Mistral Large 4: Specs, Benchmarks, Pricing & Use Cases

Mistral AI’s Mistral Large 4, nicknamed “Le Chonk,” is a public-preview multimodal flagship model built with a sparse Mixture-of-Experts architecture containing 1.05 trillion total parameters but activating 49 billion per token, alongside a 1.6 billion-parameter vision encoder and a one-million-token context window. Available through the Mistral API from October 6, 2026, with open weights planned for late October under a custom license, it accepts text and images and produces text for use cases including coding agents, cybersecurity, document analysis, finance, legal work, manufacturing, and visual reasoning. Mistral says the model was trained from scratch on roughly 4,000 NVIDIA Grace Blackwell GPUs and supports more than 160 languages, structured outputs, function calling, tools, and agents. Its sparse design lowers per-token computation compared with a dense trillion-parameter model, though self-hosting still requires substantial memory, estimated at roughly 1 TB of GPU memory for 8-bit weights alone. Mistral reports strong benchmark results in software engineering, finance, legal agents, and visual grounding, but many results are vendor-reported and independent evaluations place it ahead of Western open-weight models while behind several leading Chinese alternatives. Pricing is listed at $0.68 per million input tokens, $0.07 for cached input, and $2.09 for output, with the article emphasizing that teams should assess cost per successful task and benchmark the preview model against their own workloads before adopting it.

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