mradermacher/codestral-22b-v0.1-gguf overview

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  "card_data": {
    "base_model": "mistralai/Codestral-22B-v0.1",
    "language": [
      "code"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://mistral.ai/licences/MNPL-0.1.md",
    "license_name": "mnpl",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "code",
      "mistral-common"
    ],
    "frontmatter": {
      "base_model": "mistralai/Codestral-22B-v0.1",
      "language": [
        "code"
      ],
      "library_name": "transformers",
      "license": "other",
      "license_link": "https://mistral.ai/licences/MNPL-0.1.md",
      "license_name": "mnpl",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "code",
        "mistral-common"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      static quants of https://huggingface.co/mistralai/Codestral-22B-v0.1  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Codestral-22B-v0.1-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: mistralai/Codestral-22B-v0.1\nlanguage:\n- code\nlibrary_name: transformers\nlicense: other\nlicense_link: https://mistral.ai/licences/MNPL-0.1.md\nlicense_name: mnpl\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- code\n- mistral-common\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags:  -->\nstatic quants of https://huggingface.co/mistralai/Codestral-22B-v0.1\n\n<!-- provided-files -->\n\n***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Codestral-22B-v0.1-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Codestral-22B-v0.1-i1-GGUF\n## Usage\n\nIf you are unsure how to use GGUF files, refer to one of [TheBloke's\nREADMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for\nmore details, including on how to concatenate multi-part files.\n\n## Provided Quants\n\n(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)\n\n| Link | Type | Size/GB | Notes |\n|:-----|:-----|--------:|:------|\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q2_K.gguf) | Q2_K | 8.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.IQ3_XS.gguf) | IQ3_XS | 9.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q3_K_S.gguf) | Q3_K_S | 9.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.IQ3_S.gguf) | IQ3_S | 9.8 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.IQ3_M.gguf) | IQ3_M | 10.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q3_K_M.gguf) | Q3_K_M | 10.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q3_K_L.gguf) | Q3_K_L | 11.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.IQ4_XS.gguf) | IQ4_XS | 12.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q4_K_S.gguf) | Q4_K_S | 12.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q4_K_M.gguf) | Q4_K_M | 13.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q5_K_S.gguf) | Q5_K_S | 15.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q5_K_M.gguf) | Q5_K_M | 15.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q6_K.gguf) | Q6_K | 18.4 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Codestral-22B-v0.1-GGUF/resolve/main/Codestral-22B-v0.1.Q8_0.gguf) | Q8_0 | 23.7 | fast, best quality |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)\n\nAnd here are Artefact2's thoughts on the matter:\nhttps://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9\n\n## FAQ / Model Request\n\nSee https://huggingface.co/mradermacher/model_requests for some answers to\nquestions you might have and/or if you want some other model quantized.\n\n## Thanks\n\nI thank my company, [nethype GmbH](https://www.nethype.de/), for letting\nme use its servers and providing upgrades to my workstation to enable\nthis work in my free time.\n\n<!-- end -->\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "code",
    "mistral-common",
    "base_model:mistralai/Codestral-22B-v0.1",
    "base_model:quantized:mistralai/Codestral-22B-v0.1",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 86,
  "gated": false,
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  "last_modified": "2025-07-26T01:38:00.000Z",
  "created_at": "2024-09-11T14:52:30.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
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