Mistral

Mistral AI focuses on efficiency and coding capabilities. Their “Mixture of Experts” (MoE) architecture (Mixtral) changed the game.

When to Use

• Coding: Mistral Large 2 (Codestral) is specifically optimized for code generation.
• Efficiency: Mixtral 8x7B offers GPT-3.5+ performance at a fraction of the inference cost.
• Open Weights: Apache 2.0 licenses (for smaller models).

Core Concepts

MoE (Mixture of Experts)

Only a subset of parameters (experts) are active per token. High quality, low compute.

Codestral

A model trained specifically on 80+ programming languages.

Le Chat

Mistral’s chat interface (chat.mistral.ai).

Best Practices (2025)

Do:

• Use codestral-mamba: For infinite context window coding tasks (linear time complexity).
• Deploy via vLLM: Mistral models run exceptionally well on vLLM.

Don’t:

• Don’t ignore small models: Mistral NeMo (12B) is surprisingly capable for RAG.

References

• Mistral AI Documentation