContentMs": 8967.14904199983, "generationMs": 4343.468083000043, "totalMs": 9554.13512500003, "visibleTokensPerSecond": 48.118230871318666, "contentChunkCount": 88, "averageContentChunkCharacters": 12.238636363636363, "maxContentStallMs": 548.2151669999585, "finalContentBurstRatio": 0.059424326833797586, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-1393", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:16:50.883Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Using two different names for the same thing can be useful, but it depends on the context.\n\n**Pros**\n- **Clarity for different audiences:** Synonyms can help people recognize a concept by the name they know.\n- **Flexibility:** You can choose the name that fits the tone or setting.\n- **Discoverability:** Including synonyms can make information easier to find in searches.\n\n**Cons**\n- **Confusion:** People may assume the two names refer to different things.\n- **Inconsistency:** Switching names can make instructions or documentation harder to follow.\n- **Extra explanation:** You may need to state that the names are synonyms, especially when introducing them.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1432918463085199, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 205, "reasoningTokens": 65, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2804, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "205", "reasoningTokens": "65", "cachedTokens": "0" }, "timing": { "headersMs": 1036.4708749998827, "firstEventMs": 1282.0011249999516, "firstReasoningMs": 2527.0573750000913, "firstContentMs": 3739.9485830001067, "lastContentMs": 3847.497750000097, "generationMs": 107.73112499993294, "totalMs": 3847.6797080000397, "visibleTokensPerSecond": 1290.249219991776, "contentChunkCount": 69, "averageContentChunkCharacters": 9.594202898550725, "maxContentStallMs": 102.5834170000162, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1393", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:16:54.731Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "## Pros\n- **More accessible:** Different synonyms can make an idea easier to understand for people with different backgrounds or vocabularies.\n- **More flexible:** Synonyms can suit different contexts, tones, or audiences.\n- **Better discoverability:** Using multiple synonyms can help people find the same thing when they search using different terms.\n\n## Cons\n- **Potential confusion:** People may not realize the two names refer to the same thing.\n- **Inconsistent communication:** Different synonyms across documents or teams can make information harder to follow.\n- **Extra effort:** Readers may need to remember which synonyms are interchangeable and when to use each one.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.006593083516503854, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 184, "reasoningTokens": 50, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2854, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "184", "reasoningTokens": "50", "cachedTokens": "0" }, "timing": { "headersMs": 5014.26487500011, "firstEventMs": 5326.907000000123, "firstReasoningMs": 6786.641042000148, "firstContentMs": 7466.52254200005, "lastContentMs": 7906.565834000008, "generationMs": 440.15408300003037, "totalMs": 7906.67662500008, "visibleTokensPerSecond": 302.1669118538901, "contentChunkCount": 67, "averageContentChunkCharacters": 10.119402985074627, "maxContentStallMs": 438.8005000001285, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-2", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:17:02.911Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/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": 0.012068041758278983, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1266, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 617.845708000008, "firstEventMs": 927.2195000001229, "firstReasoningMs": null, "firstContentMs": 1374.8032080000266, "lastContentMs": 1465.7160830001812, "generationMs": 510.0718330000527, "totalMs": 1884.8750410000794, "visibleTokensPerSecond": 21.565589958775202, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 28.686708000022918, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-2", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:17:04.796Z", "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": 0.06022927561229297, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1479, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 912.4010419999249, "firstEventMs": 1221.190084000118, "firstReasoningMs": null, "firstContentMs": 1937.5348340000492, "lastContentMs": 1937.5917500001378, "generationMs": 409.7491250000894, "totalMs": 2347.2839590001386, "visibleTokensPerSecond": 26.84569491148419, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 0.01295799994841218, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-2", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:17:07.143Z", "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": 0.0013196989782188384, "classifierCostIndex": 0, "promptTokens": 29, "completionTokens": 32, "reasoningTokens": 18, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3025, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "32", "reasoningTokens": "18", "cachedTokens": "0" }, "timing": { "headersMs": 305.4629999999888, "firstEventMs": 921.582791000139, "firstReasoningMs": 2354.891583000077, "firstContentMs": 3276.968957999954, "lastContentMs": 3276.985791000072, "generationMs": 91.29954200005159, "totalMs": 3368.2685000000056, "visibleTokensPerSecond": 142.3884470306834, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 0.010291999904438853, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-2", "category": "easy", "arm": "smart", "at": "2026-09-26T09:17:10.512Z", "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": 0.005028519838072191, "classifierCostIndex": 0.00439877112012153, "promptTokens": 29, "completionTokens": 12, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1235, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "29", "completionTokens": "12", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1544.8094170000404, "firstEventMs": 1868.716000000015, "firstReasoningMs": null, "firstContentMs": 2726.8897499998566, "lastContentMs": 2726.9300829998683, "generationMs": 20.80341700022109, "totalMs": 2747.6931670000777, "visibleTokensPerSecond": 528.7592898744998, "contentChunkCount": 8, "averageContentChunkCharacters": 1.25, "maxContentStallMs": 0.015042000217363238, "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": 584, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-6", "category": "easy", "arm": "gpt-6-luna", "at": "2026-09-26T09:17:13.426Z", "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": 0.0018743648737285503, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 47, "reasoningTokens": 36, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2996, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "47", "reasoningTokens": "36", "cachedTokens": "0" }, "timing": { "headersMs": 337.0787499998696, "firstEventMs": 768.7943750000559, "firstReasoningMs": 2420.8125, "firstContentMs": 3324.4040830000304, "lastContentMs": 3324.4162079999223, "generationMs": 14.426124999998137, "totalMs": 3338.8302080000285, "visibleTokensPerSecond": 693.1868398479351, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.008167000021785498, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "easy-6", "category": "easy", "arm": "gpt-6-sol", "at": "2026-09-26T09:17:16.765Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "ORD-59-27", "evaluation": { "passed": true, "answer": "ORD-59-27", "expected": "ORD-59-27" }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.010716550954341904, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 786, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 218.41895800014026, "firstEventMs": 497.3120000001509, "firstReasoningMs": null, "firstContentMs": 871.8032500001136, "lastContentMs": 878.8092500001658, "generationMs": 139.24091699998826, "totalMs": 1011.0441670001019, "visibleTokensPerSecond": 57.45437600070298, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 6.588333000196144, "finalContentBurstRatio": 0, "buffered": false }, "error": null, "routing": null }, { "caseId": "easy-6", "category": "easy", "arm": "smart", "at": "2026-09-26T09:17:17.777Z", "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": 0.004981170310406728, "classifierCostIndex": 0.0044177109311877155, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3315, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1034.7848749998957, "firstEventMs": 1345.918124999851, "firstReasoningMs": null, "firstContentMs": 2439.183041999815, "lastContentMs": 2439.2418749998324, "generationMs": 2059.9677080002148, "totalMs": 4499.15075000003, "visibleTokensPerSecond": 3.8835560231991586, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.036792000057175756, "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": 581, "classifierFailed": false, "classifierReused": false } }, { "caseId": "easy-6", "category": "easy", "arm": "gpt-6-astra", "at": "2026-09-26T09:17:22.276Z", "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": 0.053466410218017256, "classifierCostIndex": 0, "promptTokens": 34, "completionTokens": 9, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1285, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "34", "completionTokens": "9", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 527.3253750000149, "firstEventMs": 828.858917000005, "firstReasoningMs": null, "firstContentMs": 1763.3302919999696, "lastContentMs": 1763.3632920000236, "generationMs": 72.64408300002106, "totalMs": 1835.9743749999907, "visibleTokensPerSecond": 110.12596855269935, "contentChunkCount": 5, "averageContentChunkCharacters": 1.8, "maxContentStallMs": 0.016875000204890966, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1107", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:17:25.181Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "Why did the rocket break up with the moon?\nIt needed 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": 0.5331448587639348, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 151, "reasoningTokens": 119, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 5569, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "151", "reasoningTokens": "119", "cachedTokens": "0" }, "timing": { "headersMs": 5513.18441700004, "firstEventMs": 5819.958333000075, "firstReasoningMs": 9482.51766699995, "firstContentMs": 10580.155917000026, "lastContentMs": 11074.6125419999, "generationMs": 870.1348749999888, "totalMs": 11450.290792000014, "visibleTokensPerSecond": 35.62666075187527, "contentChunkCount": 26, "averageContentChunkCharacters": 4.230769230769231, "maxContentStallMs": 492.7905830000527, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1107", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:17:36.632Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "Why did the rocket need a vacation? It was burned out.******Why did the rocket get a promotion? Its career was taking off.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.1121453270101782, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 159, "reasoningTokens": 125, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 3655, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "159", "reasoningTokens": "125", "cachedTokens": "0" }, "timing": { "headersMs": 411.2454999999609, "firstEventMs": 817.1770839998499, "firstReasoningMs": 2767.687833999982, "firstContentMs": 3781.6394999998156, "lastContentMs": 4005.4684589998797, "generationMs": 257.12850000010803, "totalMs": 4038.7679999999236, "visibleTokensPerSecond": 128.34049901114088, "contentChunkCount": 28, "averageContentChunkCharacters": 4.357142857142857, "maxContentStallMs": 221.68879200005904, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-1107", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:17:40.671Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Why did the rocket bring a ladder? It wanted to reach new heights!******What do rockets eat for breakfast? Launchables!", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.005689789813011574, "classifierCostIndex": 0.004409323300572691, "promptTokens": 33, "completionTokens": 30, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 1618, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "30", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 672.909500000067, "firstEventMs": 1018.0960409999825, "firstReasoningMs": null, "firstContentMs": 1800.5431660001632, "lastContentMs": 2241.3830409999937, "generationMs": 451.08554199989885, "totalMs": 2251.628708000062, "visibleTokensPerSecond": 64.28935822555471, "contentChunkCount": 26, "averageContentChunkCharacters": 4.576923076923077, "maxContentStallMs": 396.8272920001764, "finalContentBurstRatio": 0.3949579831932773, "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": 216, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-1107", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:17:42.923Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "Why did the rocket bring a map? It didn’t want to lose its space.******What did the rocket say to the astronaut? You’re out of this world!", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.0029363471370825104, "classifierCostIndex": 0, "promptTokens": 33, "completionTokens": 78, "reasoningTokens": 38, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2593, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "33", "completionTokens": "78", "reasoningTokens": "38", "cachedTokens": "0" }, "timing": { "headersMs": 2210.08133299998, "firstEventMs": 2516.9011249998584, "firstReasoningMs": null, "firstContentMs": 4614.715415999992, "lastContentMs": 4758.688957999926, "generationMs": 473.57716699992307, "totalMs": 5088.292582999915, "visibleTokensPerSecond": 82.35194328954279, "contentChunkCount": 33, "averageContentChunkCharacters": 4.181818181818182, "maxContentStallMs": 138.6322920001112, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2471", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:17:48.233Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "# Executive Demands and Presidential Well-Being\n\n[Author Name] \n[Department], [University Name] \n[Course Number]: [Course Title] \n[Instructor Name] \n[Submission Date]\n\n## Abstract\n\nThe presidency combines extensive decision-making, public communication, and continuous responsibility for national affairs. These features make presidential well-being an important subject for political science and leadership studies. This paper examines how the structure of presidential work shapes the demands placed on the person holding office and considers practices that support clear judgment and sustained performance. Drawing on research in executive leadership, occupational health, and political institutions, it argues that thoughtful scheduling, trusted counsel, physical activity, and periods for reflection can help presidents meet the office’s demands. The analysis also considers how institutional arrangements can support these practices while respecting the responsibilities of the presidency. [Research Focus]\n\n**Keywords:** presidency, executive leadership, well-being, decision-making, public service\n\n## Introduction\n\nThe president of the United States holds an office with broad responsibilities and a highly visible public role. A president may meet with advisers, review policy options, communicate with the public, and respond to developments in domestic and international affairs within the same day. This combination of duties makes the presidency a useful case for studying how people carry out demanding leadership roles over time [Source One].\n\nPresidential well-being matters because executive decisions can shape public policy and national priorities. A president’s ability to listen, evaluate information, and communicate clearly supports the work of government. This paper examines the demands associated with presidential service and the practices that can sustain effective leadership. It argues that personal routines and institutional support work together: individual habits can aid sound judgment, while a well-organized executive branch can make presidential attention more effective.\n\n## The Structure of Presidential Work\n\nPresidential work is broad in scope. The president serves as head of state, chief executive, commander in chief, and a leading voice in national political life. Each role involves distinct forms of attention and communication. In one setting, a president may study technical information; in another, the president may speak to a national audience or confer with foreign leaders [Source Two].\n\nThe presidency also has a continuous character. Public affairs proceed across the calendar, while the president’s schedule includes both planned events and emerging matters. This pattern calls for sustained concentration and the ability to move between topics. Research on senior leadership suggests that work design, access to reliable information, and clear decision procedures can influence how leaders use their attention [Source Three].\n\nPublic visibility adds another dimension. Presidential words and actions receive close attention from citizens, journalists, public officials, and institutions. This visibility gives presidential communication particular reach. It also makes preparation, careful listening, and consistent public engagement valuable elements of the role [Source Four].\n\n## Decision-Making and Well-Being\n\nSound decision-making depends on more than access to information. Leaders also benefit from time to consider options, hear informed perspectives, and clarify priorities. A structured process can support these tasks by identifying the question at hand, presenting relevant evidence, and making room for discussion among advisers [Source Five].\n\nWell-being has a practical place in this process. Sleep, regular movement, nutritious meals, and moments for reflection can contribute to alertness and steady attention. These practices are relevant across occupations, and they hold particular value for people whose work involves frequent judgment and communication [Source Six]. Presidential schedules can make such routines a deliberate part of executive planning.\n\nA president’s personal habits operate within an institutional setting. Advisers, agency leaders, and staff members help gather information and coordinate the work of government. Clear channels for consultation allow the president to hear perspectives from specialists and public officials. Delegation also enables members of the executive branch to carry out responsibilities assigned to their offices [Source Seven].\n\n## Practices That Support Presidential Service\n\nSeveral practices can support sustained presidential performance. First, a well-designed schedule can balance meetings, briefings, public appearances, and time for review. Protected periods for focused work allow a president to consider important questions without frequent transitions. Regular planning can also help staff coordinate the flow of information [Source Eight].\n\nSecond, a strong advisory process can improve the quality of executive deliberation. Advisers with varied expertise can explain the available evidence, outline possible courses of action, and identify relevant considerations. A president who invites careful discussion can draw on the knowledge of the wider executive team. Research on leadership groups emphasizes the value of clear roles and constructive exchange [Source Nine].\n\nThird, personal routines can support the daily work of the office. Physical activity, consistent sleep schedules, and opportunities for quiet reflection may help maintain energy and focus. These practices do not determine policy outcomes; rather, they contribute to the conditions in which leaders carry out their duties [Source Ten].\n\nFinally, institutional continuity matters. Established procedures for briefings, decision records, and communication can provide a dependable framework for presidential work. Such procedures help staff members coordinate their contributions and give the president a coherent view of issues requiring attention [Source Eleven].\n\n## Institutional and Ethical Considerations\n\nDiscussion of presidential well-being should respect both personal privacy and public accountability. The public has a legitimate interest in the president’s capacity to fulfill the duties of the office. At the same time, personal health information deserves appropriate confidentiality. A balanced approach can focus on functional responsibilities, institutional support, and the quality of executive decision processes [Source Twelve].\n\nThe presidency also depends on cooperation across institutions. Congress, federal agencies, state governments, the courts, and the public each participate in the broader system of American governance. Presidential leadership therefore involves consultation and coordination as well as individual judgment. Recognizing this shared structure places executive well-being within a wider account of public service [Source Thirteen].\n\n## Conclusion\n\nThe presidency calls for sustained attention, broad knowledge, and frequent communication. These features make presidential well-being relevant to the study of executive leadership and democratic governance. Thoughtful scheduling, informed counsel, healthy routines, and dependable institutional procedures can support a president’s capacity to serve.\n\nFurther study could compare presidential work patterns across administrations, examine the role of executive staff, or analyze how leaders organize time for reflection and consultation. Such research can deepen understanding of how the design of high-level public service supports capable leadership over time [Future Research Topic].\n\n## References\n\n[Author One]. ([Year]). *[Title of book or article]*. [Publisher or Journal].\n\n[Author Two]. ([Year]). *[Title of book or article]*. [Publisher or Journal].\n\n[Author Three]. ([Year]). *[Title of book or article]*. [Publisher or Journal].\n\n[Author Four]. ([Year]). *[Title of book or article]*. [Publisher or Journal].", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.06458746142298698, "classifierCostIndex": 0, "promptTokens": 66, "completionTokens": 1858, "reasoningTokens": 516, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 12453, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "66", "completionTokens": "1858", "reasoningTokens": "516", "cachedTokens": "0" }, "timing": { "headersMs": 343.46483299997635, "firstEventMs": 689.8609160000924, "firstReasoningMs": 3213.436708000023, "firstContentMs": 7768.646750000073, "lastContentMs": 12743.700458000181, "generationMs": 5121.075375000015, "totalMs": 12889.722125000088, "visibleTokensPerSecond": 261.8590631464775, "contentChunkCount": 157, "averageContentChunkCharacters": 51.146496815286625, "maxContentStallMs": 2092.2090000000317, "finalContentBurstRatio": 0.3676214196762142, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2471", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:18:01.124Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "# Presidential Well-Being: Executive Responsibilities and Adaptive Capacity\n\n**Author:** [student name] \n**Institution:** [college or university] \n**Course:** [course title] \n**Instructor:** [instructor name] \n**Date:** [submission date]\n\n## Abstract\n\nThe presidency of the United States combines national leadership, international diplomacy, and continuous public attention. These responsibilities create a distinctive setting for examining the relationship between executive work and personal well-being. Focusing on [president’s name] during [period of study], this paper considers how sustained engagement shapes attention, physiological activation, and decision-making. It argues that presidential effectiveness depends partly on the interaction between individual habits and institutional support. Structured schedules, trusted advisers, restorative routines, and deliberate reflection can help sustain the capacities required for effective leadership.\n\n## Introduction\n\nThe American president occupies several roles simultaneously: chief executive, commander in chief, diplomatic representative, and national spokesperson. Each role requires preparation, judgment, and responsiveness. Together, they produce a working environment characterized by frequent transitions and consequential choices.\n\nPresidential scholarship offers useful frameworks for understanding this environment. Richard Neustadt (1990) emphasizes persuasion and political relationships, while Fred Greenstein (2009) examines leadership qualities such as organizational capacity and emotional intelligence. Building on these perspectives, this paper argues that presidential well-being is both a personal resource and an institutional consideration.\n\n## Executive Work and Physiological Activation\n\nA president’s daily schedule may move from intelligence briefings to legislative negotiations, ceremonial appearances, and diplomatic conversations. Such transitions require the executive to redirect attention while maintaining continuity across several policy areas.\n\nHigh-intensity situations can be accompanied by increased alertness, changes in heart rate, and the mobilization of energy. These responses support immediate engagement. When activation continues across extended periods, the availability of restorative intervals becomes especially relevant to sustained concentration and thoughtful deliberation.\n\nA case study of [president’s name] could examine this relationship through [presidential library collection], [daily schedule archive], and [firsthand account]. These materials would establish the sequence and duration of official activities. Physiological interpretations would require separately documented evidence, with conclusions calibrated to its scope.\n\n## Decision-Making and Institutional Support\n\nPresidential decision-making is embedded in an extensive organizational network. Advisers, cabinet officials, and administrative personnel help organize information and establish priorities. Their contributions shape both the substance of decisions and the pace at which the president encounters them.\n\nNeustadt’s (1990) emphasis on relationships suggests that executive capacity extends beyond individual effort. A well-organized advisory system can distribute preparatory work, clarify alternatives, and create opportunities for reflection. Similarly, Greenstein’s (2009) discussion of organizational capacity highlights the importance of arrangements that connect presidential preferences with effective administrative practice.\n\nFor the selected case, [policy episode] offers an opportunity to examine these processes. Comparing [meeting record] with [adviser’s account] could illuminate how information moved through the administration. Attention to [decision-making practice] would further clarify the relationship between presidential engagement and staff coordination.\n\n## Restorative Routines and Sustainable Leadership\n\nPersonal routines also deserve scholarly attention. Sleep, physical activity, recreation, and time with trusted companions can provide opportunities for physiological regulation and renewed attention. Their significance lies in how they fit within the rhythms of executive service.\n\nEvidence from [biographical source] and [schedule sample] could help identify recurring patterns. For example, a documented [restorative activity] might show how a president created transitions between official responsibilities and personal time. Such evidence supports a contextual interpretation rather than a clinical conclusion.\n\n## Conclusion\n\nThe presidency places sustained cognitive, interpersonal, and physiological demands on its occupant. Understanding presidential well-being therefore requires attention to both individual practices and organizational design. In the case of [president’s name], the relationship among scheduling, advisory support, and restorative routines provides a productive framework for further study. Effective leadership emerges through the coordinated use of personal capacities and institutional resources.\n\n## References\n\nGreenstein, F. I. (2009). *The presidential difference: Leadership style from FDR to Barack Obama* (3rd ed.). Princeton University Press.\n\nNeustadt, R. E. (1990). *Presidential power and the modern presidents: The politics of leadership from Roosevelt to Reagan*. Free Press.", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 4.235959769243836, "classifierCostIndex": 0, "promptTokens": 66, "completionTokens": 1239, "reasoningTokens": 364, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 26864, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "66", "completionTokens": "1239", "reasoningTokens": "364", "cachedTokens": "0" }, "timing": { "headersMs": 5296.4036669998895, "firstEventMs": 5922.595874999883, "firstReasoningMs": 11746.408208000008, "firstContentMs": 17478.634666999802, "lastContentMs": 31935.099291999824, "generationMs": 14683.390958000207, "totalMs": 32162.02562500001, "visibleTokensPerSecond": 59.523035414636524, "contentChunkCount": 214, "averageContentChunkCharacters": 25.018691588785046, "maxContentStallMs": 597.36029099999, "finalContentBurstRatio": 0.21292491595069107, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2471", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:18:33.286Z", "model": "anthropic/claude-sonnet-5", "loggedModel": "anthropic/claude-sonnet-5", "content": "# The Weight of Leadership: Examining Presidential Burden in Modern Governance\n\n## Abstract\n\nThis paper explores the demanding nature of the presidency of the United States, focusing on the psychological and physiological burdens placed upon individuals who occupy [position title]. Drawing upon historical records, biographical accounts, and institutional analysis, this study examines how the responsibilities associated with [office name] affect the individual holding this role, from [start date] through [end date] of a typical term.\n\n## Introduction\n\nThe role of [job title] represents one of the most demanding positions within [country name]'s governmental structure. Since the establishment of the office in [year established], those who have served have faced considerable challenges balancing [policy area], [policy area], and [policy area] simultaneously. This paper seeks to understand the toll that constant decision-making, public scrutiny, and global responsibility can place on an individual operating from [address].\n\n## The Nature of Executive Responsibility\n\nIndividuals serving in [office name] must contend with numerous demands daily, including briefings on [topic], meetings regarding [topic], and correspondence with leaders from [country name] and [country name]. The cumulative weight of these obligations often manifests in physical changes observable during a term, as documented by [researcher name] in a study published in [year].\n\nAccording to [source name], the average occupant of this office experiences significant alterations in [health metric] over the course of [duration] years. These findings were corroborated by [institution name], which conducted longitudinal research examining photographs and public appearances from [year] to [year].\n\n## Historical Perspectives\n\nHistorical records maintained at [archive name] reveal that previous officeholders often confided in close advisors about the overwhelming nature of their duties. Correspondence found in the collection at [location] indicates that [historical figure] frequently discussed the challenges of balancing [responsibility] with personal well-being. Similarly, letters housed at [presidential library name] suggest that decisions regarding [policy issue] weighed heavily on the decision-making process.\n\n## Institutional Support Mechanisms\n\nTo address these challenges, various support systems have been implemented, including consultations with [type of professional] and regular briefings from [department name]. The White House Medical Unit, established in [year], provides ongoing care coordinated by [title/role], ensuring that the officeholder maintains adequate wellness throughout their term at [address].\n\n## Conclusion\n\nThe demands placed upon those who hold the position of [office name] remain significant and multifaceted. Future research conducted by [institution name] or [researcher name] might further illuminate coping mechanisms and institutional reforms that could better support individuals in this uniquely challenging role.\n\n## References\n\n[Author name]. ([year]). *[Title of work]*. [Publisher name].\n\n[Author name]. ([year]). [Article title]. *[Journal name]*, [volume]([issue]), [page numbers].", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6484945312377821, "classifierCostIndex": 0.004525397285535456, "promptTokens": 90, "completionTokens": 933, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 13409, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "90", "completionTokens": "933", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 1413.8177920000162, "firstEventMs": 2452.571166999871, "firstReasoningMs": null, "firstContentMs": 2452.595999999903, "lastContentMs": 14824.608083999949, "generationMs": 12410.281834000023, "totalMs": 14862.877833999926, "visibleTokensPerSecond": 75.09901970530852, "contentChunkCount": 271, "averageContentChunkCharacters": 11.892988929889299, "maxContentStallMs": 690.0168330001179, "finalContentBurstRatio": 0.15265280794291033, "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": 160, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2471", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:18:48.150Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "[Student Name] \n[Course] \n[Instructor] \n[Institution] \n[Date]\n\n# Presidential Well-Being and the Demands of Executive Leadership\n\n## Introduction\n\nThe president of the United States holds a position that requires sustained attention, timely decisions, and communication with many audiences. Daily responsibilities range from overseeing federal agencies to consulting with advisers and representing the nation abroad. These responsibilities create substantial cognitive and emotional demands. Examining how a president manages those demands offers insight into both individual well-being and the quality of executive decision-making. This paper argues that reliable routines, thoughtful delegation, and access to varied perspectives can help a president maintain clarity throughout a demanding term.\n\n## The Nature of Presidential Demands\n\nArticle II of the Constitution places executive power in the presidency, while the modern federal government requires the president to coordinate with a broad network of officials and institutions. A typical day may involve briefings, meetings, public remarks, and decisions with long-term consequences. Research on executive decision-making suggests that sustained attention is a limited resource [Source 1]. Research on occupational well-being also connects opportunities for rest and reflection with effective performance [Source 2]. These findings provide a framework for considering the presidency as a human role as well as a constitutional office.\n\nPresidential demands vary with circumstances. During [Historical Event 1], for example, a president had to weigh competing priorities while communicating with the public. A comparison with [Historical Event 2] could show how different administrations organized advisers and scheduled decisions [Source 3]. Such comparisons should account for differences in technology, institutions, and public expectations rather than assume that every presidency operates under identical conditions.\n\n## Practices That Support Clear Decisions\n\nDelegation is one practical way to manage a large volume of information. Cabinet members, agency leaders, and White House staff can identify options and explain their implications before a decision reaches the president. Delegation is most useful when responsibilities are clear and advisers can share well-supported, differing views [Source 4]. A study of [Administration or President] could illustrate how a particular advisory structure shaped the flow of information [Public Record 1].\n\nDaily routines matter as well. Time reserved for reading, exercise, family, or reflection may help a president approach subsequent tasks with renewed focus [Source 5]. These practices do not replace institutional support; rather, they complement schedules that allow adequate preparation for consequential choices. An analysis of [Presidential Schedule] alongside [Memoir or Interview] could provide a fuller picture of how one president allocated time.\n\n## Institutional Implications\n\nPresidential well-being is not solely a private matter. The organization of briefings, the range of expertise in meetings, and the timing of major decisions can all influence how effectively the executive branch works [Source 6]. Researchers might examine [Archival Collection], [Decision Memo], and [Public Statement] to assess how those practices functioned in a specific administration. Evidence from [Scholarly Study] could then place the findings in a broader context.\n\n## Conclusion\n\nThe presidency combines constitutional authority with unusually wide-ranging daily responsibilities. A careful study of presidential well-being therefore asks how leaders sustain attention, evaluate advice, and make room for renewal. Historical records and scholarly research can help answer that question without reducing presidential performance to personality alone. By examining both personal routines and institutional design, scholars can better understand the conditions that support clear executive leadership [Source 7].\n\n## References\n\n[Full Reference 1] \n[Full Reference 2] \n[Full Reference 3]", "evaluation": { "passed": true, "answer": "11", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 2, "instructionsTotal": 2 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.8390958610397967, "classifierCostIndex": 0, "promptTokens": 66, "completionTokens": 1226, "reasoningTokens": 516, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10869, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "66", "completionTokens": "1226", "reasoningTokens": "516", "cachedTokens": "0" }, "timing": { "headersMs": 471.921917000087, "firstEventMs": 734.1616670000367, "firstReasoningMs": 5169.323291999986, "firstContentMs": 8664.695167000173, "lastContentMs": 11260.468958999962, "generationMs": 2971.230332999956, "totalMs": 11635.925500000129, "visibleTokensPerSecond": 238.6216888423273, "contentChunkCount": 139, "averageContentChunkCharacters": 29.503597122302157, "maxContentStallMs": 356.8957919999957, "finalContentBurstRatio": 0.14216044867105584, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2374", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:19:00.195Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "# Project Proposal: LearningBridge AI\n\n## Project summary\n\n**Duration:** 36 months \n**Initial scope:** 100 schools across two countries \n**Primary participants:** Students in grades 3 to 8 and their teachers \n**Estimated budget:** USD 2.4 million\n\nLearningBridge AI will use machine learning and artificial intelligence to support better teaching and learning in underserved communities. The project will provide offline-capable learning tools and teacher support in local languages. It will work with education ministries and local communities to adapt the program to each setting.\n\nAI will support teachers rather than replace them. Teachers will retain control over lessons and decisions about students.\n\n## The need\n\nMany schools face shortages of learning materials and trained teachers. Students may receive limited feedback or lessons that do not match their current skill levels. These challenges can be greater in rural areas and in communities where children learn in languages that are underrepresented in digital tools.\n\nAI could help address some of these barriers. However technology alone cannot improve education. Tools must work with limited connectivity and local curricula. They must protect children’s data and support educators.\n\n## Project goals\n\n1. Improve student literacy and numeracy.\n2. Help teachers identify learning needs and plan suitable lessons.\n3. Expand access to learning resources in local languages.\n4. Build local expertise in responsible education technology.\n5. Generate reliable evidence about which approaches are effective.\n\n## Main activities\n\n### 1. Adaptive learning resources\n\nStudents will use tablets or shared school devices to access lessons and practice activities. A machine learning system will use student responses to recommend suitable next steps. Recommendations will be simple and visible to teachers.\n\nThe system will not make high-stakes decisions about students. Teachers will be able to review and change its suggestions.\n\n### 2. Teacher support tool\n\nTeachers will have access to an AI assistant that can help them:\n\n- Create lesson plans aligned with the national curriculum.\n- Adapt activities for different learning levels.\n- Generate practice questions and reading materials.\n- Translate or simplify selected content into local languages.\n- Review class progress and identify students who may need support.\n\nAll generated content will be reviewed by teachers before classroom use. The project will provide training so teachers can assess accuracy and suitability.\n\n### 3. Offline-first technology\n\nThe learning platform will be designed to function without a continuous internet connection. Schools will be able to download approved resources when connectivity is available and sync learning records later.\n\nThe project will use low-cost devices where possible. It will also explore options such as local school servers and printed materials for settings where device access is limited.\n\n### 4. Local language and curriculum development\n\nLocal educators and language experts will help select and review learning materials. The project will prioritize languages and dialects chosen with participating communities. It will not assume that one language model or curriculum can serve every location.\n\n### 5. Teacher development\n\nTeachers and school leaders will receive practical training in:\n\n- Using the learning platform.\n- Interpreting student progress information.\n- Reviewing AI-generated materials.\n- Protecting student privacy.\n- Maintaining meaningful human judgment in teaching.\n\n## Implementation plan\n\n### Phase 1: Co-design and preparation \n**Months 1 to 6**\n\n- Select participating districts with education authorities.\n- Consult teachers families students and local language experts.\n- Review connectivity device access and existing curriculum.\n- Establish data protection and safeguarding procedures.\n- Develop and test initial learning materials.\n\n### Phase 2: Pilot \n**Months 7 to 12**\n\n- Introduce the tools in 20 schools.\n- Train teachers and school leaders.\n- Collect feedback on usability and local relevance.\n- Fix technical and content problems before expansion.\n\n### Phase 3: Expansion \n**Months 13 to 28**\n\n- Expand to 100 schools.\n- Provide ongoing teacher coaching.\n- Monitor system performance and student access.\n- Adapt the program based on school feedback.\n\n### Phase 4: Evaluation and transition \n**Months 29 to 36**\n\n- Measure learning and implementation outcomes.\n- Share findings with ministries and communities.\n- Prepare a plan for local ownership and future funding.\n- Publish open resources where licensing and privacy rules allow.\n\n## Evaluation\n\nAn independent evaluation will compare participating schools with similar schools that do not yet use the program. Where appropriate and approved by local partners the evaluation may use a phased rollout to ensure that comparison schools can receive the program later.\n\nMeasures will include:\n\n- Student reading and mathematics results.\n- Attendance and time spent on learning activities.\n- Teacher confidence and lesson preparation time.\n- Student access across gender disability language and location.\n- Tool reliability and frequency of offline use.\n- Student family and teacher satisfaction.\n\nThe project will establish baseline measures before rollout. It will set final targets with local education partners after the baseline is complete. Results will be reported honestly including negative or mixed findings.\n\n## Ethics and safeguards\n\n- Collect only the data required to deliver and evaluate the program.\n- Obtain appropriate consent and explain data use in accessible language.\n- Use encryption and role-based access controls.\n- Set clear limits on data retention and deletion.\n- Avoid facial recognition and other unnecessary surveillance.\n- Test tools for unequal performance across language and student groups.\n- Provide a way for students families and teachers to raise concerns.\n- Require human review for consequential educational decisions.\n- Do not sell student data or use it for advertising.\n\n## Partnership and governance\n\nThe project will be governed by a steering group with representatives from education ministries local universities teacher organizations participating schools and community groups. A student and family advisory group will provide feedback throughout the project.\n\nLocal partners will lead curriculum decisions and guide the selection of languages. The project team will provide technical support and training. Responsibility for long-term operation will be agreed with education authorities before the end of the project.\n\n## Budget outline\n\n- Technology development and maintenance: USD 550000\n- Devices and offline infrastructure: USD 500000\n- Teacher training and coaching: USD 450000\n- Local language content and curriculum work: USD 300000\n- Monitoring evaluation and research: USD 250000\n- Community engagement and safeguarding: USD 150000\n- Project management and contingency: USD 200000\n\n**Total: USD 2.4 million**\n\n## Expected result\n\nBy the end of the project participating schools will have practical tools for adapting learning activities and identifying student needs. Teachers will have greater access to curriculum-aligned resources and relevant training. Education authorities will have evidence to guide future decisions about responsible AI use.\n\nThe project will treat AI as one part of a broader effort to improve education. Its success will depend on strong teachers local leadership safe technology and sustained public investment.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.058652536341033054, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 1692, "reasoningTokens": 354, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 10807, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "1692", "reasoningTokens": "354", "cachedTokens": "0" }, "timing": { "headersMs": 488.75312499981374, "firstEventMs": 970.110875000013, "firstReasoningMs": 3173.9337909999304, "firstContentMs": 5213.987957999809, "lastContentMs": 11342.720250000013, "generationMs": 6144.912125000032, "totalMs": 11358.90008299984, "visibleTokensPerSecond": 217.57837586652116, "contentChunkCount": 167, "averageContentChunkCharacters": 45.25748502994012, "maxContentStallMs": 620.810499999905, "finalContentBurstRatio": 0.13297168563111936, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2374", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:19:11.554Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "# Project Proposal: AI Support for Better Learning\n\n## Goal\nImprove literacy and numeracy for children in underserved communities by giving teachers practical tools and giving students more opportunities to learn at their own pace.\n\n## Pilot plan\nRun a 24 month pilot in 20 schools serving approximately 4000 students. Work with local educators to select grades and adapt materials to the national curriculum and local languages.\n\n## What the project will do\n- **Support students:** Provide short practice activities that adjust to each learner’s progress and work offline on shared devices.\n- **Support teachers:** Use machine learning to identify common learning gaps and suggest activities for small groups. Teachers will decide how to use every recommendation.\n- **Make content accessible:** Develop low bandwidth lessons with audio and text options for learners with different needs.\n- **Train local teams:** Prepare teachers and education officials to use the tools and maintain them after the pilot.\n\n## Safeguards\nCollect only the data needed to support learning. Obtain appropriate consent and protect student records. Test the tools across languages and student groups to identify unfair results. Keep teachers responsible for instruction and ensure students can learn without using the AI system.\n\n## Evaluation\nIntroduce the tools in phases so schools using them can be compared with schools awaiting access. Measure changes in literacy and numeracy assessments as well as attendance and teacher workload. Gather feedback from students and teachers each term and use it to improve the program.\n\n## Expected outcome\nBy the end of the pilot the education ministry and its partners will have evidence on whether the approach improves learning at an affordable cost and a practical plan for expanding it if it works.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.3382988467332586, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 492, "reasoningTokens": 162, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4972, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "492", "reasoningTokens": "162", "cachedTokens": "0" }, "timing": { "headersMs": 2078.2463750001043, "firstEventMs": 2394.1759580001235, "firstReasoningMs": null, "firstContentMs": 4922.885207999963, "lastContentMs": 7021.385540999938, "generationMs": 2106.130041999975, "totalMs": 7029.0152499999385, "visibleTokensPerSecond": 156.21067713728755, "contentChunkCount": 100, "averageContentChunkCharacters": 18.24, "maxContentStallMs": 714.7620420001913, "finalContentBurstRatio": 0.40899122807017546, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2374", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:19:18.584Z", "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 strategy to deploy machine learning and artificial intelligence tools to strengthen educational outcomes in resource-limited communities. The initiative targets three critical areas: personalized learning access teacher support and infrastructure gaps.\n\n## Problem Statement\n\nMany developing countries face severe teacher shortages overcrowded classrooms and limited access to quality learning materials. Students often progress through grades without mastering foundational skills because instructors cannot provide individualized attention. Rural areas frequently lack qualified teachers in subjects like mathematics and science.\n\n## Proposed Solution\n\n### Adaptive Learning Platforms\n\nWe will develop AI-driven tutoring systems that adjust content difficulty based on individual student performance. These platforms will work offline through low-cost tablets and sync data when internet connectivity becomes available. The system will identify knowledge gaps and provide targeted practice exercises in local languages.\n\n### Teacher Support Tools\n\nMachine learning models will analyze student performance data to help teachers identify struggling students early. Automated grading systems will reduce administrative burden allowing educators to focus more time on instruction rather than paperwork. Chatbot assistants will provide teachers with lesson planning suggestions and pedagogical resources.\n\n### Speech Recognition for Literacy\n\nAI-powered speech recognition tools will help students practice reading aloud and receive immediate pronunciation feedback. This technology will support literacy development in regions where reading tutors are scarce.\n\n### Content Translation and Localization\n\nNatural language processing will be used to translate educational materials into multiple local languages and dialects ensuring cultural relevance and comprehension.\n\n## Implementation Strategy\n\n### Phase One: Needs Assessment\n\nOur team will conduct field research partnering with local ministries of education and community leaders to understand specific challenges and infrastructure limitations in target regions.\n\n### Phase Two: Pilot Programs\n\nWe will launch pilot programs in three to five schools across different countries testing the adaptive learning platform and gathering feedback from students and teachers.\n\n### Phase Three: Iteration and Refinement\n\nBased on pilot results we will refine algorithms and user interfaces ensuring the tools are culturally appropriate and pedagogically sound.\n\n### Phase Four: Scaled Deployment\n\nFollowing successful pilots we will expand the program to additional schools and regions establishing partnerships with local governments and nonprofit organizations for sustainable implementation.\n\n## Technology Requirements\n\nThe project will utilize low-power devices solar charging stations and offline-first software architecture to accommodate limited electricity and internet access. Cloud-based servers will handle data processing when connectivity is available while edge computing will manage core functions offline.\n\n## Expected Outcomes\n\nStudents will demonstrate improved literacy and numeracy scores within eighteen months. Teachers will report reduced administrative workload and increased instructional time. Schools will gain sustainable technology infrastructure supporting long-term educational improvement.\n\n## Monitoring and Evaluation\n\nWe will establish clear metrics including student assessment scores teacher satisfaction surveys and system usage analytics. Quarterly reports will track progress against baseline data collected during the needs assessment phase.\n\n## Budget Considerations\n\nFunding will cover device procurement software development local staff training and ongoing technical support. We will seek partnerships with technology companies nonprofit foundations and government education ministries to diversify funding sources and ensure long-term sustainability.\n\n## Risk Mitigation\n\nPotential challenges include limited digital literacy among teachers and students unreliable power sources and resistance to technology adoption. We will address these through comprehensive training programs community engagement initiatives and phased implementation allowing time for adjustment.\n\n## Conclusion\n\nThis initiative represents a scalable and sustainable approach to addressing educational inequities through thoughtful application of machine learning and artificial intelligence. By focusing on adaptability offline functionality and cultural relevance we aim to create lasting positive impact on student outcomes across developing regions.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.939387166156744, "classifierCostIndex": 0.004423392874507572, "promptTokens": 49, "completionTokens": 1371, "reasoningTokens": 0, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 14942, "loggedFinishReason": "end_turn", "billedUsage": { "promptTokens": "49", "completionTokens": "1371", "reasoningTokens": "0", "cachedTokens": "0" }, "timing": { "headersMs": 590.0299589999486, "firstEventMs": 1372.9616670000833, "firstReasoningMs": null, "firstContentMs": 1373.045167000033, "lastContentMs": 15527.576374999946, "generationMs": 14163.066832999932, "totalMs": 15536.111999999965, "visibleTokensPerSecond": 96.73046213464879, "contentChunkCount": 314, "averageContentChunkCharacters": 15.178343949044587, "maxContentStallMs": 723.2902500000782, "finalContentBurstRatio": 0.11603021401594629, "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-2374", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:19:34.120Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "# Project Proposal: Learning Together with AI\n\n## 1. Project Summary\n\n**Learning Together with AI** is an 18-month pilot designed to improve foundational literacy and numeracy in underserved schools in a developing country.\n\nThe project will support approximately 6000 students and 180 teachers across 30 schools. It will combine offline learning tools with machine learning that identifies learning gaps and recommends suitable practice activities.\n\nThe guiding principle is simple: **AI should strengthen teachers rather than replace them.**\n\nThe pilot will be developed with the education ministry and local communities. 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 struggle to identify each student’s needs or provide individual support.\n\nDigital education projects can also fail when they depend on reliable internet access or content that does not match local languages and curricula.\n\nThis project addresses these constraints through shared devices and locally reviewed materials that work offline.\n\n## 3. Objectives\n\nThe project will aim to:\n\n- Improve foundational reading and mathematics skills.\n- Help teachers identify learning gaps earlier.\n- Reduce time spent preparing routine classroom materials.\n- Improve access for students with disabilities and learners in remote communities.\n- Establish whether AI-supported instruction offers better value than existing alternatives.\n\n## 4. Proposed Solution\n\n### Adaptive student practice\n\nStudents will use shared tablets during scheduled classroom rotations.\n\nA lightweight machine learning model will estimate skill mastery from short assessments and practice responses. It will recommend activities from a curriculum-aligned content library.\n\nTeachers will be able to review and override recommendations. Students will not be assigned permanent ability labels.\n\n### Teacher planning assistant\n\nAn AI assistant will help teachers prepare lesson plans and differentiated exercises using approved curriculum materials.\n\nGenerated content will require teacher review before classroom use. The assistant will not make grading or disciplinary decisions.\n\n### Learning progress dashboard\n\nA simple dashboard will show which skills need additional instruction. It will recommend small-group activities without publicly ranking students.\n\nResults will support teacher judgment rather than determine high-stakes outcomes.\n\n### Local language and accessibility support\n\nLocal educators will adapt materials into selected languages and review them for accuracy and cultural relevance.\n\nAccessible features will include adjustable text size and audio instructions. Speech-based tools will be introduced only where testing shows acceptable performance across local accents.\n\n## 5. Implementation Plan\n\n### Months 1–3: Co-design and preparation\n\n- Select schools with local education authorities.\n- Assess electricity and connectivity.\n- Consult teachers and families.\n- Conduct baseline learning assessments.\n- Establish data protection rules and procurement requirements.\n\n### Months 4–6: Development and testing\n\n- Configure the offline platform.\n- Adapt and review learning materials.\n- Train teachers and school-based technical leads.\n- Test usability and content safety in a small group of classrooms.\n\n### Months 7–15: Classroom pilot\n\n- Introduce regular supervised practice sessions.\n- Provide ongoing teacher coaching.\n- Maintain devices and monitor implementation.\n- Correct inaccurate content and investigate unequal performance.\n\n### Months 16–18: Evaluation and transition\n\n- Conduct independent endline assessments.\n- Compare results and costs with the control group.\n- Share findings with participating communities.\n- Develop an expansion plan only if evidence supports it.\n\n## 6. Infrastructure and Sustainability\n\nEach school will receive shared tablets and a local content server where needed. Solar charging will be provided where electricity is unreliable.\n\nCore learning activities will work without continuous internet access. Updates and encrypted data transfers will occur when connectivity is available.\n\nOpen standards and exportable content will reduce vendor dependence. Local technicians will receive maintenance training. The education ministry will help assess long-term replacement and support costs.\n\n## 7. Safeguards\n\nThe project will collect only data needed for learning support and evaluation.\n\nStudent records will use pseudonymous identifiers. Access will be restricted by role. Written agreements will prohibit advertising and unrelated model training using student data.\n\nParticipation will follow applicable consent requirements. Students who do not participate in research will retain access to normal instruction.\n\nChildren will not interact with unrestricted generative chatbots. All student-facing materials will come from a reviewed library.\n\n## 8. Evaluation\n\nSubject to statistical power analysis the pilot will randomly assign schools to immediate implementation or delayed rollout.\n\nThe primary measure will be improvement on independent literacy and numeracy assessments. An illustrative target is an average gain of **0.15 standard deviations** above the comparison group. This is a target rather than a promised result.\n\nSecondary measures will include:\n\n- Teacher preparation time.\n- Student participation.\n- Device uptime.\n- Cost per student.\n- Learning outcomes across demographic and language groups.\n\nThe evaluation will distinguish the effects of the full support package from claims about AI alone.\n\n## 9. Illustrative Budget\n\n| Category | Cost |\n|---|---:|\n| Devices and power infrastructure | $100000 |\n| Software and local content development | $110000 |\n| Teacher training and coaching | $80000 |\n| Technical support and maintenance | $60000 |\n| Independent evaluation and safeguarding | $60000 |\n| Project management and contingency | $40000 |\n| **Total** | **$450000** |\n\nThe estimated pilot cost is **$75 per student**. Actual costs will depend on local procurement and infrastructure needs.\n\n## 10. Expected Value\n\nThe project will test whether carefully targeted AI can improve learning while making teachers’ work easier.\n\nSuccess will mean stronger student skills and a locally maintainable system. It will also produce practical evidence about when simpler non-AI approaches may offer better value.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 4.3489296544572165, "classifierCostIndex": 0, "promptTokens": 38, "completionTokens": 1278, "reasoningTokens": 163, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 24589, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "38", "completionTokens": "1278", "reasoningTokens": "163", "cachedTokens": "0" }, "timing": { "headersMs": 2732.775499999989, "firstEventMs": 3346.952874999959, "firstReasoningMs": 7956.076750000007, "firstContentMs": 10925.869540999876, "lastContentMs": 27309.812707999954, "generationMs": 16389.44312499999, "totalMs": 27315.312665999867, "visibleTokensPerSecond": 67.97058274058965, "contentChunkCount": 239, "averageContentChunkCharacters": 27.01673640167364, "maxContentStallMs": 714.0728329999838, "finalContentBurstRatio": 0.12126374477311445, "buffered": false }, "error": null, "routing": null }, { "caseId": "ifeval-2311", "category": "ifeval", "arm": "gpt-6-sol", "at": "2026-09-26T09:20:02.966Z", "model": "azure/gpt-6-sol", "loggedModel": "azure/gpt-6-sol", "content": "A 32 gram serving of unsalted almonds has about 185 calories, not 396. Almonds are calorie-dense because they contain a lot of fat, but 396 calories would be closer to a 68 gram serving. The number you saw may be a labeling or serving-size error.", "evaluation": { "passed": false, "answer": "0", "expected": "all instructions followed", "detail": "Failed: punctuation:no_comma", "score": 0, "metrics": { "instructionsPassed": 0, "instructionsTotal": 1 } }, "sensitivityPassed": false, "sensitivityIncluded": true, "costIndex": 0.11539485745167656, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 164, "reasoningTokens": 98, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 7803, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "164", "reasoningTokens": "98", "cachedTokens": "0" }, "timing": { "headersMs": 1580.9395409999415, "firstEventMs": 2923.116791000124, "firstReasoningMs": 6254.577583000064, "firstContentMs": 8590.109915999928, "lastContentMs": 9421.534665999934, "generationMs": 831.6954169999808, "totalMs": 9421.80533299991, "visibleTokensPerSecond": 78.15361089094651, "contentChunkCount": 46, "averageContentChunkCharacters": 5.3478260869565215, "maxContentStallMs": 470.3354579999577, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2311", "category": "ifeval", "arm": "gpt-6-luna", "at": "2026-09-26T09:20:12.388Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "There should not be 396 food Calories in 32 grams of unsalted almonds. That amount is typically around 185 to 190 Calories. A listing of 396 may refer to kilojoules rather than Calories or to a larger serving. Check the package’s serving size and units.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.012346727549681424, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 351, "reasoningTokens": 286, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4130, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "351", "reasoningTokens": "286", "cachedTokens": "0" }, "timing": { "headersMs": 612.916416999884, "firstEventMs": 759.0618329998106, "firstReasoningMs": 3409.5024170000106, "firstContentMs": 4709.510917000007, "lastContentMs": 4709.67416699999, "generationMs": 0.31462499988265336, "totalMs": 4709.8255419998895, "visibleTokensPerSecond": 203416.76606712842, "contentChunkCount": 46, "averageContentChunkCharacters": 5.5, "maxContentStallMs": 0.01583399996161461, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null }, { "caseId": "ifeval-2311", "category": "ifeval", "arm": "smart", "at": "2026-09-26T09:20:17.098Z", "model": "azure/gpt-6-luna", "loggedModel": "azure/gpt-6-luna", "content": "There should be about **185 calories** in 32 grams of unsalted almonds. Almonds have roughly 579 calories per 100 grams.\n\nA figure of 396 calories may refer to a larger serving or be a labeling or data-entry error. It is not the expected calorie count for 32 grams.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.009549588023935376, "classifierCostIndex": 0.004412840694056412, "promptTokens": 32, "completionTokens": 142, "reasoningTokens": 74, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": "low", "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 2703, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "142", "reasoningTokens": "74", "cachedTokens": "0" }, "timing": { "headersMs": 1636.7520840000361, "firstEventMs": 2045.796667000046, "firstReasoningMs": 3584.9787500000093, "firstContentMs": 4299.74450000003, "lastContentMs": 4299.940458999947, "generationMs": 0.32666700007393956, "totalMs": 4300.071167000104, "visibleTokensPerSecond": 205101.8314823195, "contentChunkCount": 47, "averageContentChunkCharacters": 5.638297872340425, "maxContentStallMs": 0.017500000074505806, "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": 688, "classifierFailed": false, "classifierReused": false } }, { "caseId": "ifeval-2311", "category": "ifeval", "arm": "gpt-6-astra", "at": "2026-09-26T09:20:21.399Z", "model": "azure/gpt-6-astra", "loggedModel": "azure/gpt-6-astra", "content": "A 32 gram serving of unsalted almonds typically contains **about 185 calories** rather than 396.\n\nAlmonds are calorie-dense because they contain a lot of fat. But 396 calories would correspond to roughly 68 grams of almonds.\n\nIf your label shows 396 it may refer to a different portion size or use kilojoules instead of calories. It could also be a labeling error. **396 kilojoules equals about 95 calories** which would still be unusually low for 32 grams of plain almonds.\n\nIf you share the label I can help interpret it.", "evaluation": { "passed": true, "answer": "1", "expected": "all instructions followed", "score": 1, "metrics": { "instructionsPassed": 1, "instructionsTotal": 1 } }, "sensitivityPassed": true, "sensitivityIncluded": true, "costIndex": 0.6610136110681658, "classifierCostIndex": 0, "promptTokens": 32, "completionTokens": 189, "reasoningTokens": 63, "cachedInputTokens": 0, "finishReason": "stop", "resolvedReasoningEffort": null, "loggedMaxTokens": 4096, "loggedInferenceDurationMs": 4425, "loggedFinishReason": "stop", "billedUsage": { "promptTokens": "32", "completionTokens": "189", "reasoningTokens": "63", "cachedTokens": "0" }, "timing": { "headersMs": 331.6077089998871, "firstEventMs": 919.8006670000032, "firstReasoningMs": 3489.446416999912, "firstContentMs": 4752.943208999932, "lastContentMs": 4760.4804999998305, "generationMs": 22.983624999877065, "totalMs": 4775.926833999809, "visibleTokensPerSecond": 5438.65469440389, "contentChunkCount": 66, "averageContentChunkCharacters": 7.924242424242424, "maxContentStallMs": 3.596707999939099, "finalContentBurstRatio": 1, "buffered": true }, "error": null, "routing": null } ] }