Mistral and Nvidia plan to use AI to speed up how cars, planes and chips are designed and tested, and to publish open tests so others can check the results.
Mistral and Nvidia are teaming up to use AI to speed up engineering simulations and industrial product design. Simulations are computer tests that show how a design might behave before anyone builds it. The partners say they want design, simulation and AI training to run in one continuous workflow.
Mistral will bring its language model, Mistral Large 4, and its physics AI. Physics AI is software built to model how things behave in the real world. Nvidia adds its CUDA-X and Warp software libraries and Omniverse, its tool for 3D simulations. The target industries are aerospace, automotive and semiconductors.
Mistral Large 4 has about one trillion parameters, the settings an AI model learns during training. It was trained on 3,800 Nvidia Grace Blackwell chips in Europe. It is set to ship in late October as an open-weight model, meaning its trained settings are published for others to use.
The companies also plan to release public benchmarks and open datasets. These would let outside teams test and compare physics models and AI agents that work with engineering software. If that happens, smaller firms may be able to try similar tools instead of relying on a single vendor.
The two have worked together before on Mistral NeMo, and they are working on an open foundation model as part of the Nemotron Coalition. Mistral also wants to grow its computing capacity to one gigawatt by 2030.
The plan is to speed up product design with AI, but the real test is whether the promised open benchmarks let outsiders check the results.
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