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mradermacher/mimo-v2-flash-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/MiMo-V2-Flash-GGUF

transformersggufenbase_model:XiaomiMiMo/MiMo-V2-Flashbase_model:quantized:XiaomiMiMo/MiMo-V2-Flashlicense:mitendpoints_compatibleregion:usimatrixconversational
mradermacher/mimo-v2-flash-i1-gguf visual
Downloads
2,192
Likes
2
Pipeline
—
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

21 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
MiMo-V2-Flash.i1-IQ1_M.gguf GGUF IQ1_M 64.64 GB Download
MiMo-V2-Flash.i1-IQ1_S.gguf GGUF IQ1_S 58.20 GB Download
MiMo-V2-Flash.i1-IQ2_M.gguf GGUF IQ2_M 93.87 GB Download
MiMo-V2-Flash.i1-IQ2_S.gguf GGUF IQ2_S 85.29 GB Download
MiMo-V2-Flash.i1-IQ2_XS.gguf GGUF IQ2_XS 84.00 GB Download
MiMo-V2-Flash.i1-IQ2_XXS.gguf GGUF IQ2_XXS 75.37 GB Download
MiMo-V2-Flash.i1-IQ3_M.gguf GGUF IQ3_M 125.52 GB Download
MiMo-V2-Flash.i1-IQ3_S.gguf GGUF IQ3_S 123.99 GB Download
MiMo-V2-Flash.i1-IQ3_XS.gguf GGUF IQ3_XS 117.12 GB Download
MiMo-V2-Flash.i1-IQ3_XXS.gguf GGUF IQ3_XXS 110.41 GB Download
MiMo-V2-Flash.i1-IQ4_XS.gguf GGUF IQ4_XS 153.13 GB Download
MiMo-V2-Flash.i1-Q2_K.gguf GGUF Q2_K 104.57 GB Download
MiMo-V2-Flash.i1-Q2_K_S.gguf GGUF Q2_K_S 97.22 GB Download
MiMo-V2-Flash.i1-Q3_K_L.gguf GGUF Q3_K_L 148.65 GB Download
MiMo-V2-Flash.i1-Q3_K_M.gguf GGUF Q3_K_M 137.19 GB Download
MiMo-V2-Flash.i1-Q3_K_S.gguf GGUF Q3_K_S 123.96 GB Download
MiMo-V2-Flash.i1-Q4_0.gguf GGUF — 162.70 GB Download
MiMo-V2-Flash.i1-Q4_1.gguf GGUF — 180.01 GB Download
MiMo-V2-Flash.i1-Q4_K_M.gguf GGUF Q4_K_M 173.97 GB Download
MiMo-V2-Flash.i1-Q4_K_S.gguf GGUF Q4_K_S 163.33 GB Download
MiMo-V2-Flash.imatrix.gguf GGUF — 474.77 MB Download

Model Details Live

Model Slug
mradermacher/mimo-v2-flash-i1-gguf
Author
mradermacher
Pipeline Task
—
Library
transformers
Created
2026-01-02
Last Modified
2026-01-05
Gated
No
Private
No
HF SHA
989a2debcf00345d1b5b2eadcc17e48236c398e6
License
mit
Language
en
Base Model
XiaomiMiMo/MiMo-V2-Flash

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "XiaomiMiMo/MiMo-V2-Flash",
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "mit",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "XiaomiMiMo/MiMo-V2-Flash",
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "mit",
      "mradermacher": [],
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/MiMo-V2-Flash-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: XiaomiMiMo/MiMo-V2-Flash\nlanguage:\n- en\nlibrary_name: transformers\nlicense: mit\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags: nicoboss -->\n<!-- ### quants:  Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nweighted/imatrix quants of https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash\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#MiMo-V2-Flash-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/MiMo-V2-Flash-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/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.imatrix.gguf) | imatrix | 0.6 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ1_S.gguf) | i1-IQ1_S | 62.6 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ1_M.gguf) | i1-IQ1_M | 69.5 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 81.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ2_XS.gguf) | i1-IQ2_XS | 90.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ2_S.gguf) | i1-IQ2_S | 91.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ2_M.gguf) | i1-IQ2_M | 100.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q2_K_S.gguf) | i1-Q2_K_S | 104.5 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q2_K.gguf) | i1-Q2_K | 112.4 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 118.7 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ3_XS.gguf) | i1-IQ3_XS | 125.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q3_K_S.gguf) | i1-Q3_K_S | 133.2 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ3_S.gguf) | i1-IQ3_S | 133.2 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ3_M.gguf) | i1-IQ3_M | 134.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q3_K_M.gguf) | i1-Q3_K_M | 147.4 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q3_K_L.gguf) | i1-Q3_K_L | 159.7 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-IQ4_XS.gguf) | i1-IQ4_XS | 164.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q4_0.gguf) | i1-Q4_0 | 174.8 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q4_K_S.gguf) | i1-Q4_K_S | 175.5 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q4_K_M.gguf) | i1-Q4_K_M | 186.9 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q4_1.gguf) | i1-Q4_1 | 193.4 |  |\n| [P1](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_S.gguf.part1of5) [P2](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_S.gguf.part2of5) [P3](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_S.gguf.part3of5) [P4](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_S.gguf.part4of5) [P5](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_S.gguf.part5of5) | i1-Q5_K_S | 212.6 |  |\n| [P1](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_M.gguf.part1of5) [P2](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_M.gguf.part2of5) [P3](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_M.gguf.part3of5) [P4](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_M.gguf.part4of5) [P5](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q5_K_M.gguf.part5of5) | i1-Q5_K_M | 219.2 |  |\n| [P1](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q6_K.gguf.part1of6) [P2](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q6_K.gguf.part2of6) [P3](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q6_K.gguf.part3of6) [P4](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q6_K.gguf.part4of6) [P5](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q6_K.gguf.part5of6) [P6](https://huggingface.co/mradermacher/MiMo-V2-Flash-i1-GGUF/resolve/main/MiMo-V2-Flash.i1-Q6_K.gguf.part6of6) | i1-Q6_K | 253.6 | 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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.\n\n<!-- end -->\n",
    "related_quantizations": []
  },
  "tags": [
    "transformers",
    "gguf",
    "en",
    "base_model:XiaomiMiMo/MiMo-V2-Flash",
    "base_model:quantized:XiaomiMiMo/MiMo-V2-Flash",
    "license:mit",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 2,
  "downloads": 2192,
  "gated": false,
  "private": false,
  "last_modified": "2026-01-05T21:32:33.000Z",
  "created_at": "2026-01-02T11:15:03.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
  "_id": "6957a8b7137782117c481a95",
  "id": "mradermacher/MiMo-V2-Flash-i1-GGUF",
  "modelId": "mradermacher/MiMo-V2-Flash-i1-GGUF",
  "sha": "989a2debcf00345d1b5b2eadcc17e48236c398e6",
  "createdAt": "2026-01-02T11:15:03.000Z",
  "lastModified": "2026-01-05T21:32:33.000Z",
  "author": "mradermacher",
  "downloads": 2192,
  "likes": 2,
  "gated": false,
  "private": false,
  "pipeline_tag": "",
  "library_name": "transformers",
  "siblings_count": 39
}