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mradermacher/gemma-3-r1984-27b-i1-gguf IQ2_XXS GGUF - Free GGUF Download is indexed on GraySoft with repository links, GGUF quant files, and Hugging Face metadata. This page helps you pick a local model for guIDE or other runtimes. See related models in the same shard below.

Model Intelligence Sheet

mradermacher/gemma-3-r1984-27b-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/VIDraft/Gemma-3-R1984-27B For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/Gemma-3-R1984-27B-GGUF This is a vision model - mmproj files (if any) will be in the static repository.

transformersggufenkojazhesruarhiidmlfrdebase_model:VIDraft/Gemma-3-R1984-27Bbase_model:quantized:VIDraft/Gemma-3-R1984-27Blicense:gemmaendpoints_compatibleregion:usimatrixconversational
mradermacher/gemma-3-r1984-27b-i1-gguf visual
Downloads
134
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

24 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Gemma-3-R1984-27B.i1-IQ1_M.gguf GGUF IQ1_M 6.33 GB Download
Gemma-3-R1984-27B.i1-IQ1_S.gguf GGUF IQ1_S 5.83 GB Download
Gemma-3-R1984-27B.i1-IQ2_M.gguf GGUF IQ2_M 8.84 GB Download
Gemma-3-R1984-27B.i1-IQ2_S.gguf GGUF IQ2_S 8.18 GB Download
Gemma-3-R1984-27B.i1-IQ2_XS.gguf GGUF IQ2_XS 7.86 GB Download
Gemma-3-R1984-27B.i1-IQ2_XXS.gguf GGUF IQ2_XXS 7.16 GB Download
Gemma-3-R1984-27B.i1-IQ3_M.gguf GGUF IQ3_M 11.69 GB Download
Gemma-3-R1984-27B.i1-IQ3_S.gguf GGUF IQ3_S 11.33 GB Download
Gemma-3-R1984-27B.i1-IQ3_XS.gguf GGUF IQ3_XS 10.77 GB Download
Gemma-3-R1984-27B.i1-IQ3_XXS.gguf GGUF IQ3_XXS 9.98 GB Download
Gemma-3-R1984-27B.i1-IQ4_XS.gguf GGUF IQ4_XS 13.75 GB Download
Gemma-3-R1984-27B.i1-Q2_K.gguf GGUF Q2_K 9.78 GB Download
Gemma-3-R1984-27B.i1-Q2_K_S.gguf GGUF Q2_K_S 9.09 GB Download
Gemma-3-R1984-27B.i1-Q3_K_L.gguf GGUF Q3_K_L 13.54 GB Download
Gemma-3-R1984-27B.i1-Q3_K_M.gguf GGUF Q3_K_M 12.51 GB Download
Gemma-3-R1984-27B.i1-Q3_K_S.gguf GGUF Q3_K_S 11.33 GB Download
Gemma-3-R1984-27B.i1-Q4_0.gguf GGUF 14.55 GB Download
Gemma-3-R1984-27B.i1-Q4_1.gguf GGUF 15.99 GB Download
Gemma-3-R1984-27B.i1-Q4_K_M.gguf GGUF Q4_K_M 15.41 GB Download
Gemma-3-R1984-27B.i1-Q4_K_S.gguf GGUF Q4_K_S 14.60 GB Download
Gemma-3-R1984-27B.i1-Q5_K_M.gguf GGUF Q5_K_M 17.95 GB Download
Gemma-3-R1984-27B.i1-Q5_K_S.gguf GGUF Q5_K_S 17.48 GB Download
Gemma-3-R1984-27B.i1-Q6_K.gguf GGUF Q6_K 20.64 GB Download
Gemma-3-R1984-27B.imatrix.gguf GGUF 12.48 MB Download

Model Details Live

Model Slug
mradermacher/gemma-3-r1984-27b-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2025-09-26
Last Modified
2025-12-05
Gated
No
Private
No
HF SHA
be4ed735df31035e02f6db3c5751454855db860e
License
gemma
Language
en, ko, ja, zh, es, ru, ar, hi, id, ml, fr, de
Base Model
VIDraft/Gemma-3-R1984-27B

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "VIDraft/Gemma-3-R1984-27B",
    "language": [
      "en",
      "ko",
      "ja",
      "zh",
      "es",
      "ru",
      "ar",
      "hi",
      "id",
      "ml",
      "fr",
      "de"
    ],
    "library_name": "transformers",
    "license": "gemma",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "frontmatter": {
      "base_model": "VIDraft/Gemma-3-R1984-27B",
      "language": [
        "en",
        "ko",
        "ja",
        "zh",
        "es",
        "ru",
        "ar",
        "hi",
        "id",
        "ml",
        "fr",
        "de"
      ],
      "library_name": "transformers",
      "license": "gemma",
      "mradermacher": [],
      "quantized_by": "mradermacher"
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/VIDraft/Gemma-3-R1984-27B  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/Gemma-3-R1984-27B-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: VIDraft/Gemma-3-R1984-27B\nlanguage:\n- en\n- ko\n- ja\n- zh\n- es\n- ru\n- ar\n- hi\n- id\n- ml\n- fr\n- de\nlibrary_name: transformers\nlicense: gemma\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/VIDraft/Gemma-3-R1984-27B\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#Gemma-3-R1984-27B-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/Gemma-3-R1984-27B-GGUF\n\n**This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-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/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ1_S.gguf) | i1-IQ1_S | 6.4 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ1_M.gguf) | i1-IQ1_M | 6.9 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 7.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 8.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ2_S.gguf) | i1-IQ2_S | 8.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ2_M.gguf) | i1-IQ2_M | 9.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 9.9 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q2_K.gguf) | i1-Q2_K | 10.6 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 10.8 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 11.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ3_S.gguf) | i1-IQ3_S | 12.3 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 12.3 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ3_M.gguf) | i1-IQ3_M | 12.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 13.5 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 14.6 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 14.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q4_0.gguf) | i1-Q4_0 | 15.7 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 15.8 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 16.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q4_1.gguf) | i1-Q4_1 | 17.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 18.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 19.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Gemma-3-R1984-27B-i1-GGUF/resolve/main/Gemma-3-R1984-27B.i1-Q6_K.gguf) | i1-Q6_K | 22.3 | 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": [
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    "gguf",
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    "zh",
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    "base_model:VIDraft/Gemma-3-R1984-27B",
    "base_model:quantized:VIDraft/Gemma-3-R1984-27B",
    "license:gemma",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 134,
  "gated": false,
  "private": false,
  "last_modified": "2025-12-05T00:36:00.000Z",
  "created_at": "2025-09-26T05:32:07.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
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Source payload excerpt (from Hugging Face API)
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