Mistral AI vs OpenAI API
Two model provider options for LLM API. When each fits, what it costs, who moves from one to the other, and what makers who chose it say.
Mistral AIModel providerllms.txtIn Replit
OpenAI APIModel providerllms.txtIn Lovable, ReplitWhich fits you
- Token cost dominates your budget, for example high-volume batch or agent workloads
Use it whenYou want an EU-based provider, or document OCR alongside text models.
Trade-offA smaller ecosystem of third-party integrations than the largest providers.
- You want the strongest general models and the widest ecosystem of examples and integrations
Use it whenYou want one account that covers text, images, speech and embeddings, with the most examples to copy from.
Trade-offFrequent model and API changes to keep up with, and no option to run its hosted models elsewhere.
At a glance
| Used by | 15 makers' products · 69 open-source projects | 734 makers' products · 481 open-source projects |
|---|---|---|
| Cost at default usageinput tokens 50 million tokens, output tokens 10 million tokens | $6.00/mo Ministral 3 (3B) | $10/mo GPT-6 Luna |
| Moved to it on GitHubpull requests since Oct 2024 | 9 from OpenAI API | 4 from Mistral AI |
| Downloads | 7.1M/wk6× vs npm | 34.1M/wk+61% vs npm |
| Pricing | Pay per token; the free plan includes $10/mo in API credits to test models in Mistral Studio. · paid from Pay per token | Pay per token. · paid from Pay per token |
| Free tier | Yes | No |
| Open source | No | No |
| Incidents, 90 daysfrom its status page | no public status feed | 25+ (4 major) |
Cost as you grow
At 1M tokens Mistral AI costs less ($0.12 vs $0.20); and still does at 5B tokens ($600 vs $1,000).
The numbers, plan by plan
| Input tokens per month | Mistral AI | OpenAI API |
|---|---|---|
| 1 | $0.12 Ministral 3 (3B) | $0.20 GPT-6 Luna |
| 5 | $0.60 Ministral 3 (3B) | $1.00 GPT-6 Luna |
| 10 | $1.20 Ministral 3 (3B) | $2.00 GPT-6 Luna |
| 50 | $6.00 Ministral 3 (3B) | $10 GPT-6 Luna |
| 100 | $12 Ministral 3 (3B) | $20 GPT-6 Luna |
| 500 | $60 Ministral 3 (3B) | $100 GPT-6 Luna |
| 1,000 | $120 Ministral 3 (3B) | $200 GPT-6 Luna |
| 5,000 | $600 Ministral 3 (3B) | $1,000 GPT-6 Luna |
From each vendor's pricing page: Mistral AI, OpenAI API.
Who moves from one to the other
Public pull requests on GitHub since Oct 2024 whose title says "Mistral AI to OpenAI API" or the reverse — real code changes, by developers in general rather than makers only.
- Migrate runtime from OpenAI to Mistral and add Mistral transports, analyzers and harnessesarnaudconnan-svg/acp-chat · 2026-08-29
- docs: switch LLM provider from Anthropic/OpenAI to MistralBimsara-Yehan/ChemSentry · 2026-08-18
- Migration from openAI to MistralZering-Max/tepsia-chatbot · 2026-08-10
- fix(ai): switch rag-eval from OpenAI to Mistral (credits exhausted)andrelair-platform/minicloud-gitops · 2026-08-02
- Migrate from OpenAI to Mistral, add reliability, idempotency, telemetry, and runbooksAbdulmuiz44/SayReady · 2026-03-21
- fix: switch CI LLM from OpenAI to Mistral MAASrossoctl/rossoctl · 2026-03-03
- fix: add mergeToolResultText for OpenAI provider to fix Mistral tool message orderingRooCodeInc/Roo-Code · 2026-01-13
- change openai to mistral ai as llm apiOscar-Hirsch/newsPortal · 2025-06-19
- Change openAI to Mistral in text about VCsalkem-io/client-web · 2025-03-12
- test: fix Mistral test due to new OpenAI SDK releasedeepset-ai/haystack-core-integrations · 2026-09-01
- Port AI integration from Mistral to OpenAI API; rename Mistral→Chat throughoutLavey/mastra48 · 2026-03-18
- feat: migrate from Mistral to OpenAI gpt-5-nanoLyleW473/NLPGroupCoursework · 2025-12-07
- test: adapt Mistral to OpenAI refactoringdeepset-ai/haystack-core-integrations · 2025-01-02
What makers say
Makers on using it for LLM API, from Product Hunt and Starter Story interviews, each linked to the source. Products with a page of their own and fuller notes first.
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.
We use Mistral as an endpoint in our team builder flow; you can combine this model with all available models.
Mistral helped us create a few different AI agents using their console is pretty smooth
We use GPT-5.6 to power the Basedash AI data analyst. It's incredibly intelligent and, with the right harness, allows us to rank #1 on BI Bench for solving real-world BI scenarios.
Credit where it’s due: OpenAI’s dev tools made it incredibly easy to prototype and test multiple ideas fast. Still unmatched when you need raw speed, documentation, and flexibility.
Quven writes subtitles from the audio of a film on the machine of the user. The Whisper models, run locally through whisper.cpp, can do it and the audio never leaves that machine.
Loved and watch-outs
Themes that recur in makers' words and Hacker News comments, each linked to what it summarises.
- Its models are strong at code generation, reasoning and creative tasks, often chosen after testing alternatives. PHPH 2PH 3PH 4
- The API is reliable and well-priced as the foundation for production features. PHPH 2PH 3HN
- Good docs and a smooth developer experience make integration straightforward. PHPH 2PH 3PH 4