Mistral AI · language model
Mistral Large 4: pricing, context and benchmarks
Mistral Large 4 is a language model from Mistral AI released on October 6, 2026. It costs $1.36 per million input tokens and $4.18 per million output tokens, with a 1M-token context window. Epoch AI ranks it #60 of 125 rated models.
What you need to know about Mistral Large 4
Mistral Large 4 was released by Mistral AI (France) on October 6, 2026. It accepts text and images as input and produces text. Its context window reaches 1,048,576 tokens, larger than 93 % of the models in the registry, and it can write up to 262,144 tokens in one go.
It is a recent model: real-world feedback and independent scores are still scarce.
Mistral Large 4 pricing
On OpenRouter, Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens. Counting three tokens read for every token written, its average price is $2.065 per million, more expensive than 73 % of paid models (2.7 times the median of $0.76).
A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.0048. At 1,000 tasks a day, budget $144 a month. The price calculator redoes this with your own volumes.
Tokens already sent and cached are billed at $0.14 per million.
Performance and benchmarks
The Epoch Capabilities Index (ECI), which aggregates published results across many benchmarks, gives Mistral Large 4 a score of 150 (range 146.9 to 152.7). That places it #60 of 125 rated models.
Scores published by Epoch AI on the benchmarks the site tracks:
| Benchmark | What it measures | Score | Date |
|---|---|---|---|
| GPQA Diamond | PhD-level science questions | 88.1 % | Oct 6, 2026 |
| FrontierMath | research-level maths problems (tiers 1-3) | 58.6 % | Oct 6, 2026 |
| OTIS Mock AIME | maths competition problems | 98.3 % | Oct 6, 2026 |
| SimpleQA Verified | accuracy on simple facts | 20 % | Oct 6, 2026 |
For at least equal performance, Claude Haiku 5.5, GPT-6 Luna, and GPT-5.6 Luna cost at least 30% less.
Features, privacy and local use
- It supports tool calling, so it can drive an AI agent, call APIs or MCP servers.
- It can answer in an enforced JSON format (structured outputs).
- It is a reasoning model: it "thinks" before answering, which helps on hard tasks but uses more output tokens.
Its weights are not published: it can only be used through the Mistral AI API or a broker such as OpenRouter, which means sending your data off your machines.
Other Mistral AI models
| Model | Released | Avg. price | ECI |
|---|---|---|---|
| Mistral Medium 3.5 | Apr 30, 2026 | $3 | 141.4 |
| Mistral Small 4 | Mar 16, 2026 | $0.26 | — |
| Devstral 2 2512 | Dec 9, 2025 | $0.8 | — |
| Ministral 3 14B 2512 | Dec 2, 2025 | $0.2 | — |
| Ministral 3 8B 2512 | Dec 2, 2025 | $0.15 | — |
| Ministral 3 3B 2512 | Dec 2, 2025 | $0.1 | — |
| Mistral Large 3 2512 | Dec 1, 2025 | $0.75 | — |
| Voxtral Small 24B 2507 | Oct 30, 2025 | $0.15 | — |
Verdict
Mistral Large 4 scores 54/100 on our grid, which only uses published figures.
Strengths
- Very large context (1M tokens): long documents or a whole codebase fit in one request.
- Agent-ready: tool calling and structured JSON output.
Avoid if…
- you process large volumes on a tight budget;
- your data must not leave your servers;
- your tasks are mostly simple: a non-reasoning model will cost less.
Alternatives
- GLM 5.2$1.78
- Muse Spark 1.1$2
- Gemini 3 Flash Preview$1.13
- Grok 4.20$1.56
- Qwen3.7 Max$2.21
- GPT-5$3.44
Comparisons and tools
Learn more
Frequently asked questions
How much does Mistral Large 4 cost?
$1.36 per million input tokens and $4.18 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.0048.
How big is Mistral Large 4's context window?
1,048,576 tokens, roughly 786,000 words, with a maximum of 262,144 output tokens.
Can Mistral Large 4 run locally?
No, Mistral AI does not publish its weights: it is API-only.
Is Mistral Large 4 suitable for an AI agent?
Technically yes: it supports tool calling and structured outputs. Then check its cost for your volume.
How good is Mistral Large 4?
Epoch AI ranks it #60 of 125 rated models (ECI 150). On GPQA Diamond, it scores 88.1%.
What are the alternatives to Mistral Large 4?
The closest models on price and performance are GLM 5.2, Muse Spark 1.1, and Gemini 3 Flash Preview.
Related articles
- Mistral AI: models, pricing and agentsOctober 25, 2026
- LLM benchmarks: how to read model rankingsOctober 24, 2026
- Running a local LLM: hardware, software, and limitationsOctober 24, 2026
- Open-source or closed models for your AI agents?October 5, 2026
Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score