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mradermacher/minimax-m2-thrift-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/VibeStudio/MiniMax-M2-THRIFT For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-GGUF

transformersggufmoeminimaxbfloat16sglangendataset:nick007x/github-code-2025dataset:tatsu-lab/alpacabase_model:VibeStudio/MiniMax-M2-THRIFTbase_model:quantized:VibeStudio/MiniMax-M2-THRIFTlicense:mitendpoints_compatibleregion:usimatrixconversational
mradermacher/minimax-m2-thrift-i1-gguf visual
Downloads
169
Likes
10
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

4 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
MiniMax-M2-THRIFT.i1-IQ1_M.gguf GGUF IQ1_M 36.37 GB Download
MiniMax-M2-THRIFT.i1-IQ1_S.gguf GGUF IQ1_S 32.80 GB Download
MiniMax-M2-THRIFT.i1-IQ2_XXS.gguf GGUF IQ2_XXS 42.32 GB Download
MiniMax-M2-THRIFT.imatrix.gguf GGUF 353.32 MB Download

Model Details Live

Model Slug
mradermacher/minimax-m2-thrift-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2025-11-06
Last Modified
2025-12-10
Gated
No
Private
No
HF SHA
06efa0d7276e9e6376091e1fb8d92f2d5ff83978
License
mit
Language
en
Base Model
VibeStudio/MiniMax-M2-THRIFT

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "VibeStudio/MiniMax-M2-THRIFT",
    "datasets": [
      "nick007x/github-code-2025",
      "tatsu-lab/alpaca"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "mit",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "moe",
      "minimax",
      "bfloat16",
      "sglang",
      "gguf"
    ],
    "frontmatter": {
      "base_model": "VibeStudio/MiniMax-M2-THRIFT",
      "datasets": [
        "nick007x/github-code-2025",
        "tatsu-lab/alpaca"
      ],
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "mit",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "moe",
        "minimax",
        "bfloat16",
        "sglang",
        "gguf"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/VibeStudio/MiniMax-M2-THRIFT  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: VibeStudio/MiniMax-M2-THRIFT\ndatasets:\n- nick007x/github-code-2025\n- tatsu-lab/alpaca\nlanguage:\n- en\nlibrary_name: transformers\nlicense: mit\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- moe\n- minimax\n- bfloat16\n- sglang\n- gguf\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/VibeStudio/MiniMax-M2-THRIFT\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#MiniMax-M2-THRIFT-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-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/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.imatrix.gguf) | imatrix | 0.5 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ1_S.gguf) | i1-IQ1_S | 35.3 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ1_M.gguf) | i1-IQ1_M | 39.1 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 45.5 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ2_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ2_XS.gguf.part2of2) | i1-IQ2_XS | 50.7 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ2_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ2_S.gguf.part2of2) | i1-IQ2_S | 51.6 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ2_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ2_M.gguf.part2of2) | i1-IQ2_M | 56.7 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q2_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q2_K_S.gguf.part2of2) | i1-Q2_K_S | 58.7 | very low quality |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q2_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q2_K.gguf.part2of2) | i1-Q2_K | 63.0 | IQ3_XXS probably better |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ3_XXS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ3_XXS.gguf.part2of2) | i1-IQ3_XXS | 66.5 | lower quality |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ3_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ3_XS.gguf.part2of2) | i1-IQ3_XS | 70.6 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q3_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q3_K_S.gguf.part2of2) | i1-Q3_K_S | 74.6 | IQ3_XS probably better |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ3_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ3_S.gguf.part2of2) | i1-IQ3_S | 74.6 | beats Q3_K* |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ3_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ3_M.gguf.part2of2) | i1-IQ3_M | 75.6 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q3_K_M.gguf.part2of2) | i1-Q3_K_M | 82.6 | IQ3_S probably better |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q3_K_L.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q3_K_L.gguf.part2of2) | i1-Q3_K_L | 89.4 | IQ3_M probably better |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ4_XS.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-IQ4_XS.gguf.part2of2) | i1-IQ4_XS | 92.1 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_0.gguf.part2of2) | i1-Q4_0 | 97.8 | fast, low quality |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_K_S.gguf.part2of2) | i1-Q4_K_S | 98.2 | optimal size/speed/quality |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_K_M.gguf.part3of3) | i1-Q4_K_M | 104.5 | fast, recommended |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_1.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_1.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q4_1.gguf.part3of3) | i1-Q4_1 | 108.2 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q5_K_S.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q5_K_S.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q5_K_S.gguf.part3of3) | i1-Q5_K_S | 118.9 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q5_K_M.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q5_K_M.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q5_K_M.gguf.part3of3) | i1-Q5_K_M | 122.5 |  |\n| [PART 1](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q6_K.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q6_K.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/MiniMax-M2-THRIFT-i1-GGUF/resolve/main/MiniMax-M2-THRIFT.i1-Q6_K.gguf.part3of3) | i1-Q6_K | 141.7 | 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",
    "moe",
    "minimax",
    "bfloat16",
    "sglang",
    "en",
    "dataset:nick007x/github-code-2025",
    "dataset:tatsu-lab/alpaca",
    "base_model:VibeStudio/MiniMax-M2-THRIFT",
    "base_model:quantized:VibeStudio/MiniMax-M2-THRIFT",
    "license:mit",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 10,
  "downloads": 169,
  "gated": false,
  "private": false,
  "last_modified": "2025-12-10T12:30:50.000Z",
  "created_at": "2025-11-06T05:55:02.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
  "_id": "690c383619dd483b22024b3a",
  "id": "mradermacher/MiniMax-M2-THRIFT-i1-GGUF",
  "modelId": "mradermacher/MiniMax-M2-THRIFT-i1-GGUF",
  "sha": "06efa0d7276e9e6376091e1fb8d92f2d5ff83978",
  "createdAt": "2025-11-06T05:55:02.000Z",
  "lastModified": "2025-12-10T12:30:50.000Z",
  "author": "mradermacher",
  "downloads": 169,
  "likes": 10,
  "gated": false,
  "private": false,
  "pipeline_tag": "",
  "library_name": "transformers",
  "siblings_count": 51
}