Mistral Large (24.02)
Mistral AI · Active · available in 9 of 31 regions
- Context window
- 32K
- 32,000 tokens
- Max output
- —
- Input / 1M
- $4.00
- us-east-1
- Output / 1M
- $12.00
What Mistral Large (24.02) is good for
editorialMistral Large (24.02) offers a 32K-token context window with tool use, at the premium end of this provider’s range at $4.00 per 1M input tokens. Callable in 9 of 31 regions.
Suits
- Tool use. Can call functions, so it can drive retrieval, look things up, and take actions rather than only answering.
Think twice if
- Long context. Only 32K tokens — long documents will need chunking, and agentic histories will hit the ceiling.
- Agentic loops. No prompt caching published, so every step re-pays full price for the prompt prefix. Expensive for agents that resend a long context.
- Documents with layout. Text only. Scanned PDFs, screenshots and charts need a vision model or an OCR step first.
- High volume. At $4.00 per 1M input tokens it sits at the expensive end of the Mistral AI range. Worth it for hard tasks, wasteful for bulk extraction.
This section is judgement, not data from AWS. It is composed from the capabilities, context window, price position and region coverage shown elsewhere on this page — so it stays in step with the daily snapshot rather than going stale.
Where teams typically use it
Coding
Writing, reviewing and refactoring code, usually across more than one file.
- · A review pass that flags real defects with a severity and leaves style alone.
- · A framework upgrade applied across a repository, one module at a time, tests green between each.
- · Turning a failing bug report into a reproducing test and then a fix.
Chat and assistants
Conversational work where responsiveness matters as much as depth.
- · A customer-facing assistant where the first token needs to appear in under a second.
- · An in-product copilot that explains what the user is looking at and answers follow-ups.
- · A triage bot that qualifies an incoming request before routing it to the right team.
Model & inference profile IDs
Base model ID — direct on-demand invoke
Pricing by region
USD per 1M tokens| Region | Input | Output | Cache read | Cache write | Batch in | Batch out | Source |
|---|---|---|---|---|---|---|---|
| us-east-1 US East (N. Virginia) | $4.00 | $12.00 | — | — | — | — | API |
| us-west-2 US West (Oregon) | $4.00 | $12.00 | — | — | — | — | API |
| ca-central-1 Canada (Central) | $4.60 | $13.80 | — | — | — | — | API |
| eu-west-1 EU (Ireland) | $4.30 | $13.00 | — | — | — | — | API |
| eu-west-2 EU (London) | $5.20 | $15.60 | — | — | — | — | API |
| eu-west-3 EU (Paris) | $5.20 | $15.60 | — | — | — | — | API |
| ap-south-1 Asia Pacific (Mumbai) | $4.80 | $14.40 | — | — | — | — | API |
| ap-southeast-2 Asia Pacific (Sydney) | $5.20 | $15.60 | — | — | — | — | API |
| sa-east-1 South America (Sao Paulo) | $6.70 | $20.20 | — | — | — | — | API |
Region availability
TPM / RPM are default account quotas from AWS Service Quotas where a model-specific limit is published. They are per-account defaults and adjustable on request.
Where this model actually runs
Under a strict residency constraint, Mistral Large (24.02) can be served without the request leaving 9 of the 25 jurisdictions with a Bedrock region.
Mistral Large (24.02) appears in
Common questions
- How much does Mistral Large (24.02) cost on Amazon Bedrock?
- $4.00 per 1M input tokens and $12.00 per 1M output tokens in us-east-1.
- Which AWS regions support Mistral Large (24.02)?
- 9 of 31 regions: us-east-1, us-west-2, ca-central-1, eu-west-1, eu-west-2, eu-west-3, ap-south-1, ap-southeast-2, sa-east-1.
- What is the context window of Mistral Large (24.02)?
- 32,000 tokens (32K).
- What is the model ID for Mistral Large (24.02) on Bedrock?
- mistral.mistral-large-2402-v1:0.