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
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164
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0
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
16 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| 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
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": [
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"ko",
"es",
"de",
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"license": "other",
"license_link": "LICENSE",
"license_name": "k-exaone",
"mradermacher": [],
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"tags": [
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"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\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"
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Source payload excerpt (from Hugging Face API)
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