Family Mistral · 675B parameters★ Made in France

Mistral Large 3 675B

675B/41B active MoE + 2.5B vision encoder, Apache 2.0. #2 OSS non-reasoning model on LMArena. Trained on 3,000 H200s.

🇫🇷 Mistral AI·License Apache 2.0·Context 250k tokens·Output December 2025← Catalog

01What it can do

Strengths
  • Flagship FR frontier
  • Apache 2.0
  • #2 OSS non-reasoning LMArena
  • Multimodal
Limitations to know
  • —405 GB in Q4 — B200/H200 server required
Architecture
Granular MoE 675B/41B active + 2.5B vision encoder · 256k ctx
Training
From scratch on 3000 H200s.
Ideal for
Open EU frontierVisionMultilingual

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$# HuggingFace : mistralai/Mistral-Large-3-675B-Instruct-2512
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
405 GB
Q5_K_M
Good quality/size compromise
485 GB
Q8_0
Nearly indistinguishable from FP16
720 GB
FP16
Full precision — server use
1350 GB
Fallback CPU · If you don't have a GPU, allow 480 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Mistral Large 3 675B?

To run Mistral Large 3 675B locally with Q4 quantization, you need about 405 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — this model exceeds this mini-PC's GPU capacity: choose a smaller model or suitable infrastructure.

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This model in your private ChatGPT, without the cloud

Too large for your machine? The kit gives you the model that fits in your VRAM

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03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~1t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~5t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~15t/s
RTX 4090, M4 Max, Radeon 7900