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Mistral AI

API for Mistral's models — chat, coding, OCR and speech — from a European provider that also publishes open-weight models.

Visit mistral.ai ↗Pricing & calculatorAlternatives
Works with AI agents:llms.txtBuilt into Replit
Ask your AI about this, with this page as the source:ChatGPT ↗Claude ↗Perplexity ↗

Mistral AI is a French model maker. Its API, managed from the Mistral Studio console, serves Mistral's own models for chat, coding, vision, OCR, embeddings and audio, plus a few third-party open-weight models, so one European vendor can cover text generation, document OCR and transcription.

You create an Organization with Workspaces, issue API keys per Workspace, and call REST endpoints such as /v1/chat/completions, /v1/ocr, /v1/embeddings and /v1/audio/transcriptions. Official SDKs exist for Python (mistralai) and TypeScript, and the chat endpoint follows OpenAI's request structure, so OpenAI-compatible clients work after changing the base URL and model name. Stateful APIs sit on top: agents with tools, conversations, document libraries for RAG and batch jobs.

Useful for a small team: data is hosted in the EU by default, with optional EU or US regional endpoints when you must state where inference runs; monthly spending caps per Organization and per Workspace; zero data retention on request for stateless endpoints on paid plans; and many models released under Apache 2.0, so you can move to running them yourself later.

The main limits: in Studio's free mode your inputs and outputs may be used for training unless you opt out, zero data retention does not cover stateful features such as agents, files, libraries or batch, and regional endpoints serve only the models hosted in that region and support function calling as the only tool type.

Where it fits

LLM API · Model providerA European provider whose API covers chat, coding, OCR and speech models.Trade-off: A smaller ecosystem of third-party integrations than the largest providers.

How Mistral AI itself is built

1 tools, from its own code, website and Product Hunt page.

Netlify

Who uses it

15 makers' products, each linked to the source that shows it, and 69 open-source projects that declare it in their code.

The maker says so 10Subprocessor list 7Declared in code 69How evidence is collected →
OmnifactPrivacy First AI Chat Assistants for Businesses

“A special thanks to Mistral AI for their exceptional generative AI solutions. As an EU-based team, their commitment to GDPR compliance aligns seamlessly with our mission to provide privacy-first models. Their focus on data sovereignty and security helps us deliver robust AI capabilities while ensuring adherence to strict regulatory standards. Together, we're advancing AI with a strong emphasis on privacy and innovation.”

LLM APIMaker says so +1 · source ↗
RankfenderThe platform for modern visibility management ( SEO & GEO )

“We chose Mistral AI over Claude for a few specific reasons: Speed first. Mistral Small 3.1 delivers 150 tokens/second inference speed . For Rankfender, where we're constantly scanning AI answers in real-time, that low latency matters. Claude Haiku 4.5 is fast too, but Mistral's architecture felt more optimized for our use case. Open-weight flexibility. Mistral releases under Apache 2.0 . We can self-host if needed, fine-tune for specialized domains, and avoid vendor lock-in. Claude is proprietary—great model, but you're tied to Anthropic's infrastructure. Cost efficiency. At $0.50/$1.50 per million tokens , Mistral competes well on price. For a startup processing thousands of queries daily, those margins add up. European alignment. As a company building for global agencies, having a strong EU-based AI provider felt strategically smart—especially with evolving regulations. Claude's Sonnet 4.5 is arguably more powerful for complex reasoning , but for our specific needs—speed, flexibility, cost—Mistral was the better fit.”

LLM APIMaker says so · source ↗
Officely AIAny Process to AI with All LLM Models

“We use Mistral as an endpoint in our team builder flow; you can combine this model with all available models.”

LLM APIMaker says so · source ↗
TalespinnerAI assisted story writing with complete control

“Talespinner uses Mistral Large as a writing model. It is great for writing novels with more mature topics, since it doesn't censor your writing that much.”

LLM APIMaker says so · source ↗
OpenSaucedOptimize Your Open Source Project with Deep Insights

“Mistral-7b is the best open source foundational model to date. We leverage it to provide cost-effective summaries for embeddings.”

LLM APIMaker says so · source ↗

Open source: a project that declares Mistral AI as a dependency in its public code — verifiable, but not necessarily a live product.

What makers say

7 makers on why they use Mistral AI, in their own words on Product Hunt.

We chose Mistral AI over Claude for a few specific reasons: Speed first. Mistral Small 3.1 delivers 150 tokens/second inference speed . For Rankfender, where we're constantly scanning AI answers in real-time, that low latency matters. Claude Haiku 4.5 is fast too, but Mistral's architecture felt more optimized for our use case. Open-weight flexibility. Mistral releases under Apache 2.0 . We can self-host if needed, fine-tune for specialized domains, and avoid vendor lock-in. Claude is proprietary—great model, but you're tied to Anthropic's infrastructure. Cost efficiency. At $0.50/$1.50 per million tokens , Mistral competes well on price. For a startup processing thousands of queries daily, those margins add up. European alignment. As a company building for global agencies, having a strong EU-based AI provider felt strategically smart—especially with evolving regulations. Claude's Sonnet 4.5 is arguably more powerful for complex reasoning , but for our specific needs—speed, flexibility, cost—Mistral was the better fit.
RankfenderSep 2026 ↗
A special thanks to Mistral AI for their exceptional generative AI solutions. As an EU-based team, their commitment to GDPR compliance aligns seamlessly with our mission to provide privacy-first models. Their focus on data sovereignty and security helps us deliver robust AI capabilities while ensuring adherence to strict regulatory standards. Together, we're advancing AI with a strong emphasis on privacy and innovation.
OmnifactSep 2026 ↗
Talespinner uses Mistral Large as a writing model. It is great for writing novels with more mature topics, since it doesn't censor your writing that much.
TalespinnerSep 2026 ↗
We use Mistral as an endpoint in our team builder flow; you can combine this model with all available models.
Officely AISep 2026 ↗
Mistral helped us create a few different AI agents using their console is pretty smooth
PodpodSep 2026 ↗

Loved and watch-outs

Themes that recur in makers' words and Hacker News comments, each linked to what it summarises, with how Product Hunt tags its reviews.

Most loved
  • As an EU company focused on GDPR and data sovereignty, it suits privacy-first products. PHHN
  • Its models are cost-effective for tasks like summaries and agents. PHPH 2
  • Open-weight models and fast small models give deployment flexibility. PHPH 2
  • The Voxtral voice model is a strong speech option with broad language support. HNHN 2
Watch-outs
  • Its general LLMs are seen as trailing the leading models. HNHN 2
On Product Hunt 5.0★ · 41 reviews
open source models 6open technology commitment 5performance and scalability 5support for AI community 4cost-effective solutions 3optimized commercial models 3flexible deployment options 2memory efficiency 2
Read the reviews on Product Hunt ↗

Who switches

Public pull requests on GitHub since Oct 2024 whose title says "X to Y" — real code changes moving a project from one tool to another, by developers in general. Open a row to see the pull requests.

OpenAI API → Mistral AI9 PRs
OpenAI API vs Mistral AI compared →All matching pull requests on GitHub ↗
Gemini API → Mistral AI6 PRs
Gemini API vs Mistral AI compared →All matching pull requests on GitHub ↗
Groq → Mistral AI3 PRs
All matching pull requests on GitHub ↗
Mistral AI → Gemini API6 PRs
Mistral AI vs Gemini API compared →All matching pull requests on GitHub ↗
Mistral AI → Groq5 PRs
All matching pull requests on GitHub ↗
Mistral AI → OpenAI API4 PRs
Mistral AI vs OpenAI API compared →All matching pull requests on GitHub ↗

Alternatives to Mistral AI

All alternatives by situation →
ClaudeCoding, long documents and agent-style tool use.251 makers · LLM APICompare with Mistral AI →
OpenAI APIThe broadest model lineup — text, images, speech, embeddings — and the largest ecosystem.734 makers · LLM APICompare with Mistral AI →
Gemini APIVery long context and multimodal input, with a free tier to start.Free tier99 makers · LLM APICompare with Mistral AI →
DeepSeekLow per-token prices on strong reasoning and coding models, with OpenAI- and Anthropic-format endpoints.11 makers · LLM APICompare with Mistral AI →
GroqVery low-latency inference on open models, for real-time features.Free tier39 makers · LLM API

On Product Hunt, people weigh it against: OpenAI API, DeepSeek, Gemini API, MiniMax, Claude, Eden AI.

Questions makers ask about Mistral AI

Does Mistral train on my API inputs and outputs?

In Studio's free mode it may, but you can opt out at any time. Pay-as-you-go customers also control this processing and can opt out whenever they want. source ↗

Where is my data stored?

In the European Union by default, or in the United States if you explicitly call the US endpoint. Some features can temporarily send data to subprocessors outside the EU, covered by the EU Standard Contractual Clauses. source ↗

Can I keep inference inside the EU or the US?

Yes, by sending requests to api.eu.mistral.ai or api.us.mistral.ai, which cost more than the global endpoint. The global endpoint makes no location promise, and account data such as keys, billing and usage analytics is not made regional. source ↗

Is zero data retention available?

On paid plans, on request, for stateless endpoints such as chat completions, embeddings, OCR, moderation and transcription. Agents, conversations, libraries, batch files and the Files API are excluded because they have to store data to work. source ↗

Can I keep using the OpenAI SDK?

Yes. Point an OpenAI-compatible client at https://api.mistral.ai/v1 and change the model name; the official Mistral SDKs use slightly different method names. source ↗

Is Mistral SOC 2 or ISO 27001 certified?

Mistral states it complies with SOC 2 Type II and ISO 27001/27701, and compliance reports can be requested through its Trust Center. source ↗

Can I run Mistral's open models commercially myself?

Most are Apache 2.0, which allows any use, modification and redistribution. Some use a modified MIT license that requires companies above $20M in monthly revenue to buy a commercial license or use the models through Mistral Studio; each model card states its license. source ↗

Is Mistral AI free?

Yes — there is a free tier a small product can run on; paid use starts at Pay per token. source ↗

Is Mistral AI open source or self-hostable?

Not open source, and hosted only.

Can AI coding agents work with Mistral AI?

It serves an llms.txt docs index; Replit set it up natively.

Who uses Mistral AI?

15 makers' products we track, each with a source, and 69 open-source projects declare it in their code. source ↗