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Mixtral 8x22B
Mistral's largest open-weights MoE — 141B total / 39B active, Apache 2.0
0Visit Mixtral 8x22B
https://mistral.ai/news/mixtral-8x22b
About Mixtral 8x22B
Mistral AI's largest open-weights mixture-of-experts model, released April 17, 2024. Mixtral 8x22B uses a sparse MoE architecture with 141B total parameters and ~39B active per token (8 groups of 22B, routing 2 experts per token). At launch it was the strongest open-weight model on reasoning, math, and coding benchmarks — outperforming LLaMA 3 70B and GPT-3.5 Turbo on most tasks. Supports 64k token context, natively multilingual (English, French, German, Italian, Spanish), with function calling and JSON mode. Weights released under Apache 2.0 on Hugging Face.
Key Features
Mixtral 8x22B Pros & Cons
✅ Pros
- +Best open-weight performance at launch — top of open-source leaderboards on reasoning, MATH, and coding
- +MoE efficiency: 141B total params with only ~39B active means faster tokens-per-second than a comparably-performing dense model
- +Apache 2.0 license — fully permissive, fine-tune and deploy without restrictions
- +64k context window covers long-document tasks most 2024 open models couldn't handle
- +Multilingual out-of-the-box across five European languages
⚠️ Cons
- −Heavy self-hosting requirements: needs ~4× A100 80GB GPUs or equivalent for inference
- −Superseded for most use cases by Mistral Small 4 and newer open-weight models
- −No multimodal / vision support — text-only
- −Commercial API has been deprecated in favor of newer Mistral models on La Plateforme
Who Is Mixtral 8x22B Best For?
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