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    Open Source Models

    Open-weight models — Llama, DeepSeek, Qwen, GLM, Kimi, GPT-OSS, Gemma, and more — served through one API

    Compare
    Use Case
    Capabilities
    Provider
    Status
    Input Price ($/M tokens)
    Output Price ($/M tokens)
    Context Size (tokens)
    76/258
    Models
    28/55
    Providers
    25
    Vision Models (filtered)
    62
    Tool-enabled (filtered)
    0
    Free Models (filtered)
    Features
    Vertex AI (OpenAI-compatible)
    glm-5
    		$1.00$3.20$0.10
    Alibaba Cloud(cn-beijing)
    glm-5
    		$0.57$2.58—
    EmberCloud
    glm-5
    		$0.72$2.30$0.14
    Alibaba Cloud
    glm-5
    		$0.57$2.58—
    NovitaAI
    glm-5
    		$1.00$3.20$0.20
    Baidu
    glm-5
    		$1.00$3.20$0.20
    Z AI
    glm-5
    		$1.00$3.20$0.20
    MiniMax
    minimax-m2.5
    		$0.30$1.20$0.03
    Nebius AI
    minimax-m2.5
    		$0.30$1.20—
    NovitaAI
    minimax-m2.5
    		$0.30$1.20$0.03
    DeepInfra
    qwen3-vl-30b-a3b-instruct
    		$0.15$0.60—
    NovitaAI
    qwen3-vl-30b-a3b-instruct
    		$0.20$0.70—
    NovitaAI
    qwen3-235b-a22b-fp8
    		$0.20$0.80—
    Moonshot AI
    kimi-k2.5
    		$0.60$3.00$0.10
    EmberCloud
    kimi-k2.5
    		$0.40$1.98$0.22
    Alibaba Cloud(cn-beijing)
    kimi-k2.5
    		$0.57$3.01—
    DeepInfra
    kimi-k2.5
    		$0.45$2.25$0.07
    Alibaba Cloud(us-virginia)
    kimi-k2.5
    		$0.57$3.01—
    Alibaba Cloud(eu-frankfurt)
    kimi-k2.5
    		$0.57$3.01—
    Alibaba Cloud
    kimi-k2.5
    		$0.57$3.01—
    NovitaAI
    llama-3.2-3b-instruct
    		$0.03$0.05—
    NovitaAI
    llama-3-70b-instruct
    		$0.51$0.74—
    NovitaAI
    qwen3-vl-235b-a22b-thinking
    		$0.98$3.95—
    DeepInfra
    qwen3-vl-235b-a22b-instruct
    		$0.20$0.88$0.11
    NovitaAI
    qwen3-vl-235b-a22b-instruct
    		$0.30$1.50—
    MiniMax
    minimax-text-01
    		$0.20$1.10—
    MiniMax
    minimax-m2.1-lightning
    		$0.12$0.48—
    EmberCloud
    glm-4.7-flash
    		$0.06$0.40$0.01
    Z AI
    glm-4.7-flashx
    		$0.07$0.40$0.01
    Z AI
    glm-4.6v-flashx
    		$0.04$0.40$0.00
    NovitaAI
    minimax-m2.1
    		$0.30$1.20$0.03
    MiniMax
    minimax-m2.1
    		$0.27$1.10—
    NovitaAI
    glm-4.7
    		$0.60$2.20$0.11
    Z AI
    glm-4.7
    		$0.60$2.20$0.11
    Together AI
    glm-4.7
    		$0.45$2.00—
    Cerebras
    glm-4.7
    		$2.25$2.75—
    EmberCloud
    glm-4.7
    		$0.38$1.98$0.19
    ByteDance
    glm-4.7
    		$0.60$2.20$0.11
    Vertex AI (OpenAI-compatible)
    glm-4.7
    		$0.60$2.20—
    Z AI
    glm-4.6v
    		$0.30$0.90$0.05
    NovitaAI
    glm-4.6v
    		$0.30$0.90$0.06
    NovitaAI
    deepseek-v3.2
    		$0.27$0.40$0.13
    ByteDance
    deepseek-v3.2
    		$0.28$0.42$0.06
    Vertex AI (OpenAI-compatible)
    deepseek-v3.2
    		$0.56$1.68$0.06
    DeepInfra
    deepseek-v3.2
    		$0.26$0.38$0.13
    MiniMax
    minimax-m2
    		$0.20$1.00$0.03
    Vertex AI (OpenAI-compatible)
    kimi-k2-thinking
    		$0.60$2.50$0.06
    AWS Bedrock
    llama-3.1-70b-instruct
    		$0.72$0.72—
    AWS Bedrock(us)
    llama-3.1-70b-instruct
    		$0.79$0.79—
    AWS Bedrock(us)
    llama-4-maverick-17b-instruct
    		$0.26$1.07—
    Page 3 of 5

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    © 2026 LLM Gateway. All rights reserved.

    Open-weight models have closed most of the gap with proprietary frontiers: DeepSeek V4, Qwen3.7, GLM-5, Kimi K2, and MiniMax M3 sit near the top of real-world leaderboards, joined by OpenAI's GPT-OSS and Google's Gemma releases. Their weights are public — but running a 200B+ parameter model yourself means serious GPU infrastructure.

    This page lists open-weight models served by hosted providers, so you get the openness — inspectable weights, no lock-in, the option to self-host later — with API convenience. LLM Gateway itself is open source (AGPLv3) and self-hostable, so the whole stack can run on your terms.

    Frequently asked questions

    What is the best open source LLM?

    DeepSeek V4, Qwen3.7, GLM-5.2, Kimi K2.6, and MiniMax M3 are the current leaders, each within striking distance of proprietary frontier models. For smaller, hardware-friendly options, GPT-OSS 20B, Gemma 4, and Qwen3.5 9B are the standouts.

    What does 'open source' mean for LLMs?

    Usually 'open weight': the trained weights are downloadable, but licenses vary — some are Apache 2.0 or MIT, others (like the Llama license) carry usage restrictions, and training data is rarely published. Check the license of a specific model before building on it.

    Should I self-host or use an API?

    Self-hosting pays off with steady high volume, strict data-residency needs, or fine-tuned weights. For everything else, per-token APIs are cheaper than idle GPUs. A middle path: develop against hosted open models and keep self-hosting as an exit option, since the weights are public.

    Are open models cheaper than proprietary ones?

    Dramatically, per token. Competition among hosts drives prices down — DeepSeek V4 Flash and Qwen3 Coder 30B cost 10–50x less than frontier proprietary models. The list above shows every provider's price for each model.

    is now on LLM Gateway — 30% off open-source modelsends in 7d 10:22:19
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