mradermacher/hunyuanocr-gguf overview

{
  "metadata": {},
  "card_data": {
    "base_model": "tencent/HunyuanOCR",
    "language": [
      "multilingual"
    ],
    "library_name": "transformers",
    "license": "other",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "ocr",
      "hunyuan",
      "vision-language",
      "image-to-text",
      "1B",
      "end-to-end"
    ],
    "frontmatter": {
      "base_model": "tencent/HunyuanOCR",
      "language": [
        "multilingual"
      ],
      "library_name": "transformers",
      "license": "other",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "ocr",
        "hunyuan",
        "vision-language",
        "image-to-text",
        "1B",
        "end-to-end"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/tencent/HunyuanOCR  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/HunyuanOCR-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: tencent/HunyuanOCR\nlanguage:\n- multilingual\nlibrary_name: transformers\nlicense: other\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- ocr\n- hunyuan\n- vision-language\n- image-to-text\n- 1B\n- end-to-end\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags:  -->\n<!-- ### quants:  x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nstatic quants of https://huggingface.co/tencent/HunyuanOCR\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#HunyuanOCR-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/HunyuanOCR-i1-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/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q2_K.gguf) | Q2_K | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q3_K_S.gguf) | Q3_K_S | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q3_K_M.gguf) | Q3_K_M | 0.4 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q3_K_L.gguf) | Q3_K_L | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.IQ4_XS.gguf) | IQ4_XS | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q4_K_S.gguf) | Q4_K_S | 0.4 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q4_K_M.gguf) | Q4_K_M | 0.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q5_K_S.gguf) | Q5_K_S | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q5_K_M.gguf) | Q5_K_M | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q6_K.gguf) | Q6_K | 0.5 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.Q8_0.gguf) | Q8_0 | 0.7 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.8 | multi-modal supplement |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.mmproj-f16.gguf) | mmproj-f16 | 1.1 | multi-modal supplement |\n| [GGUF](https://huggingface.co/mradermacher/HunyuanOCR-GGUF/resolve/main/HunyuanOCR.f16.gguf) | f16 | 1.2 | 16 bpw, overkill |\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",
    "ocr",
    "hunyuan",
    "vision-language",
    "image-to-text",
    "1B",
    "end-to-end",
    "multilingual",
    "base_model:tencent/HunyuanOCR",
    "base_model:quantized:tencent/HunyuanOCR",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 644,
  "gated": false,
  "private": false,
  "last_modified": "2026-04-07T17:19:33.000Z",
  "created_at": "2026-04-07T15:59:43.000Z",
  "pipeline_tag": "image-to-text",
  "library_name": "transformers"
}

{
  "_id": "69d529ef11033297bb986df6",
  "id": "mradermacher/HunyuanOCR-GGUF",
  "modelId": "mradermacher/HunyuanOCR-GGUF",
  "sha": "064e0f150acccae9de70b279f0b0f41989ecb735",
  "createdAt": "2026-04-07T15:59:43.000Z",
  "lastModified": "2026-04-07T17:19:33.000Z",
  "author": "mradermacher",
  "downloads": 644,
  "likes": 0,
  "gated": false,
  "private": false,
  "pipeline_tag": "image-to-text",
  "library_name": "transformers",
  "siblings_count": 16
}