Mistral Medium 3.5 - Mistral AI

2026-04-29 · Source: mistral.ai via Google News · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Advanced, quick

Summary

Mistral Medium 3.5 is a new frontier-class multimodal model released in April 2026, optimized for agentic and coding use cases. It is available with open weights under a Modified MIT license. The model features a 256k context window and is priced at $1.5/M tokens for input and $7.5/M tokens for output. Key functionalities include chat completions, function calling, agents & conversations, built-in tools, and structured outputs. It also supports advanced features like predicted outputs, OCR with annotations and BBox extraction, document QnA, Fill-in-the-Middle (FIM), embeddings, and moderation. Furthermore, it offers audio capabilities such as transcriptions with timestamps and text-to-speech, alongside batch processing.

Key takeaway

For AI Architects evaluating new foundation models, Mistral Medium 3.5 offers a compelling option due to its open-weight licensing and optimization for agentic and coding tasks. Its 256k context window and multimodal capabilities, including OCR and audio processing, suggest broad applicability. Consider integrating this model for applications requiring advanced conversational AI, code generation, or complex document and audio data interaction, while factoring in the $1.5/$7.5 per million token pricing.

Key insights

Mistral Medium 3.5 is a multimodal, open-weight model optimized for agents and coding with extensive features.

Principles

• Open weights foster broader adoption
• Multimodality expands application scope

Method

The model integrates diverse APIs for chat, agents, document processing, audio, and embeddings to support complex AI workflows.

In practice

• Develop AI agents with built-in tools
• Integrate OCR for document analysis
• Utilize FIM for code completion

Topics

• Mistral Medium 3.5
• Multimodal AI
• Agentic AI
• Coding Applications
• Open Weights Model

Best for: CTO, VP of Engineering/Data, AI Architect, AI Engineer, Machine Learning Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by mistral.ai via Google News.