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Mistral releases improved Mistral Large 4 open weights for coding and cybersecurity

Le Chonk: Built for Coders, Trusted by Defenders.

Who
Mistral
What
releases the improved open weights of Mistral Large 4
Quote
Today, we're releasing the weights of this improved Mistral Large 4.

What happened

Mistral AI released open weights for an improved Mistral Large 4 (Le Chonk), its 1-trillion-parameter multimodal model previewed earlier this month. Mistral reports a 48% Artificial Analysis Coding Agent Index score with 47% fewer tokens per task than GLM-5.3, alongside three reasoning modes. The Mistral Ecosystem Open-Weight license permits use, modification, fine-tuning, and commercialization, but businesses operating Model-as-a-Service offerings must obtain a separate commercial license before commercial use.

Why it matters

The reported coding results pair benchmark scores with token usage, providing a concrete comparison of performance and inference efficiency against other open-weight models.

Read next

See the full storyMistral Releases Large 4 Open Weights With Licensing Conditions and Launch-Day Inference Support

Reported by 5 sources

    The story so far

    Mistral AI released improved open weights for Mistral Large 4, also called Le Chonk, with launch-day inference support from NVIDIA and vLLM. Mistral says its license allows free use, modification, fine-tuning and commercialization, but businesses operating Model-as-a-Service offerings must obtain a separate license before commercial use. The Decoder describes that exception more narrowly as covering companies offering Large 4 as a commercial cloud service, and reports that access requires review and contractual restrictions. The multimodal model targets agentic coding and cybersecurity. Artificial Analysis lists 1.05 trillion total parameters and 52 billion active parameters, and says it narrowly leads open-weight models developed outside China. Mistral reports a 48% Artificial Analysis Coding Agent Index score using 47% fewer tokens per task than GLM-5.3, and first place among open models on Cognition’s FrontierCode. Those coding claims have a different scope from the overall Artificial Analysis score of 26 reported by The Decoder, which places it behind several Chinese rivals. NVIDIA announced NVFP4 weights on Hugging Face and an optimized Dynamo configuration for distributed inference. vLLM added support for FP8 and NVFP4 checkpoints with a built-in DSpark drafter, and describes the model as supporting a 1-million-token context.

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