Mistral Large
Analysis Summary
Mistral Large is a text and file-capable model with a 128,000-token context window, tool use, and function calling. Its benchmark results indicate useful general knowledge and instruction capability, with enough coding performance for basic implementation, transformation, and debugging tasks.
The combination of file input and tool support suits document-heavy automation, structured extraction, internal assistants, and code generation under review. It can serve client workflows that need predictable API interaction without frontier-level reasoning. The supplied intelligence and coding measures remain modest, and there is no agentic benchmark data, so complex autonomous execution should be avoided.
Pricing is higher than many lightweight alternatives while capability is no longer leading. Use it where file processing and existing integration patterns matter, but compare newer models before committing it to broad production traffic.
Assessed September 7, 2026
Editorial notes
Mistral Large offers a 128K context, file handling, and function calling for document and automation workflows, but its older benchmark profile and mid-range pricing limit its role in demanding work.
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DFO Verdict
Mistral Large offers a 128K context, file handling, and function calling for document and automation workflows, but its older benchmark profile and mid-range pricing limit its role in demanding work.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
1 Intelligence Index
How Mistral Large compares
Mistral Large ranks #355 of 435 AI models we track for overall intelligence. Its 128K-token context window is larger than 35% of the models we list. At $2.00 per million input tokens it is cheaper than 18% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $2.00 | $0.002000 |
| Output | $6.00 | $0.006000 |
What would Mistral Large cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 756 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Mistral Large for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Mistral Large
This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more...
Frequently asked questions about Mistral Large
How much does Mistral Large cost?
Mistral Large costs $2.00 per million input tokens and $6.00 per million output tokens.
What is the context window of Mistral Large?
Mistral Large has a context window of 128,000 tokens (128K).
What can Mistral Large do?
Mistral Large supports tool use and function calling.
Who created Mistral Large?
Mistral Large is developed by Mistral AI and was released on February 26, 2024.