fuland539/Mistral-Small-3.1-24B-Instruct-2503

VISIONPricing:Input $0.867 / Output $1.61Concurrent Unit Cost:2Model Size:24BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Mar 28, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

Mistral-Small-3.1-24B-Instruct-2503 is a 24 billion parameter instruction-tuned language model developed by Mistral AI, building upon Mistral Small 3. It features state-of-the-art vision understanding and an extended 128k token context window, while maintaining strong text performance. This model is highly knowledge-dense, capable of local deployment on consumer hardware like an RTX 4090, and excels in conversational agents, function calling, programming, math reasoning, and long document and visual understanding.

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Overview of Mistral-Small-3.1-24B-Instruct-2503

Mistral-Small-3.1-24B-Instruct-2503 is an instruction-finetuned model from Mistral AI, featuring 24 billion parameters. It significantly enhances its predecessor, Mistral Small 3, by integrating state-of-the-art vision understanding and extending its long context capabilities up to 128k tokens without compromising text performance. This model is designed for efficient local deployment, fitting within a single RTX 4090 or a 32GB RAM MacBook when quantized, making it accessible for hobbyists and organizations with sensitive data.

Key Capabilities

  • Vision Understanding: Analyzes images and provides insights based on visual content alongside text.
  • Extended Context Window: Supports a 128k token context, ideal for long document understanding.
  • Multilingual Support: Proficient in dozens of languages, including major European, Asian, and Middle Eastern languages.
  • Agent-Centric Design: Features best-in-class agentic capabilities with native function calling and JSON outputting.
  • Advanced Reasoning: Offers strong conversational, programming, and mathematical reasoning abilities.
  • System Prompt Adherence: Maintains robust adherence to system prompts for tailored interactions.

Good For

  • Fast-response conversational agents and chatbots.
  • Low-latency function calling and tool use.
  • Local inference for privacy-sensitive applications or hobbyist projects.
  • Programming and math reasoning tasks.
  • Long document analysis and summarization.
  • Visual understanding applications requiring image analysis.
  • Fine-tuning for subject matter expert applications.

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