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mradermacher/k-exaone-236b-a23b-i1-gguf IQ3_XS 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/k-exaone-236b-a23b-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/LGAI-EXAONE/K-EXAONE-236B-A23B For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-GGUF

transformersgguflg-aiexaonek-exaoneenkoesdejavibase_model:LGAI-EXAONE/K-EXAONE-236B-A23Bbase_model:quantized:LGAI-EXAONE/K-EXAONE-236B-A23Blicense:otherendpoints_compatibleregion:usimatrixconversational
mradermacher/k-exaone-236b-a23b-i1-gguf visual
Downloads
164
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

16 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
K-EXAONE-236B-A23B.i1-IQ3_M.gguf GGUF IQ3_M 96.72 GB Download
K-EXAONE-236B-A23B.i1-IQ3_S.gguf GGUF IQ3_S 95.39 GB Download
K-EXAONE-236B-A23B.i1-IQ3_XS.gguf GGUF IQ3_XS 90.17 GB Download
K-EXAONE-236B-A23B.i1-IQ4_XS.gguf GGUF IQ4_XS 117.74 GB Download
K-EXAONE-236B-A23B.i1-Q2_K.gguf GGUF Q2_K 80.56 GB Download
K-EXAONE-236B-A23B.i1-Q3_K_L.gguf GGUF Q3_K_L 114.39 GB Download
K-EXAONE-236B-A23B.i1-Q3_K_M.gguf GGUF Q3_K_M 105.56 GB Download
K-EXAONE-236B-A23B.i1-Q3_K_S.gguf GGUF Q3_K_S 95.36 GB Download
K-EXAONE-236B-A23B.i1-Q4_0.gguf GGUF 125.04 GB Download
K-EXAONE-236B-A23B.i1-Q4_1.gguf GGUF 138.31 GB Download
K-EXAONE-236B-A23B.i1-Q4_K_M.gguf GGUF Q4_K_M 133.62 GB Download
K-EXAONE-236B-A23B.i1-Q4_K_S.gguf GGUF Q4_K_S 125.52 GB Download
K-EXAONE-236B-A23B.i1-Q5_K_M.gguf GGUF Q5_K_M 156.72 GB Download
K-EXAONE-236B-A23B.i1-Q5_K_S.gguf GGUF Q5_K_S 152.05 GB Download
K-EXAONE-236B-A23B.i1-Q6_K.gguf GGUF Q6_K 181.26 GB Download
K-EXAONE-236B-A23B.imatrix.gguf GGUF 337.81 MB Download

Model Details Live

Model Slug
mradermacher/k-exaone-236b-a23b-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2026-01-15
Last Modified
2026-01-20
Gated
No
Private
No
HF SHA
1411386bb9f8f5dc7b093a6dbcbc89a19f228ac4
License
other
Language
en, ko, es, de, ja, vi
Base Model
LGAI-EXAONE/K-EXAONE-236B-A23B

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "LGAI-EXAONE/K-EXAONE-236B-A23B",
    "language": [
      "en",
      "ko",
      "es",
      "de",
      "ja",
      "vi"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "LICENSE",
    "license_name": "k-exaone",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "lg-ai",
      "exaone",
      "k-exaone"
    ],
    "frontmatter": {
      "base_model": "LGAI-EXAONE/K-EXAONE-236B-A23B",
      "language": [
        "en",
        "ko",
        "es",
        "de",
        "ja",
        "vi"
      ],
      "library_name": "transformers",
      "license": "other",
      "license_link": "LICENSE",
      "license_name": "k-exaone",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "lg-ai",
        "exaone",
        "k-exaone"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/LGAI-EXAONE/K-EXAONE-236B-A23B  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: LGAI-EXAONE/K-EXAONE-236B-A23B\nlanguage:\n- en\n- ko\n- es\n- de\n- ja\n- vi\nlibrary_name: transformers\nlicense: other\nlicense_link: LICENSE\nlicense_name: k-exaone\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- lg-ai\n- exaone\n- k-exaone\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/LGAI-EXAONE/K-EXAONE-236B-A23B\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#K-EXAONE-236B-A23B-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-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/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.imatrix.gguf) | imatrix | 0.5 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q2_K.gguf) | i1-Q2_K | 86.6 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 96.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 102.5 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-IQ3_S.gguf) | i1-IQ3_S | 102.5 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-IQ3_M.gguf) | i1-IQ3_M | 103.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 113.4 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 122.9 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 126.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q4_0.gguf) | i1-Q4_0 | 134.4 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 134.9 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 143.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q4_1.gguf) | i1-Q4_1 | 148.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 163.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 168.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/K-EXAONE-236B-A23B-i1-GGUF/resolve/main/K-EXAONE-236B-A23B.i1-Q6_K.gguf) | i1-Q6_K | 194.7 | 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",
    "lg-ai",
    "exaone",
    "k-exaone",
    "en",
    "ko",
    "es",
    "de",
    "ja",
    "vi",
    "base_model:LGAI-EXAONE/K-EXAONE-236B-A23B",
    "base_model:quantized:LGAI-EXAONE/K-EXAONE-236B-A23B",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 0,
  "downloads": 164,
  "gated": false,
  "private": false,
  "last_modified": "2026-01-20T18:36:49.000Z",
  "created_at": "2026-01-15T15:10:17.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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  "id": "mradermacher/K-EXAONE-236B-A23B-i1-GGUF",
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