Triangle104
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README.md
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This model was converted to GGUF format from [`mistralai/Mistral-Small-24B-Instruct-2501`](https://huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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This model was converted to GGUF format from [`mistralai/Mistral-Small-24B-Instruct-2501`](https://huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501) for more details on the model.
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Model details:
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Mistral Small 3 ( 2501 ) sets a new benchmark in the "small" Large Language Models category below 70B, boasting 24B parameters and achieving state-of-the-art capabilities comparable to larger models!
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This model is an instruction-fine-tuned version of the base model: Mistral-Small-24B-Base-2501.
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Mistral Small can be deployed locally and is exceptionally "knowledge-dense", fitting in a single RTX 4090 or a 32GB RAM MacBook once quantized.
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Perfect for:
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Fast response conversational agents.
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Low latency function calling.
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Subject matter experts via fine-tuning.
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Local inference for hobbyists and organizations handling sensitive data.
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For enterprises that need specialized capabilities (increased context, particular modalities, domain specific knowledge, etc.), we will be releasing commercial models beyond what Mistral AI contributes to the community.
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This release demonstrates our commitment to open source, serving as a strong base model.
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Learn more about Mistral Small in our blog post.
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Model developper: Mistral AI Team
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Key Features
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Multilingual: Supports dozens of languages, including English, French, German, Spanish, Italian, Chinese, Japanese, Korean, Portuguese, Dutch, and Polish.
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Agent-Centric: Offers best-in-class agentic capabilities with native function calling and JSON outputting.
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Advanced Reasoning: State-of-the-art conversational and reasoning capabilities.
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Apache 2.0 License: Open license allowing usage and modification for both commercial and non-commercial purposes.
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Context Window: A 32k context window.
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System Prompt: Maintains strong adherence and support for system prompts.
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Tokenizer: Utilizes a Tekken tokenizer with a 131k vocabulary size.
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---
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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