Model Overview
unsloth/Mistral-Small-24B-Instruct-2501 is a 24 billion parameter instruction-fine-tuned model from Mistral AI, designed to offer state-of-the-art capabilities in the "small" LLM category. It is built upon the Mistral-Small-24B-Base-2501 and features a substantial 32k context window. This model is notable for its efficiency, capable of local deployment on a single RTX 4090 or a 32GB RAM MacBook, especially when quantized.
Key Features & Capabilities
- Multilingual Support: Proficient in dozens of languages, including English, French, German, Spanish, Italian, Chinese, Japanese, and Korean.
- Agent-Centric Design: Offers robust agentic capabilities with native function calling and JSON outputting, making it suitable for complex automated workflows.
- Advanced Reasoning: Demonstrates strong conversational and reasoning abilities, comparable to larger models.
- System Prompt Adherence: Maintains strong adherence to and support for system prompts, enhancing control over model behavior.
- Apache 2.0 License: Provides an open license for both commercial and non-commercial use and modification.
Performance Highlights
Mistral-Small-24B-Instruct-2501 shows competitive performance across various benchmarks:
- Reasoning & Knowledge: Achieves 0.663 on
mmlu_pro_5shot_cot_instruct and 0.453 on gpqa_main_cot_5shot_instruct. - Math & Coding: Scores 0.848 on
humaneval_instruct_pass@1 and 0.706 on math_instruct. - Instruction Following: Records 8.35 on
mtbench_dev and 52.27 on wildbench.
Good for
- Fast Response Conversational Agents: Its efficiency and conversational capabilities make it ideal for chatbots requiring quick interactions.
- Low Latency Function Calling: Excellent for applications needing rapid execution of tool-use and function calls.
- Subject Matter Experts: Can be fine-tuned for specialized domain knowledge.
- Local Inference: Suitable for hobbyists and organizations handling sensitive data that require on-premise model deployment.