Mistral Medium 3.5

A 128B model for coding, reasoning, and long tasks

Mistral Medium 3.5 介绍

Mistral Medium 3.5 is a 128B dense language model that unifies instruction-following, reasoning, and coding in a single set of weights. It features a 256k context window and configurable reasoning effort, making it suitable for complex, long-running tasks. The model achieves 77.6% on SWE-Bench Verified and is available as open weights on Hugging Face, empowering engineers to run self-hosted inference.

核心功能

128B dense model with state-of-the-art coding and reasoning performance
256k token context window for handling long documents and conversations
Configurable reasoning effort per request for flexible responses
Open weight release under modified MIT license for self-hosting
Scores 77.6% on SWE-Bench Verified and 91.4 on τ³-Telecom

典型使用场景

Software engineers using Vibe CLI for asynchronous, cloud-based coding agents
Developers needing a powerful LLM for complex multi-step reasoning tasks
Teams running self-hosted inference for data-sensitive applications
Users of Le Chat's Work mode for research, inbox triage, and cross-tool workflows

为什么适合初创团队

Mistral Medium 3.5 offers startup-friendly open weights, enabling self-hosting to avoid per-token costs and maintain data privacy. Its strong performance on coding and reasoning tasks accelerates development cycles, while the 256k context supports long-form agentic workflows. Startups can leverage the same model for both quick queries and complex, multi-step tasks without switching between different models.

可替代选择

GPT-4, Claude 3.5, Gemini 2.0, Qwen 3.5, Llama 3.1

常见问题

What is the context length of Mistral Medium 3.5?

It supports a 256k token context window.

Is the model available as open source?

Yes, it is released with open weights on Hugging Face under a modified MIT license.

How does the pricing work for the API?

The API costs $1.5 per million input tokens and $7.5 per million output tokens.

Can I run Mistral Medium 3.5 on my own hardware?

Yes, it can be self-hosted on as few as four GPUs, with deployment guides available.

Mistral Medium 3.5