Most flagship models dominating the market are from frontier labs and are closed models. French AI lab Mistral seeks to change that with its latest model.
On Tuesday, Mistral launched a public preview of Mistral Large 4 (ML4), le Chonk, its new flagship, 1-trillion-parameter, open-weight model meant for general agentic capabilities. Mistral claims its competitive advantage lies in the fact that it is comparable to the best closed models while staying competitive with open-weight models three times its size. Meanwhile, it was trained on 4,000 NVIDIA Grace Blackwell GPUs at what it describes as a fraction of its competitors' cost.
With this launch, Mistral is also telling a cybersecurity story, not only claiming it is strong in both offensive and defensive categories, but also capitalizing on the fact that it is an open-weight model. Mistral's co-founder and chief scientist Guillaume Lample told The Deep View that the open-weight nature of the model allows companies to safely build and deploy cybersecurity defenses without fearing that the model is suddenly deprecated or sundowned.
"Basically, new [cybersecurity] workflows require a lot of tokens, a lot of inference, so you cannot afford to be vulnerable to the fact that the model you are using to protect yourself might disappear one day, or might be too limited," said Lample.
Beyond cyber, the new model is proficient in other realms including coding, domain-specific knowledge work, and multi-modality. Some other features, according to the blog post, include:
- Based on its grounding capabilities, "it outperforms all existing models, including the closed ones," Mistral claims.
- Deployment on Mistral's own data centers in Europe and served in preview on that infrastructure.
- Trained using reinforcement learning, and the team continues to see rapid progress. This is notable as many open models are mostly distilled, and the team is highlighting its own research, training infrastructure, and expertise.
The open-weight model is aimed primarily at enterprises deploying it on-premise or in a private cloud, but it will also be available through Mistral’s API. At one trillion parameters, it’s too large to run locally on a desktop or laptop and may be impractical for some universities to run themselves. The weights will be released on October 27.
Our Deeper View
Open-weight models play a key role in the AI industry because they let companies and users retain control over which model they use and how they use it. Because the weights are publicly available, users can inspect, test, and run a model themselves to judge whether it meets their needs. Once a model is deployed, they also hold a complete copy of it, so they don't depend on a provider's decision to continue to maintain it or keep it available. This matters because every model version behaves slightly differently. Even a forced migration to a newer, more capable model can set off a chain reaction that breaks systems built around the old one. That makes ongoing efforts to build open-weight models that rival closed models from leading labs especially significant. Much of the open-weight ecosystem is driven by the Chinese frontier labs, so the industry tends to welcome alternatives from providers like Mistral.