Mistral Large · Mistral AI
Mistral Large is the flagship model of Mistral AI (Paris). Excellent in multiple languages. Good balance of quality and cost.
About Mistral Large
Mistral Large is the flagship model of Mistral AI (Paris). Excellent in multiple languages. Good balance of quality and cost.
Where it shines: European multilingual · Mistral flagship · GDPR-friendly.
How to use Mistral Large
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Type or upload
Type what you want in the box above — or upload the file if the tool asks for one.
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Generate
Click the main button. Wait 2-30 seconds depending on the model and input size.
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Download or share
Download the result or share the direct link. No watermark, ready to use.
Frequently asked questions
How much does it cost to use Mistral Large?
Mistral Large is a Pro model: it costs 20 tokens per use (~$0.10 real cost for us). You need a Pro plan ($9/month → 15,000 tokens) or a one-shot pack.If you already have tokens in the free account, you can also spend them directly.
How many uses of Mistral Large come in the Pro plan?
Pro ($9/month) gives you 15,000 recurring tokens. At 20 tokens per Mistral Large use, that’s ~750 full uses per cycle. If you run out, the one-shot packs (5,000 / 25,000 / 80,000 tokens) add to the balance without expiring before one year.
What makes Mistral Large special?
Mistral AI (Paris) builds efficient models with a focus on European multilingualism and GDPR compliance, with specific strengths: European multilingual, mistral flagship and gdpr-friendly.
How fast does Mistral Large respond?
Mistral Large has a balanced speed: 5-15 seconds per response — neither the fastest nor the slowest in the catalog.The actual time also depends on the length of the prompt and the load of the datacenter — models with huge context take longer when you enter very long texts.
How do I use Mistral Large in ia.gratis?
You can use Mistral Large from /chat/ by selecting Mistral Large in the picker, or via the REST API with `model=mistral-large` in the body of the POST. Quick summary: European flagship. Excellent multilingual. The internal model identifier is `mistral-large` — useful when integrating via API.