Open-weight models

Mistral Large 3, the Mistral AI model in numbers

Mistral Large 3 in numbers: price per token, context window, independent benchmark scores and comparable models, based on public data checked on October 22, 2026.

Data as of October 22, 2026

Key figures

DeveloperMistral AI
ReleasedDecember 2, 2025
Knowledge cutoffDecember 2024
Context window128,000 tokens (≈ 192 pages)
Maximum output262,144 tokens
Input price$0.50 per million tokens (median of 17 providers)
Output price$1.5 per million tokens
Open weightsYes
Reasoning modeNo
Tool callingYes
Structured output (JSON)Not disclosed
Accepted inputstext, image
Providers offering it17

What you need to know

Mistral Large 3 is a language model from Mistral AI, released on December 2, 2025. That makes it 10 months old as of October 22, 2026. Its weights are published: you can download it and run it on your own servers, or use one of the 17 API providers that list it on models.dev. It has no declared reasoning mode: it answers directly, without an extra billed thinking step.

We file it under open-weight models (68 models in this category on the site).

Measured performance

Epoch AI publishes 2 results for Mistral Large 3 on our basket's benchmarks: too few to compute a reliable capability index.

  • GPQA Diamond (PhD-level science questions): 38.8% — the best tracked model, Gemini 4 Argon, reaches 96.4%
  • OTIS Mock AIME (competition mathematics problems): 1.9% — the best tracked model, GPT-5.5 Pro, reaches 100%

Pricing and budget

Mistral Large 3 costs $0.50 per million input tokens and $1.5 per million output tokens (median of 17 providers, checked on October 22, 2026).

To put it in perspective: reading 20,000 tokens (about thirty pages) and writing 2,000 costs roughly $0.013; a thousand of those tasks, $13.

That is 1.5 times the median output price of open-weight models ($1).

To estimate your own budget, use the agent cost calculator.

Technical specifications

Its context window reaches 128,000 tokens, roughly 192 pages of text at 500 words per page: enough for a medium-length document. A single answer can run to 262,144 tokens.

It accepts as input: text and image. Its knowledge stops at December 2024: beyond that, it needs web search or your documents.

It can call tools (functions, APIs), which makes it a possible foundation for an AI agent.

Who is it for?

Given its category, Mistral Large 3 is mainly aimed at projects where you want control over your data or hosting, or want to adapt the model to your field.

Before adopting it, test it on your own examples: benchmarks measure standard tasks, not your job.

What could replace it?

In the same category, the models closest to Mistral Large 3 are:

Independent benchmark scores

BenchmarkWhat it measuresScore
GPQA DiamondPhD-level science questions38.8%
OTIS Mock AIMEcompetition mathematics problems1.9%

Similar models

Other Mistral AI models

Frequently asked questions

How much does Mistral Large 3 cost?

As of October 22, 2026, Mistral Large 3 costs $0.50 per million input tokens and $1.5 per million output tokens (median of 17 providers). A task that reads 20,000 tokens and writes 2,000 costs about $0.013.

What is the context window of Mistral Large 3?

128,000 tokens, roughly 192 pages of text. An answer can reach 262,144 tokens.

Is Mistral Large 3 open source?

Its weights are published: you can install it on your own servers. Check the license before commercial use.

When was Mistral Large 3 released?

Mistral Large 3 was released on December 2, 2025, according to models.dev.

Can you build an agent with Mistral Large 3?

Yes: it can call tools, the two basic building blocks of an agent.

Data sources

Data as of October 22, 2026

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