Mistral previewed a 1-trillion-parameter model and promised the weights
Mistral opened a public preview of Mistral Large 4 on Tuesday - a one-trillion-parameter, natively multimodal mixture-of-experts model with roughly 49 billion parameters active per token, trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral’s own European datacenters. The company says the weights will be released by the end of the month and calls it the strongest open-weight model developed outside China; the preview API is live on Mistral Studio now.
The benchmark case is deliberately practical. On the independent Artificial Analysis Cyber Index it ranks in the global top five and leads non-Chinese open models: it scores 82% on a test that has a model reproduce a real open-source vulnerability and then patch it, the highest of any model, and solves 93% of Cybench’s 40 security exercises. Mistral argues this matters because closed models including Claude Opus 5.5 and GPT-6 Astra score near zero on the same test by refusing the task. On coding it scores 61.7% on DeepSWE v1.1 and 28.3% on Terminal-Bench 4.0, and ranked second of five in a blind human evaluation by Surge AI, behind only Claude Opus 5. The first independent placement on general capability is less flattering: on Artificial Analysis’s Intelligence Index, which folds ten evaluations into one score, the preview sits at 38.4 - eighth among open models once its weights arrive, with all seven ahead of it Chinese, led by Xiaomi’s MiMo-V2.6-Pro at 46.3.
WHY IT MATTERS
A trillion-parameter model with the weights promised openly is the milestone the open-weight lane has been pointing at all year, and here sovereignty is doing real work rather than acting as a slogan: European datacenters, a training mix spanning more than 160 languages including every EU official language, and a security model an organization can run on its own metal with no provider able to refuse a task mid-incident. For a builder, the cyber numbers are the interesting part - the refusals that make closed models safe in a chat window are exactly what block legitimate vulnerability research, and Mistral is selling their absence. The caveat deserves one line: the launch scores are Mistral’s own, and nothing is downloadable until the promised release.