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Mistral AI announced Mistral Large 4 on October 6, a model with one trillion parameters in total. Only 49 billion of them work on any single request, which is how a model this large keeps the cost of each answer under control. The company trained it from scratch on 3,800 Nvidia Grace Blackwell GPUs in its data centers in France, and the same cluster now serves the public preview. The article walks through how that design works using a simple hospital comparison, so the idea of experts switching on and off becomes easy to picture.

The company reports 62% on DeepSWE v1.1, a coding benchmark, a little ahead of several well-known open-weight models, and it pitches the model heavily for cybersecurity work. Mistral itself calls the benchmark figures preliminary, and the cyber claims arrived without published numbers. The article keeps those two things apart, so you can see what has been confirmed by several outlets and what still rests on the company's word.

The weights are scheduled for October 27, and that is the date when researchers and companies can start testing the model themselves. We also explain what open-weight means in practice and how the €3 billion Series D round connects to the cluster behind this release. If you follow GPUs and data centers, the training setup is probably the most interesting part of the story.

Xiaomi released MiMo-V2.6 today, and the release notes read less like a routine update and more like a case study in how far reinforcement learning can stretch a training budget. Two models, a 1.02 trillion-parameter Pro and a leaner 309-billion-parameter Flash, both natively multimodal, both open-weight under MIT, both trained through a six-day RL run that Xiaomi streamed live.
 
The scores are the part that stands out. Pro hits 46 on the Artificial Analysis Intelligence Index, the highest mark any open-weight model has posted there, tying it with a proprietary rival that costs several times more to run per token. It also tops the field on a cybersecurity benchmark and adds computer-use skills the previous generation didn't have.
 
We go through the architecture, the training approach, the reward-hacking defenses Xiaomi built in, and where the model still falls short against closed-source leaders.
 
Read the full story: https://literouteracademia.com/2026/09/23/xiaomi-releases-mimo-v2-6-as-its-strongest-open-model-yet/