Mistral AI releases the weights of Mistral Large 4 (Le Chonk)
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Mistral AI released the weights of Mistral Large 4 (Le Chonk) — a 1 trillion parameter multimodal model with three more weeks of reinforcement learning added after the public preview. Company-reported, it leads Cognition's private FrontierCode 2.0 at 19.7% and rose on Terminal-Bench 4.0 from 28% in the preview to 41% while cutting output tokens by 30%. Its Artificial Analysis Coding Agent Index score of 48% is effectively tied with GLM-5.3, the top open-weight model, while using on average 47% fewer tokens per task, and its Cyber Index score is 51%. It offers reasoning in three modes, low, medium and high, and the company said its refusal rate for malicious cyber requests, at an average 96.6%, is the highest among the open models measured. It said the model was trained from scratch on European facilities.
Why it matters
A 1 trillion parameter model has appeared on the open-weight side putting coding and defensive security forward together, and the focus of the company's figures is not the score but how few tokens it takes to reach the same score. That is aimed at the situation where cost, not performance, becomes the limit first when an agent is left running for a long time. Putting a number on the line between doing defense and refusing attack requests, in the form of a refusal rate, is also rare for an open model. All the figures are company-reported, there is no independent reproduction outside the Artificial Analysis index, and FrontierCode 2.0 is a private evaluation, so outside checking is hard.
Source — Primary sources first; secondary reports are labelled “Press”
Officialmistral.aihttps://mistral.ai/news/mistral-large-4-oss/Added in Week 45, 2026 · See that week
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