Mistral says it is working with NVIDIA on AI for industrial engineering

Mistral said on Wednesday it is collaborating with NVIDIA to develop a new generation of AI-native engineering workflows powered by NVIDIA accelerated computing.

Simulation and design

Mistral says the initiative combines Mistral Large 4 with Mistral's data generation and physics modeling pipelines, accelerated by NVIDIA CUDA-X libraries and NVIDIA Warp. The aim, according to Mistral, is to accelerate engineering simulation and enable closed-loop workflows that connect simulation, AI model development and engineering design. The companies will also work to integrate Mistral's models with NVIDIA Omniverse libraries for GPU-accelerated 3D scene generation and SimReady asset creation.

Benchmarks for physics and agentic AI

Mistral says a central focus is public benchmarks and open datasets for evaluating physics models, giving researchers, developers and industrial teams a shared foundation to compare model accuracy and performance and to build and validate automated CAD-to-simulation workflows.

The companies also plan dedicated evaluations and benchmarks for agentic AI in computer-aided engineering (CAE) and electronic design automation (EDA), aimed at aerospace, automotive and semiconductor use cases. Mistral says these will assess agents' ability to use engineering tools, complete multistep workflows and produce technically correct results, while measuring execution time and computational cost.

"For too long, the pace of engineering has been set by the pace of simulation," said Neil Ashton, VP of Computational Engineering at Mistral.

"The next wave of engineering breakthroughs will come from exploring ideas that were once too complex or time-consuming to test," said Tim Costa, vice president and general manager of industrial and computational engineering at NVIDIA.

Existing partnership

Mistral says the work builds on an ongoing partnership with NVIDIA. The companies previously co-developed Mistral NeMo and are working together through the NVIDIA Nemotron Coalition to develop a frontier base model.

Mistral recently introduced a public preview of Mistral Large 4. Mistral says the multimodal model has approximately 1 trillion total parameters and 49 billion active parameters, was trained on 3,800 NVIDIA Grace Blackwell GPUs in Mistral-operated data centers in Europe, and has weights planned for release at the end of October. Mistral also says it is bringing additional NVIDIA-powered infrastructure online as part of a compute roadmap targeting 1 GW of capacity by 2030.