mradermacher/huihui-glm-4.7-flash-abliterated-57b-gguf IQ4_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/huihui-glm-4.7-flash-abliterated-57b-gguf overview
About static quants of https://huggingface.co/win10/Huihui-GLM-4.7-Flash-abliterated-57B For a convenient overview and download list, visit our model page for this model. weighted/imatrix quants are available at https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-i1-GGUF
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98
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0
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
11 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Huihui-GLM-4.7-Flash-abliterated-57B.IQ4_XS.gguf | GGUF | IQ4_XS | 27.93 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q2_K.gguf | GGUF | Q2_K | 19.11 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q3_K_L.gguf | GGUF | Q3_K_L | 26.94 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q3_K_M.gguf | GGUF | Q3_K_M | 24.87 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q3_K_S.gguf | GGUF | Q3_K_S | 22.52 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q4_K_M.gguf | GGUF | Q4_K_M | 31.37 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q4_K_S.gguf | GGUF | Q4_K_S | 29.54 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q5_K_M.gguf | GGUF | Q5_K_M | 36.77 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q5_K_S.gguf | GGUF | Q5_K_S | 35.72 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q6_K.gguf | GGUF | Q6_K | 42.64 GB | Download |
| Huihui-GLM-4.7-Flash-abliterated-57B.Q8_0.gguf | GGUF | — | 55.03 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "win10/Huihui-GLM-4.7-Flash-abliterated-57B",
"language": [
"en"
],
"library_name": "transformers",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"frontmatter": {
"base_model": "win10/Huihui-GLM-4.7-Flash-abliterated-57B",
"language": [
"en"
],
"library_name": "transformers",
"mradermacher": [],
"quantized_by": "mradermacher"
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/win10/Huihui-GLM-4.7-Flash-abliterated-57B ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: win10/Huihui-GLM-4.7-Flash-abliterated-57B\nlanguage:\n- en\nlibrary_name: transformers\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: -->\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/win10/Huihui-GLM-4.7-Flash-abliterated-57B\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#Huihui-GLM-4.7-Flash-abliterated-57B-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-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/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q2_K.gguf) | Q2_K | 20.6 | |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q3_K_S.gguf) | Q3_K_S | 24.3 | |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q3_K_M.gguf) | Q3_K_M | 26.8 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q3_K_L.gguf) | Q3_K_L | 29.0 | |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.IQ4_XS.gguf) | IQ4_XS | 30.1 | |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q4_K_S.gguf) | Q4_K_S | 31.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q4_K_M.gguf) | Q4_K_M | 33.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q5_K_S.gguf) | Q5_K_S | 38.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q5_K_M.gguf) | Q5_K_M | 39.6 | |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q6_K.gguf) | Q6_K | 45.9 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-GLM-4.7-Flash-abliterated-57B-GGUF/resolve/main/Huihui-GLM-4.7-Flash-abliterated-57B.Q8_0.gguf) | Q8_0 | 59.2 | fast, best quality |\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.\n\n<!-- end -->\n",
"related_quantizations": []
},
"tags": [
"transformers",
"gguf",
"en",
"base_model:win10/Huihui-GLM-4.7-Flash-abliterated-57B",
"base_model:quantized:win10/Huihui-GLM-4.7-Flash-abliterated-57B",
"endpoints_compatible",
"region:us"
],
"likes": 0,
"downloads": 98,
"gated": false,
"private": false,
"last_modified": "2026-01-29T02:25:34.000Z",
"created_at": "2026-01-28T17:02:22.000Z",
"pipeline_tag": "",
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}
Source payload excerpt (from Hugging Face API)
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