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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)
    74/283
    Models
    28/55
    Providers
    26
    Vision Models (filtered)
    64
    Tool-enabled (filtered)
    0
    Free Models (filtered)
    Features
    NovitaAI
    kimi-k2
    		$0.57$2.30—
    NovitaAI
    ernie-4.5-vl-424b-a47b
    		$0.42$1.25—
    Mistral AI
    mistral-small-2506
    $0.10$0.09
    -5% off
    $0.30$0.28
    -5% off
    		—
    SCX.ai (Turbo)
    qwen3-32b
    		$0.36$0.87—
    NovitaAI
    qwen3-235b-a22b-fp8
    		$0.20$0.80—
    Z AI
    glm-4-32b-0414-128k
    		$0.10$0.10$0.00
    AWS Bedrock(us)
    llama-4-scout-17b-instruct
    		$0.19$0.73—
    AWS Bedrock
    llama-4-scout-17b-instruct
    		$0.17$0.66—
    NovitaAI
    llama-4-scout-17b-instruct
    		$0.18$0.59—
    AWS Bedrock(us)
    llama-4-maverick-17b-instruct
    		$0.26$1.07—
    AWS Bedrock
    llama-4-maverick-17b-instruct
    		$0.24$0.97—
    NovitaAI
    llama-4-maverick-17b-instruct
    		$0.27$0.85—
    SCX.ai (Turbo)
    llama-4-maverick-17b-instruct
    		$0.53$1.62—
    Vertex AI (OpenAI-compatible)
    qwen3-coder-480b-a35b-instruct
    		$0.22$1.80$0.02
    NovitaAI
    qwen3-coder-480b-a35b-instruct
    		$0.38$1.55—
    MiniMax
    minimax-text-01
    		$0.20$1.10—
    Cerebras
    llama-3.3-70b-instruct
    		$0.85$1.20—
    NovitaAI
    llama-3.3-70b-instruct
    		$0.14$0.40—
    Inference.net
    llama-3.2-11b-instruct
    		$0.07$0.33—
    NovitaAI
    llama-3.2-3b-instruct
    		$0.03$0.05—
    AWS Bedrock(us)
    llama-3.1-70b-instruct
    		$0.79$0.79—
    AWS Bedrock
    llama-3.1-70b-instruct
    		$0.72$0.72—
    NovitaAI
    llama-3-70b-instruct
    		$0.51$0.74—
    Page 5 of 5

    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. PassingRight 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.

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  1. Baidu
  2. Perplexity
  3. Mistral AI
  4. CanopyWave
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