mistralai/ministral-3-8b-reasoning-2512-gguf overview

{
  "metadata": {},
  "card_data": {
    "library_name": "vllm",
    "language": [
      "en",
      "fr",
      "es",
      "de",
      "it",
      "pt",
      "nl",
      "zh",
      "ja",
      "ko",
      "ar"
    ],
    "license": "apache-2.0",
    "inference": false,
    "base_model": [
      "mistralai/Ministral-3-8B-Reasoning-2512"
    ],
    "extra_gated_description": "If you want to learn more about how we process your personal data, please read our <a href=\"https://mistral.ai/terms/\">Privacy Policy</a>.",
    "tags": [
      "mistral-common"
    ],
    "frontmatter": {
      "library_name": "vllm",
      "language": [
        "en",
        "fr",
        "es",
        "de",
        "it",
        "pt",
        "nl",
        "zh",
        "ja",
        "ko",
        "ar"
      ],
      "license": "apache-2.0",
      "inference": "false",
      "base_model": [
        "mistralai/Ministral-3-8B-Reasoning-2512"
      ],
      "extra_gated_description": ">-",
      "tags": [
        "mistral-common"
      ]
    },
    "hero_image_url": "",
    "summary": "A balanced model in the Ministral 3 family, **Ministral 3 8B** is a powerful, efficient tiny language model with vision capabilities. This model includes different quantization levels of the reasoning post-trained version in **GGUF**, trained for reasoning tasks, making it ideal for math, coding and stem related use cases. The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 8B can even be deployed locally, capable of fitting in 24GB of VRAM in BF16, and less than 12GB of RAM/VRAM when quantized. Learn more in our blog post and paper.",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nlibrary_name: vllm\nlanguage:\n- en\n- fr\n- es\n- de\n- it\n- pt\n- nl\n- zh\n- ja\n- ko\n- ar\nlicense: apache-2.0\ninference: false\nbase_model:\n- mistralai/Ministral-3-8B-Reasoning-2512\nextra_gated_description: >-\n  If you want to learn more about how we process your personal data, please read\n  our <a href=\"https://mistral.ai/terms/\">Privacy Policy</a>.\ntags:\n- mistral-common\n---\n\n# Ministral 3 8B Reasoning 2512 GGUF\n\nA balanced model in the Ministral 3 family, **Ministral 3 8B** is a powerful, efficient tiny language model with vision capabilities.\n\nThis model includes different quantization levels of the reasoning post-trained version in **GGUF**, trained for reasoning tasks, making it ideal for math, coding and stem related use cases.\n\nThe Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 8B can even be deployed locally, capable of fitting in 24GB of VRAM in BF16, and less than 12GB of RAM/VRAM when quantized.\n\nLearn more in our [blog post](https://mistral.ai/news/mistral-3) and [paper](https://arxiv.org/abs/2601.08584).\n\n## Key Features\nMinistral 3 8B consists of two main architectural components:\n- **8.4B Language Model**\n- **0.4B Vision Encoder**\n\nThe Ministral 3 8B Reasoning model offers the following capabilities:\n- **Vision**: Enables the model to analyze images and provide insights based on visual content, in addition to text.\n- **Multilingual**: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic.\n- **System Prompt**: Maintains strong adherence and support for system prompts.\n- **Agentic**: Offers best-in-class agentic capabilities with native function calling and JSON outputting.\n- **Reasoning**: Excels at complex, multi-step reasoning and dynamic problem-solving.\n- **Edge-Optimized**: Delivers best-in-class performance at a small scale, deployable anywhere.\n- **Apache 2.0 License**: Open-source license allowing usage and modification for both commercial and non-commercial purposes.\n- **Large Context Window**: Supports a 256k context window.\n\n### Recommended Settings\n\nWe recommend deploying with the following best practices:\n- System Prompt: Use our provided [system prompt](https://huggingface.co/mistralai/Ministral-3-8B-Reasoning-2512/blob/main/SYSTEM_PROMPT.txt), and append it to your custom system prompt to define a clear environment and use case, including guidance on how to effectively leverage tools in agentic systems.\n- Multi-turn Traces: We highly recommend keeping the reasoning traces in context.\n- Sampling Parameters: Use a **temperature of 0.7** for most environments ; Different temperatures may be explored for different use cases - developers are encouraged to experiment with alternative settings.\n- Tools: Keep the set of tools well-defined and limit their number to the minimum required for the use case - Avoiding overloading the model with an excessive number of tools.\n- Vision: When deploying with vision capabilities, we recommend maintaining an aspect ratio close to 1:1 (width-to-height) for images. Avoiding the use of overly thin or wide images - crop them as needed to ensure optimal performance.\n\n## License\n\nThis model is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0.txt).\n\n*You must not use this model in a manner that infringes, misappropriates, or otherwise violates any third party’s rights, including intellectual property rights.*",
    "related_quantizations": []
  },
  "tags": [
    "vllm",
    "gguf",
    "mistral-common",
    "en",
    "fr",
    "es",
    "de",
    "it",
    "pt",
    "nl",
    "zh",
    "ja",
    "ko",
    "ar",
    "arxiv:2601.08584",
    "base_model:mistralai/Ministral-3-8B-Reasoning-2512",
    "base_model:quantized:mistralai/Ministral-3-8B-Reasoning-2512",
    "license:apache-2.0",
    "region:us",
    "conversational"
  ],
  "likes": 23,
  "downloads": 51195,
  "gated": false,
  "private": false,
  "last_modified": "2026-01-15T11:19:00.000Z",
  "created_at": "2025-10-31T08:46:38.000Z",
  "pipeline_tag": "",
  "library_name": "vllm"
}

{
  "_id": "6904776e9b0aced61cf84fda",
  "id": "mistralai/Ministral-3-8B-Reasoning-2512-GGUF",
  "modelId": "mistralai/Ministral-3-8B-Reasoning-2512-GGUF",
  "sha": "4413bc9b7b091ddad28101650d1395f5e045a328",
  "createdAt": "2025-10-31T08:46:38.000Z",
  "lastModified": "2026-01-15T11:19:00.000Z",
  "author": "mistralai",
  "downloads": 51195,
  "likes": 23,
  "gated": false,
  "private": false,
  "pipeline_tag": "",
  "library_name": "vllm",
  "siblings_count": 7
}