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mradermacher/lfm2-24b-a2b-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/LiquidAI/LFM2-24B-A2B For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/LFM2-24B-A2B-GGUF

transformersggufliquidlfm2edgeenarzhfrdejakoesptbase_model:LiquidAI/LFM2-24B-A2Bbase_model:quantized:LiquidAI/LFM2-24B-A2Blicense:otherendpoints_compatibleregion:usimatrixconversational
mradermacher/lfm2-24b-a2b-i1-gguf visual
Downloads
873
Likes
6
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

24 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
LFM2-24B-A2B.i1-IQ1_M.gguf GGUF IQ1_M 5.01 GB Download
LFM2-24B-A2B.i1-IQ1_S.gguf GGUF IQ1_S 4.51 GB Download
LFM2-24B-A2B.i1-IQ2_M.gguf GGUF IQ2_M 7.25 GB Download
LFM2-24B-A2B.i1-IQ2_S.gguf GGUF IQ2_S 6.58 GB Download
LFM2-24B-A2B.i1-IQ2_XS.gguf GGUF IQ2_XS 6.52 GB Download
LFM2-24B-A2B.i1-IQ2_XXS.gguf GGUF IQ2_XXS 5.85 GB Download
LFM2-24B-A2B.i1-IQ3_M.gguf GGUF IQ3_M 9.70 GB Download
LFM2-24B-A2B.i1-IQ3_S.gguf GGUF IQ3_S 9.61 GB Download
LFM2-24B-A2B.i1-IQ3_XS.gguf GGUF IQ3_XS 9.08 GB Download
LFM2-24B-A2B.i1-IQ3_XXS.gguf GGUF IQ3_XXS 8.56 GB Download
LFM2-24B-A2B.i1-IQ4_XS.gguf GGUF IQ4_XS 11.85 GB Download
LFM2-24B-A2B.i1-Q2_K.gguf GGUF Q2_K 8.10 GB Download
LFM2-24B-A2B.i1-Q2_K_S.gguf GGUF Q2_K_S 7.51 GB Download
LFM2-24B-A2B.i1-Q3_K_L.gguf GGUF Q3_K_L 11.47 GB Download
LFM2-24B-A2B.i1-Q3_K_M.gguf GGUF Q3_K_M 10.58 GB Download
LFM2-24B-A2B.i1-Q3_K_S.gguf GGUF Q3_K_S 9.61 GB Download
LFM2-24B-A2B.i1-Q4_0.gguf GGUF 12.58 GB Download
LFM2-24B-A2B.i1-Q4_1.gguf GGUF 13.92 GB Download
LFM2-24B-A2B.i1-Q4_K_M.gguf GGUF Q4_K_M 13.43 GB Download
LFM2-24B-A2B.i1-Q4_K_S.gguf GGUF Q4_K_S 12.62 GB Download
LFM2-24B-A2B.i1-Q5_K_M.gguf GGUF Q5_K_M 15.76 GB Download
LFM2-24B-A2B.i1-Q5_K_S.gguf GGUF Q5_K_S 15.30 GB Download
LFM2-24B-A2B.i1-Q6_K.gguf GGUF Q6_K 18.23 GB Download
LFM2-24B-A2B.imatrix.gguf GGUF 53.52 MB Download

Model Details Live

Model Slug
mradermacher/lfm2-24b-a2b-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2026-02-25
Last Modified
2026-02-25
Gated
No
Private
No
HF SHA
fcfb7a47b993dec043dcebebbf8bf46a94a38204
License
other
Language
en, ar, zh, fr, de, ja, ko, es, pt
Base Model
LiquidAI/LFM2-24B-A2B

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "LiquidAI/LFM2-24B-A2B",
    "language": [
      "en",
      "ar",
      "zh",
      "fr",
      "de",
      "ja",
      "ko",
      "es",
      "pt"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "LICENSE",
    "license_name": "lfm1.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "liquid",
      "lfm2",
      "edge"
    ],
    "frontmatter": {
      "base_model": "LiquidAI/LFM2-24B-A2B",
      "language": [
        "en",
        "ar",
        "zh",
        "fr",
        "de",
        "ja",
        "ko",
        "es",
        "pt"
      ],
      "library_name": "transformers",
      "license": "other",
      "license_link": "LICENSE",
      "license_name": "lfm1.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "liquid",
        "lfm2",
        "edge"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/LiquidAI/LFM2-24B-A2B  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/LFM2-24B-A2B-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: LiquidAI/LFM2-24B-A2B\nlanguage:\n- en\n- ar\n- zh\n- fr\n- de\n- ja\n- ko\n- es\n- pt\nlibrary_name: transformers\nlicense: other\nlicense_link: LICENSE\nlicense_name: lfm1.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- liquid\n- lfm2\n- edge\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/LiquidAI/LFM2-24B-A2B\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#LFM2-24B-A2B-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/LFM2-24B-A2B-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/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.imatrix.gguf) | imatrix | 0.2 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ1_S.gguf) | i1-IQ1_S | 4.9 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ1_M.gguf) | i1-IQ1_M | 5.5 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 6.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 7.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ2_S.gguf) | i1-IQ2_S | 7.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ2_M.gguf) | i1-IQ2_M | 7.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 8.2 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q2_K.gguf) | i1-Q2_K | 8.8 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 9.3 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 9.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ3_S.gguf) | i1-IQ3_S | 10.4 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 10.4 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ3_M.gguf) | i1-IQ3_M | 10.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 11.5 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 12.4 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 12.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q4_0.gguf) | i1-Q4_0 | 13.6 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 13.6 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 14.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q4_1.gguf) | i1-Q4_1 | 15.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 16.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 17.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/LFM2-24B-A2B-i1-GGUF/resolve/main/LFM2-24B-A2B.i1-Q6_K.gguf) | i1-Q6_K | 19.7 | 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",
    "liquid",
    "lfm2",
    "edge",
    "en",
    "ar",
    "zh",
    "fr",
    "de",
    "ja",
    "ko",
    "es",
    "pt",
    "base_model:LiquidAI/LFM2-24B-A2B",
    "base_model:quantized:LiquidAI/LFM2-24B-A2B",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 6,
  "downloads": 873,
  "gated": false,
  "private": false,
  "last_modified": "2026-02-25T10:00:10.000Z",
  "created_at": "2026-02-25T06:18:15.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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