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mradermacher/pelican1.0-vl-72b-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/X-Humanoid/Pelican1.0-VL-72B For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/Pelican1.0-VL-72B-GGUF This is a vision model - mmproj files (if any) will be in the static repository.

transformersggufPhysical AIembodied-aimultimodal-learningroboticsenbase_model:X-Humanoid/Pelican1.0-VL-72Bbase_model:quantized:X-Humanoid/Pelican1.0-VL-72Blicense:apache-2.0endpoints_compatibleregion:usimatrixconversational
mradermacher/pelican1.0-vl-72b-i1-gguf visual
Downloads
199
Likes
0
Pipeline
robotics
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

21 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Pelican1.0-VL-72B.i1-IQ1_M.gguf GGUF IQ1_M 22.11 GB Download
Pelican1.0-VL-72B.i1-IQ1_S.gguf GGUF IQ1_S 21.13 GB Download
Pelican1.0-VL-72B.i1-IQ2_M.gguf GGUF IQ2_M 27.32 GB Download
Pelican1.0-VL-72B.i1-IQ2_S.gguf GGUF IQ2_S 26.02 GB Download
Pelican1.0-VL-72B.i1-IQ2_XS.gguf GGUF IQ2_XS 25.20 GB Download
Pelican1.0-VL-72B.i1-IQ2_XXS.gguf GGUF IQ2_XXS 23.74 GB Download
Pelican1.0-VL-72B.i1-IQ3_M.gguf GGUF IQ3_M 33.07 GB Download
Pelican1.0-VL-72B.i1-IQ3_S.gguf GGUF IQ3_S 32.12 GB Download
Pelican1.0-VL-72B.i1-IQ3_XS.gguf GGUF IQ3_XS 30.59 GB Download
Pelican1.0-VL-72B.i1-IQ3_XXS.gguf GGUF IQ3_XXS 29.66 GB Download
Pelican1.0-VL-72B.i1-IQ4_XS.gguf GGUF IQ4_XS 36.98 GB Download
Pelican1.0-VL-72B.i1-Q2_K.gguf GGUF Q2_K 27.76 GB Download
Pelican1.0-VL-72B.i1-Q2_K_S.gguf GGUF Q2_K_S 27.54 GB Download
Pelican1.0-VL-72B.i1-Q3_K_L.gguf GGUF Q3_K_L 36.79 GB Download
Pelican1.0-VL-72B.i1-Q3_K_M.gguf GGUF Q3_K_M 35.11 GB Download
Pelican1.0-VL-72B.i1-Q3_K_S.gguf GGUF Q3_K_S 32.12 GB Download
Pelican1.0-VL-72B.i1-Q4_0.gguf GGUF 38.54 GB Download
Pelican1.0-VL-72B.i1-Q4_1.gguf GGUF 42.56 GB Download
Pelican1.0-VL-72B.i1-Q4_K_M.gguf GGUF Q4_K_M 44.16 GB Download
Pelican1.0-VL-72B.i1-Q4_K_S.gguf GGUF Q4_K_S 40.88 GB Download
Pelican1.0-VL-72B.imatrix.gguf GGUF 24.11 MB Download

Model Details Live

Model Slug
mradermacher/pelican1.0-vl-72b-i1-gguf
Author
mradermacher
Pipeline Task
robotics
Library
transformers
Created
2025-11-15
Last Modified
2026-02-06
Gated
No
Private
No
HF SHA
52ef70af285d82b5178e03788b95c86da0fc2da9
License
apache-2.0
Language
en
Base Model
X-Humanoid/Pelican1.0-VL-72B

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "X-Humanoid/Pelican1.0-VL-72B",
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "Physical AI",
      "embodied-ai",
      "multimodal-learning",
      "robotics"
    ],
    "frontmatter": {
      "base_model": "X-Humanoid/Pelican1.0-VL-72B",
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "Physical AI",
        "embodied-ai",
        "multimodal-learning",
        "robotics"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/X-Humanoid/Pelican1.0-VL-72B  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/Pelican1.0-VL-72B-GGUF **This is a vision model - mmproj files (if any) will be in the static repository.**",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: X-Humanoid/Pelican1.0-VL-72B\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- Physical AI\n- embodied-ai\n- multimodal-learning\n- robotics\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/X-Humanoid/Pelican1.0-VL-72B\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#Pelican1.0-VL-72B-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/Pelican1.0-VL-72B-GGUF\n\n**This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-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/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ1_S.gguf) | i1-IQ1_S | 22.8 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ1_M.gguf) | i1-IQ1_M | 23.8 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 25.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 27.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ2_S.gguf) | i1-IQ2_S | 28.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ2_M.gguf) | i1-IQ2_M | 29.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 29.7 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q2_K.gguf) | i1-Q2_K | 29.9 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 31.9 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 32.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ3_S.gguf) | i1-IQ3_S | 34.6 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 34.6 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ3_M.gguf) | i1-IQ3_M | 35.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 37.8 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 39.6 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 39.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q4_0.gguf) | i1-Q4_0 | 41.5 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 44.0 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q4_1.gguf) | i1-Q4_1 | 45.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 47.5 | fast, recommended |\n| [PART 1](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q5_K_S.gguf.part2of2) | i1-Q5_K_S | 51.5 |  |\n| [PART 1](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q5_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q5_K_M.gguf.part2of2) | i1-Q5_K_M | 54.5 |  |\n| [PART 1](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Pelican1.0-VL-72B-i1-GGUF/resolve/main/Pelican1.0-VL-72B.i1-Q6_K.gguf.part2of2) | i1-Q6_K | 64.4 | 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",
    "Physical AI",
    "embodied-ai",
    "multimodal-learning",
    "robotics",
    "en",
    "base_model:X-Humanoid/Pelican1.0-VL-72B",
    "base_model:quantized:X-Humanoid/Pelican1.0-VL-72B",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 199,
  "gated": false,
  "private": false,
  "last_modified": "2026-02-06T14:51:39.000Z",
  "created_at": "2025-11-15T02:48:15.000Z",
  "pipeline_tag": "robotics",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
  "_id": "6917e9efb9d00158e224d2b1",
  "id": "mradermacher/Pelican1.0-VL-72B-i1-GGUF",
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  "sha": "52ef70af285d82b5178e03788b95c86da0fc2da9",
  "createdAt": "2025-11-15T02:48:15.000Z",
  "lastModified": "2026-02-06T14:51:39.000Z",
  "author": "mradermacher",
  "downloads": 199,
  "likes": 0,
  "gated": false,
  "private": false,
  "pipeline_tag": "robotics",
  "library_name": "transformers",
  "siblings_count": 29
}