mradermacher/mixtral-8x7b-v0.1-i1-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "mistralai/Mixtral-8x7B-v0.1",
    "language": [
      "fr",
      "it",
      "de",
      "es",
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "moe",
      "mistral-common"
    ],
    "frontmatter": {
      "base_model": "mistralai/Mixtral-8x7B-v0.1",
      "language": [
        "fr",
        "it",
        "de",
        "es",
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "moe",
        "mistral-common"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About weighted/imatrix quants of https://huggingface.co/mistralai/Mixtral-8x7B-v0.1  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: mistralai/Mixtral-8x7B-v0.1\nlanguage:\n- fr\n- it\n- de\n- es\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- moe\n- mistral-common\n---\n## About\n\nweighted/imatrix quants of https://huggingface.co/mistralai/Mixtral-8x7B-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#Mixtral-8x7B-v0.1-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-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/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ1_S.gguf) | i1-IQ1_S | 9.8 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ1_M.gguf) | i1-IQ1_M | 11.1 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 12.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ2_XS.gguf) | i1-IQ2_XS | 13.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ2_S.gguf) | i1-IQ2_S | 14.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ2_M.gguf) | i1-IQ2_M | 15.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q2_K.gguf) | i1-Q2_K | 17.6 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 18.6 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q3_K_XS.gguf) | i1-Q3_K_XS | 19.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ3_XS.gguf) | i1-IQ3_XS | 19.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ3_S.gguf) | i1-IQ3_S | 20.7 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q3_K_S.gguf) | i1-Q3_K_S | 20.7 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ3_M.gguf) | i1-IQ3_M | 21.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q3_K_M.gguf) | i1-Q3_K_M | 22.8 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q3_K_L.gguf) | i1-Q3_K_L | 24.4 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ4_XS.gguf) | i1-IQ4_XS | 25.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-IQ4_NL.gguf) | i1-IQ4_NL | 26.8 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q4_0.gguf) | i1-Q4_0 | 26.8 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 27.0 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q4_K_M.gguf) | i1-Q4_K_M | 28.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q5_K_S.gguf) | i1-Q5_K_S | 32.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q5_K_M.gguf) | i1-Q5_K_M | 33.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Mixtral-8x7B-v0.1-i1-GGUF/resolve/main/Mixtral-8x7B-v0.1.i1-Q6_K.gguf) | i1-Q6_K | 38.6 | practically like static Q6_K |\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",
    "moe",
    "mistral-common",
    "fr",
    "it",
    "de",
    "es",
    "en",
    "base_model:mistralai/Mixtral-8x7B-v0.1",
    "base_model:quantized:mistralai/Mixtral-8x7B-v0.1",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us"
  ],
  "likes": 1,
  "downloads": 407,
  "gated": false,
  "private": false,
  "last_modified": "2025-07-26T04:32:40.000Z",
  "created_at": "2024-02-25T14:54:26.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}

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