Mistral Large 3 — Local AI Model by Mistral AI

作者： Jakub Rusinowski · 最后更新： 2026年7月10日

PREVIEW (June 2026, specs unverified). Mistral's open-weight flagship — reported as a 675B-total / 41B-active MoE with multimodal input under Apache 2.0 and a 256K context window. Datacenter-class to self-host; estimates here are provisional pending the Hugging Face model card.

Hardware Requirements

Mistral Large 3 675B-A41BMin 408 GB VRAM · Q4_K_M · 256,000 ctx ·

Recommended GPU

The cheapest GPU that runs Mistral Large 3 locally (min 408 GB VRAM) is the Apple M3 Ultra (512 GB).

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How to Run Locally

Install Ollama then run: ollama run

Minimum VRAM: 408 GB. For best results use Q4_K_M quantization.

Mistral Large 3 — Frequently Asked Questions

How much VRAM does Mistral Large 3 need?

Mistral Large 3 needs about 408 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Mistral Large 3 675B-A41B (408 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.

Can I run Mistral Large 3 on an RTX 4090 (24 GB)?

Mistral Large 3's smallest variant needs about 408 GB, which exceeds a single RTX 4090 (24 GB). Use multiple GPUs, a higher-VRAM card, or Apple Silicon with large unified memory.

What quantization should I use for Mistral Large 3?

Q4_K_M is the best balance of quality and VRAM for Mistral Large 3 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.

How do I run Mistral Large 3 with Ollama?

Install Ollama, then run: ollama run . This downloads Mistral Large 3 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.

Can I Run Mistral Large 3 on My GPU?