Mistral Medium 3.5 is a Large Language Models (LLMs) tool. Mistral Medium 3.5 is a dense 128B parameter large language model with a 256K context window that combines instruction-following, reasoning, and coding in one unified model. It features multimodal vision input, configurable reasoning effort, and scores 77.6% on SWE-Bench Verified. Best for software developers and engineers, data scientists and analysts and scientists and researchers.
About Mistral Medium 3.5
Key Features
Frequently Asked Questions
Mistral Medium 3.5 is a 128 billion parameter large language model released by Mistral AI in April 2026. It's a dense transformer model with a 256K context window that combines instruction-following, reasoning, and coding in one unified architecture. The model is released as open weights under a modified MIT license and can be self-hosted or accessed via API.
Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens through the Mistral API. This is half the input cost of Claude Sonnet 4.6 and 40% cheaper than GPT-4o. For self-hosting, the open weights are free to download under a modified MIT license, though high-revenue enterprises may need a commercial agreement.
Yes, Mistral Medium 3.5 includes multimodal vision capabilities. It has a vision encoder trained from scratch that accepts both text and image inputs with text output. The encoder handles variable image sizes and aspect ratios, making it suitable for document parsing, diagram understanding, screenshot analysis, and visual question answering tasks.
Mistral Medium 3.5 scores 77.6% on SWE-Bench Verified, which is close to Claude Sonnet 4.6 at 79.6% but ahead of smaller models like Qwen 3.6 at 72.4%. It's designed as a unified model that handles coding, reasoning, and general tasks together, with configurable reasoning effort. The model also powers Mistral Vibe CLI for autonomous coding agents that can open pull requests.
