--- base_model: mistralai/Mistral-Small-3.1-24B-Instruct-2503 language: - en - fr - de - es - pt - it - ja - ko - ru - zh - ar - fa - id - ms - ne - pl - ro - sr - sv - tr - uk - vi - hi - bn library_name: vllm license: apache-2.0 pipeline_tag: image-text-to-text tags: - llama-cpp - gguf-my-repo inference: false extra_gated_description: If you want to learn more about how we process your personal data, please read our Privacy Policy. --- # Triangle104/Mistral-Small-3.1-24B-Instruct-2503-Q6_K-GGUF This model was converted to GGUF format from [`mistralai/Mistral-Small-3.1-24B-Instruct-2503`](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503) for more details on the model. --- Building upon Mistral Small 3 (2501), Mistral Small 3.1 (2503) adds state-of-the-art vision understanding and enhances long context capabilities up to 128k tokens without compromising text performance. With 24 billion parameters, this model achieves top-tier capabilities in both text and vision tasks. This model is an instruction-finetuned version of: Mistral-Small-3.1-24B-Base-2503. Mistral Small 3.1 can be deployed locally and is exceptionally "knowledge-dense," fitting within a single RTX 4090 or a 32GB RAM MacBook once quantized. It is ideal for: -Fast-response conversational agents. -Low-latency function calling. -Subject matter experts via fine-tuning. -Local inference for hobbyists and organizations handling sensitive data. -Programming and math reasoning. -Long document understanding. -Visual understanding. For enterprises requiring specialized capabilities (increased context, specific modalities, domain-specific knowledge, etc.), we will release commercial models beyond what Mistral AI contributes to the community. Key Features - -Vision: Vision capabilities enable the model to analyze images and provide insights based on visual content in addition to text. -Multilingual: Supports dozens of languages,including English, French, German, Greek, Hindi, Indonesian, Italian, Japanese, Korean, Malay, Nepali, Polish, Portuguese, Romanian, Russian, Serbian, Spanish, Swedish, Turkish, Ukrainian, Vietnamese, Arabic, Bengali, Chinese, Farsi. -Agent-Centric: Offers best-in-class agentic capabilities with native function calling and JSON outputting. -Advanced Reasoning: State-of-the-art conversational and reasoning capabilities. -Apache 2.0 License: Open license allowing usage and modification for both commercial and non-commercial purposes. -Context Window: A 128k context window. -System Prompt: Maintains strong adherence and support for system prompts. -Tokenizer: Utilizes a Tekken tokenizer with a 131k vocabulary size. --- ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo Triangle104/Mistral-Small-3.1-24B-Instruct-2503-Q6_K-GGUF --hf-file mistral-small-3.1-24b-instruct-2503-q6_k.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Triangle104/Mistral-Small-3.1-24B-Instruct-2503-Q6_K-GGUF --hf-file mistral-small-3.1-24b-instruct-2503-q6_k.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo Triangle104/Mistral-Small-3.1-24B-Instruct-2503-Q6_K-GGUF --hf-file mistral-small-3.1-24b-instruct-2503-q6_k.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Triangle104/Mistral-Small-3.1-24B-Instruct-2503-Q6_K-GGUF --hf-file mistral-small-3.1-24b-instruct-2503-q6_k.gguf -c 2048 ```