Mistral AI Models Compared (2026): All Models Explained

The most capable models from each major lab.

Long chain-of-thought models built for hard math, code, and planning.

Models specialised for software engineering and code generation.

Models strong at tool use, multi-step workflows, and agentic systems.

Production-grade workhorses with the best speed and cost.

Models that natively understand text, images, and beyond.

Generate and edit still images from text or reference images.

Generate short video clips from text or image prompts.

Models that understand or generate audio beyond plain speech TTS.

Text-to-speech and voice models for natural spoken audio.

Embedding models for search, RAG, clustering, and semantic similarity.

Models with publicly-released weights you can self-host or fine-tune.

Downloadable weights for self-hosting, fine-tuning, and private deployment.

Closed-weights API-only models from major labs.

Production-ready models for teams that need reliability, security, and scale.

Models popular in consumer apps, chat products, and creative tools.

All models from OpenAI — GPT, o-series and beyond.

Claude family of models from Anthropic.

Gemini family of models from Google DeepMind.

Open-weights Llama family from Meta AI.

Frontier-class open-weights models from DeepSeek.

Grok models from xAI.

Qwen family of open-weights models from Alibaba.

Embedding models from Voyage AI.

Midjourney text-to-image models.

FLUX image-generation models from Black Forest Labs.

Stable Diffusion image models from Stability AI.

Gen-series text-to-video models from Runway.

Kling text-to-video models from Kuaishou.

Text-to-speech voice models from ElevenLabs.

Sonic low-latency text-to-speech models from Cartesia.