Mistral AI Launches Magistral Small 1.1: Powerful AI Reasoning in a Compact Format
French company Mistral AI has unveiled Magistral Small 1.1, a reasoning model featuring 24 billion parameters. It can be operated locally on a single graphics card, lowering the barrier for private AI deployment among smaller companies.
What happened?
French AI company Mistral AI is launching Magistral Small 1.1, a reasoning AI model with 24 billion parameters. The model is optimized for local deployment and can be executed on consumer hardware such as a single Nvidia RTX 4090 graphics card. By employing GPTQ compression technology, the model size has been reduced to approximately 12 gigabytes, enabling advanced AI reasoning to run locally without dependency on external cloud services.
Key facts
| Modellnamn | Magistral Small 1.1 |
|---|---|
| Antal parametrar | 24 miljarder (24B) |
| Lagringsstorlek (GPTQ) | Cirka 12 GB |
| Hårdvarukrav | 1x Nvidia RTX 4090 (24GB VRAM) |
Why it matters
The launch marks a shift from massive cloud-based models toward more cost-effective and accessible AI solutions for local infrastructure. Through a new transparent reasoning mechanism, in which the model displays its step-by-step thought processes via specific settings, users can track how conclusions and code are generated. This lowers the entry threshold for companies looking to build their own high-privacy, private AI systems.
Who is affected?
The model is targeted at small and medium-sized enterprises, developers, and organizations within financial auditing, education, and software development. It is particularly relevant for entities with stringent data security and privacy requirements that prefer not to transmit business data via external APIs.
Impact on the EU
As Mistral AI is based in France, its models are developed with consideration for EU regulations such as the GDPR and the EU AI Act. The capability to run Magistral Small 1.1 entirely locally facilitates compliance with strict data protection requirements for European companies, as no sensitive information needs to be transmitted to cloud services outside the union.
What else you should know
The model's transparency is driven by a specific format where reasoning is encapsulated within dedicated thought-process tags. According to reported studies, this format has increased user trust in AI-generated conclusions in scenarios requiring auditing and traceability. Notably, reporting on the launch also references market data and user surveys from 2025 and 2026 regarding the adoption of compressed AI models in the private sector.
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