Top-Tier Reasoning

Mistral Medium 3

Mistral Medium 3 is a frontier-class language model that delivers state-of-the-art performance at up to 8 times lower cost than leading alternatives, making it ideal for enterprise applications like coding, reasoning, and multimodal understanding. With a 128,000 token context window and support for multilingual and multimodal inputs, it provides professional-grade capabilities with exceptional cost-efficiency and easy deployment.

128k Context

Top-Tier Intelligence

Mar '25 Knowledge

Available for Chat, Vision, and File Uploads.

Performance Benchmarks

HumanEval

85.4%

MMLU

57.8%

GPQA

40.0%

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Why use Mistral Medium 3?

State-of-the-art Coding Performance

Leads in coding and STEM tasks, matching large models like GPT-4o at 8X lower cost

Multimodal Understanding

Processes text and images for visual QA, document parsing, and charts with high-quality text outputs

Long Context Reasoning

Handles 128K context window for large documents, multi-step agents, and extended dialogues

Capability Examples

Multimodal Document Analysis

Analyze this scanned invoice image: extract the total amount, date, and vendor name.

The invoice from Acme Corp, dated 2025-03-15, shows a total amount of $1,247.50. Key line items include consulting services $800, materials $400, tax $47.50.

Long Context Code Summarization

Here's a 50k token Python codebase for a trading algorithm. Summarize its architecture, key functions, and potential bugs with the 128k context.

This trading algo uses a modular design: data_fetcher.py pulls market data via API, analyzer.py applies ML models for signals (LSTM predictor may overfit without validation), executor.py handles orders via broker integration. Bugs: race conditions in async trades, missing error handling in API retries. Recommend adding locks and try-except blocks.

How to use

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