Mistral AI
Mistral AI is a Paris-based startup founded in 2023, specializing in efficient, open-weight LLMs.
At-a-Glance
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Founded in April 2023 by Arthur Mensch, Guillaume Lample, and Timothée Lacroix
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Mistral’s open models are released under Apache 2.0, meaning they can be used, modified, and redistributed under that license’s terms
About Mistral AI
Mistral AI is a Paris-based AI company focused on building frontier AI and making it more accessible. Mistral positions itself against opaque-box AI approaches of the big AI.
Mistral AI focuses on developing powerful, configurable, and open-source models. It allows builders and enterprises to train, fine-tune, and deploy AI solutions with more flexibility and control.
Popular Models of Mistral AI
Below are some popular Mistral models.
| Model Name | Launch Date | Open/Closed | Strengths |
| Mistral 7B | Sep 2023 | Open (Apache 2.0) | A strong general-purpose base model for chat, summarization, and custom fine-tuning while staying relatively small/efficient. Good for self-hosting. |
| Mistral Large 2.1 | Nov 2024 | Closed (API Only) | Positioned as a flagship offering in Mistral’s current model lineup. Good for complex instructions and higher-accuracy outputs. |
| Mistral Small 3.1 | March 2025 | Open (Apache 2.0) | Optimized for speed, cost-efficiency, and can be deployed on edge devices and laptops. |
| Codestral | July 2025 | Closed (API model) | Best for coding workflows like code completion and coding assistance inside IDE-style experiences |
| Devstral 2 | Dec 2025 | Open (Apache 2.0) |
Mistral's open-source coding agent, specifically designed for code generation, completion, and assisting developers with various software engineering tasks. |
Enterprise-Grade and Privacy-First Approach
Beyond open-source models, Mistral AI also focuses on providing enterprise-grade solutions. Their offerings are designed to be AI agent-ready and committed to privacy.
Mistral AI enables organizations to deploy and build with AI in on-premise, cloud, edge environments and devices, while maintaining full control over their data.
Engineering Choices for Faster Inference
Mistral’s differentiation also shows up in its engineering choices. Their 7B announcement highlights techniques like Grouped-Query Attention (GQA) for faster inference and Sliding Window Attention (SWA) for handling longer sequences at lower cost. These details matter if you care about running models cheaper, faster, or on constrained hardware.
Future Prospects
Strategically, Mistral appears to be working towards distributed intelligence, emphasizing small, customizable models for real-world apps over massive scale. They achieved a valuation of €11.7 billion in September 2025 after a €1.7 billion Series C round led by ASML.
Mistral AI’s growth reflects a broader shift in the AI ecosystem, where teams value deployment flexibility, ownership, and practical use cases as much as raw model capability.
Mistral AI is a critical partner for Cisco Customer Experience (CX) as we build towards an Agentic-AI-led future. - Liz Centoni, Executive Vice President and Chief Customer Experience Officer, Cisco
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