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Mistral

Mistral AI, France

The European one: fast, light, and with the data staying here

A French company, models running on European servers and part of the weights published. For anyone with constraints on where data ends up, this changes the conversation.

What it is like

Mistral plays a different game. It does not chase the most powerful model in the world, it bets on three concrete things: it answers fast, it costs little, and the data stays in Europe. In a public office or a company that has to answer to an auditor on GDPR, that last point weighs more than a few benchmark points.

Where it is strong

• European servers: the data does not cross the ocean
• Fast and cheap for anyone using it via API
• Some of the models have published weights
• Very good in French, Italian and Spanish

Where it falls

• On complex problems it lags behind the frontier models
• Smaller ecosystem: fewer guides, fewer integrations
• The name means little to whoever has to approve the spend

When it is worth using

Public administration, healthcare, anyone who has to prove where the data sits.

One test to run on it

Try it in your own language on a piece of trade writing: that is where it holds up better than expected.

Open Mistral and try it ↗

What it does inside Grace

It joins the seven way comparison as a second opinion on your prompt.

Compare it on your prompt →

The AIs Grace compares

• Claude: Writes long without losing the thread, and says when it does not know
• ChatGPT: The best known, and the one that sounds certain even when it is wrong
• Gemini: The one that lives inside Google, with the roomiest memory
• Qwen: The open one, the one you can take home
• Grok: Wired into X, with the loosest tongue of them all
• Perplexity: Answers with the sources at the bottom, so you can check it

Say what you mean. Get what you need.

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