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Generative AI & Modelsupdated 9 min read

Mistral releases 1T-parameter multimodal model with open weights

Mistral released Mistral Large 4, a 1 trillion-parameter multimodal model with 49 billion active parameters and a 1 million-token context window. The model supports text and image inputs and generates text, released under the Mistral Ecosystem Open-Weight License, an MIT derivative with usage restrictions. It excels in cybersecurity, coding agents, and multimodal tasks, scoring 82% on the…

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Key points

  • Mistral Large 4 is a 1T-parameter multimodal model with 49B active parameters, released under the Mistral Ecosystem Open-Weight License
  • Scores 82% on Artificial Analysis Cyber Index, highest for reproducing and patching real software vulnerabilities, per Mistral’s internal benchmarks
  • Supports text + image inputs, excels in coding (61.7% on DeepSWE v1.1) and agentic workflows, with GGUF quants and Hugging Face deployment options

Mistral Large 4 combines Mixture-of-Experts (MoE) architecture with sparse attention mechanisms, including a Pixtral vision encoder for image processing. The model’s text decoder has 72 layers, a hidden dimension of 6,144, and 64 attention heads, while the Pixtral encoder uses 14×14 patches and a patch-merge projector. Benchmarks show strong performance in coding (61.7% on DeepSWE v1.1) and agentic workflows (49.8% on Coding Agent Index), surpassing competitors like DeepSeek V4 Pro 0813 and Qwen3.8 Max. Mistral positions the model for defensive security work, noting that open weights enable custom deployment and fine-tuning without vendor lock-in. The model is available via Hugging Face, with GGUF quantizations provided by Unsloth and llama.cpp, and supports deployment on NVIDIA Blackwell GPUs via vLLM and DSpark for accelerated inference.

Model page: Mistral Large 4 →

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Full story from Hugging Face · by merve primary sourceOpen source ↗

Welcome Le Chonk: Mistral Large 4 on Hugging Face

Hugging Face · 29 October 2026

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This text was published by Hugging Face and written by merve. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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