Pixtral Large is an AI model by Mistral. View detailed benchmark scores, pricing data, and performance metrics on Serenities AI Models.
Specifications last checked against the provider on . Benchmark scores carry their own source, linked beside each number.
General Benchmarks
Massive Multitask Language Understanding professional benchmark
HuggingFace LeaderboardHuman preference ELO from blind head-to-head votes
LMSYS / HuggingFaceCoding Benchmarks
Math Benchmarks
Reasoning Benchmarks
Speed Benchmarks
Cost Benchmarks
Context Benchmarks
Available from 5 providers
The same model costs different amounts depending on who serves it. You can bring your own key for 2 of these — connect it here.
| Provider | Input / 1M | Output / 1M | Cached in | Context | Your key |
|---|---|---|---|---|---|
| Cortecs | $1.993 | $5.978 | — | 128K | — |
| Amazon Bedrock | $2 | $6 | — | 128K | Supported |
| Eden AI | $2 | $6 | — | 128K | — |
| Merge Gateway | $2 | $6 | — | 128K | — |
| Mistral | $2 | $6 | — | 128K | Supported |
Pixtral Large — Benchmark Scores Overview
Scores normalized to percentage scale for visual comparison. ELO scores mapped to 0-100 range (1100-1500).
Compare Pixtral Large With
Pixtral Large — Frequently Asked Questions
How intelligent is Pixtral Large?
Pixtral Large scores 1270 on the Chatbot Arena ELO rating, making it a mid-tier AI model. This score is based on blind head-to-head human preference voting.
How much does Pixtral Large cost?
Pixtral Large costs $2.0 per 1M input tokens and $6.0 per 1M output tokens. This is mid-range pricing for its capability level.
How fast is Pixtral Large?
Pixtral Large generates output at 60 tokens per second, which is slower, prioritizing quality over speed compared to other models. The time to first token is 400 ms.
How good is Pixtral Large at coding?
Pixtral Large achieves 35.0% on SWE-bench Verified, demonstrating moderate real-world software engineering capability. This benchmark tests the model's ability to resolve actual GitHub issues.
How good is Pixtral Large at math and reasoning?
Pixtral Large scores 74.0% on the MATH benchmark (competition-level mathematics). It also achieves 48.0% on GPQA Diamond, a graduate-level science reasoning benchmark.
What is the context window of Pixtral Large?
Pixtral Large has a context window of 131K tokens. This determines how much text, conversation history, and code the model can process in a single request.
Who created Pixtral Large?
Pixtral Large was created by Mistral. It is classified as a flagship model in our catalogue.
Is Pixtral Large open source?
No, Pixtral Large is a proprietary model. It is available through Mistral's API and compatible providers.