In mid-2023, a brand-new Paris startup raised a jaw-dropping €105m before it had even launched a product. That company, Mistral AI, is now one of Europe’s most-watched contenders to OpenAI and Anthropic. Here’s how it happened, what Mistral is building, and why it matters for entrepreneurs and professionals betting on the next wave of AI.

What is Mistral AI and who’s behind it?

Mistral AI was founded in 2023 by three veterans of the world’s top AI research labs:

• Arthur Mensch (ex-Google DeepMind)
• Guillaume Lample (ex-Meta FAIR)
• Timothée Lacroix (ex-Meta FAIR)

Their mission: build high-performance foundation models with an emphasis on open-weight releases (models you can download and run) and developer-friendly tooling—positioning Mistral as a European AI champion rather than a clone of US rivals. Early coverage of the company’s ambitions and record-breaking seed came from Sifted and others.

The headline: a €105m seed to challenge OpenAI

In June 2023, Mistral AI closed a €105m (~$113m) seed round—exceptional both in size and timing. It was reported as one of Europe’s largest-ever seed rounds, led by Lightspeed Venture Partners, and set expectations that the team would move fast on competitive, developer-ready models (TechCrunch).

Within months, the company began shipping models that appealed to startups and enterprises seeking strong performance without being locked into closed APIs.

What Mistral is building: fast, capable, and often open-weight

Mistral’s product strategy blends open-weight releases (downloadable models) with hosted APIs and enterprise partnerships.

Key model releases and milestones

• Mistral 7B (Sept 2023): A compact open-weight LLM that impressed developers for its speed and quality relative to size, released under a permissive license (Mistral).
• Mixtral 8x7B (Dec 2023): A sparse mixture-of-experts (MoE) model that routes each token through a subset of its “experts,” delivering strong performance at lower compute cost. It quickly became a favorite among open-weight practitioners (The Verge).
• Mistral Large (Feb 2024): The company’s most capable reasoning model, offered via API and through cloud partners; it marked a step closer to frontier performance (Mistral).
• Mixtral 8x22B (2024): A bigger MoE model for higher-end use cases while retaining the efficiency advantages of sparse activation (Mistral).
• Codestral (2024): A code-focused model aimed at software development workflows such as code generation, completion, and refactoring (Mistral).

Mistral also launched Le Chat, a consumer-facing chatbot, and operates a commercial API for hosted access to its models.

Distribution and partnerships: Microsoft Azure and beyond

In early 2024, Microsoft announced a partnership to bring Mistral’s models to Azure, giving enterprises a familiar, compliant environment to deploy them. Microsoft also made a minority investment in Mistral as part of the collaboration (Microsoft; Reuters).

For buyers, this means you can evaluate Mistral models alongside OpenAI, Anthropic, and others in the same cloud environment, often with your existing governance and procurement workflows.

Funding since the seed: momentum keeps building

• Series A (Dec 2023): Mistral raised roughly €385m at a multibillion-dollar valuation, with investors including a16z and Lightspeed, giving it more compute and talent firepower (Reuters).
• Series B (June 2024): Another €600m round reportedly valued the company around €5.8-6bn, cementing its status as Europe’s flagship AI model company (Reuters; TechCrunch).

In short: the record seed wasn’t a one-off. Capital has continued to flow as Mistral shipped credible models and signed distribution deals.

Why Mistral matters for entrepreneurs and teams

Mistral is more than an “OpenAI rival.” It represents a distinct product philosophy with practical benefits for builders:

• Open-weight optionality: Download certain models and run them on your own hardware or private cloud. That’s attractive for data-sensitive industries and for cost control.
• Efficient performance: MoE designs like Mixtral 8x7B and 8x22B can punch above their weight in quality while keeping inference costs manageable.
• Multi-cloud access: Use Mistral via its own API or through Azure; this reduces vendor lock-in and simplifies evaluations.
• European compliance posture: As the EU AI Act advances, expect European providers to lean into transparent model documentation and risk management—useful if you operate under EU rules (European Parliament).

How does Mistral compare to OpenAI and Anthropic?

OpenAI and Anthropic still lead at the absolute frontier with models like GPT-4o and Claude 3, but Mistral is competitive for many real-world tasks—especially where cost, latency, and deployment control outweigh the need for the single top score on benchmarks. In many stacks, teams run a portfolio of models, using frontier APIs for complex reasoning and open-weight models for routine tasks or on-prem needs.

Challenges to watch

• Compute and efficiency: Training competitive models is capital- and compute-intensive. Mistral’s MoE bet helps at inference time but training still requires large-scale infrastructure.
• Monetization mix: Balancing open-weight releases with a sustainable API and enterprise business model is a strategic tightrope for any “open” AI company.
• Regulation: The EU AI Act introduces transparency and safety obligations that providers must operationalize. European AI startups, including Mistral, have been active in policy discussions about proportionate rules for open models (Euractiv).
• Competition: Beyond US giants, Europe’s own cohort—like Germany’s Aleph Alpha—continues to push on specialized and sovereign AI (Reuters).

Practical next steps for teams evaluating Mistral

• Scope use cases: For chat, summarization, RAG, and code, test Mistral’s latest models against your real data. Consider Mixtral for cost-sensitive, high-throughput tasks.
• Compare TCO: Model quality matters, but so do latency, hardware needs, and inference costs. Open-weight deployments can pay off at scale.
• Pilot in your cloud: If you’re already on Azure, trial Mistral via Azure AI Model Catalog to simplify security reviews and procurement.
• Plan for governance: Align your evaluation with AI Act-style controls (risk assessment, documentation, output monitoring) to future-proof deployment in the EU.

Bottom line

Mistral AI’s €105m seed was a statement of intent—and the company has largely delivered on its early promise. With strong model releases, an open-weight ethos, and major distribution through Azure, Mistral has become a credible choice for organizations that want high performance with more deployment flexibility. Expect continued competition on quality, efficiency, and governance as the European AI ecosystem matures.

FAQs

Who founded Mistral AI?

Arthur Mensch (ex-Google DeepMind), Guillaume Lample (ex-Meta FAIR), and Timothée Lacroix (ex-Meta FAIR) founded Mistral in 2023.

What makes Mistral different from OpenAI?

Mistral leans into open-weight releases, letting teams download and run some models privately. It also offers hosted APIs and Azure access, blending openness with enterprise convenience.

What is Mixtral?

Mixtral is Mistral’s family of mixture-of-experts models (e.g., 8x7B and 8x22B) that achieve strong results with lower compute per token by activating only a subset of parameters.

How can I try Mistral models?

You can use Mistral via its API, try the Le Chat interface for a chatbot experience, or access select models through Microsoft Azure.

Is Mistral really “open source”?

Mistral often releases open weights under permissive licenses, which is different from fully open-source code for training pipelines. Some flagship models (like Mistral Large) are available via API/partners only.

Sources

1. Sifted: Meta and DeepMind alumni raise €105m seed round to build OpenAI rival Mistral
2. TechCrunch: Mistral AI raises $113M at seed
3. Reuters: Mistral AI raises €385m (Series A)
4. Reuters: Mistral AI raises €600m (Series B)
5. Microsoft: Partnership bringing Mistral models to Azure
6. Reuters: Microsoft makes new AI push with Mistral
7. Mistral: Introducing Mistral Large
8. Mistral: Announcing Mistral 7B
9. Mistral: Mixtral 8x22B
10. The Verge: Mistral releases Mixtral 8x7B
11. European Parliament: AI Act adoption
12. Euractiv: Debate on open-source regulation in EU AI Act
13. Reuters: Aleph Alpha raises funds for German AI