mradermacher/fusechat-llama-3.2-1b-instruct-gguf Q4_K_M 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/fusechat-llama-3.2-1b-instruct-gguf overview
About static quants of https://huggingface.co/FuseAI/FuseChat-Llama-3.2-1B-Instruct weighted/imatrix quants are available at https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-i1-GGUF
Downloads
96
Likes
1
Pipeline
—
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
12 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| FuseChat-Llama-3.2-1B-Instruct.IQ4_XS.gguf | GGUF | IQ4_XS | 713.71 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q2_K.gguf | GGUF | Q2_K | 553.96 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q3_K_L.gguf | GGUF | Q3_K_L | 698.59 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q3_K_M.gguf | GGUF | Q3_K_M | 658.84 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q3_K_S.gguf | GGUF | Q3_K_S | 611.96 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q4_K_M.gguf | GGUF | Q4_K_M | 770.27 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q4_K_S.gguf | GGUF | Q4_K_S | 739.71 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q5_K_M.gguf | GGUF | Q5_K_M | 869.27 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q5_K_S.gguf | GGUF | Q5_K_S | 851.21 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q6_K.gguf | GGUF | Q6_K | 974.46 MB | Download |
| FuseChat-Llama-3.2-1B-Instruct.Q8_0.gguf | GGUF | — | 1.23 GB | Download |
| FuseChat-Llama-3.2-1B-Instruct.f16.gguf | GGUF | F16 | 2.31 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "FuseAI/FuseChat-Llama-3.2-1B-Instruct",
"datasets": [
"FuseAI/FuseChat-3.0-DPO-Data"
],
"language": [
"en"
],
"library_name": "transformers",
"quantized_by": "mradermacher",
"frontmatter": {
"base_model": "FuseAI/FuseChat-Llama-3.2-1B-Instruct",
"datasets": [
"FuseAI/FuseChat-3.0-DPO-Data"
],
"language": [
"en"
],
"library_name": "transformers",
"quantized_by": "mradermacher"
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/FuseAI/FuseChat-Llama-3.2-1B-Instruct weighted/imatrix quants are available at https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: FuseAI/FuseChat-Llama-3.2-1B-Instruct\ndatasets:\n- FuseAI/FuseChat-3.0-DPO-Data\nlanguage:\n- en\nlibrary_name: transformers\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: -->\nstatic quants of https://huggingface.co/FuseAI/FuseChat-Llama-3.2-1B-Instruct\n\n<!-- provided-files -->\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-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/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q2_K.gguf) | Q2_K | 0.7 | |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q3_K_S.gguf) | Q3_K_S | 0.7 | |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q3_K_M.gguf) | Q3_K_M | 0.8 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q3_K_L.gguf) | Q3_K_L | 0.8 | |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.IQ4_XS.gguf) | IQ4_XS | 0.8 | |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q4_K_S.gguf) | Q4_K_S | 0.9 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q4_K_M.gguf) | Q4_K_M | 0.9 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q5_K_S.gguf) | Q5_K_S | 1.0 | |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q5_K_M.gguf) | Q5_K_M | 1.0 | |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q6_K.gguf) | Q6_K | 1.1 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.Q8_0.gguf) | Q8_0 | 1.4 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF/resolve/main/FuseChat-Llama-3.2-1B-Instruct.f16.gguf) | f16 | 2.6 | 16 bpw, overkill |\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",
"dataset:FuseAI/FuseChat-3.0-DPO-Data",
"base_model:FuseAI/FuseChat-Llama-3.2-1B-Instruct",
"base_model:quantized:FuseAI/FuseChat-Llama-3.2-1B-Instruct",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 1,
"downloads": 96,
"gated": false,
"private": false,
"last_modified": "2025-02-11T10:35:57.000Z",
"created_at": "2025-02-09T16:16:34.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
"_id": "67a8d4e2f8b31c37084568a3",
"id": "mradermacher/FuseChat-Llama-3.2-1B-Instruct-GGUF",
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"sha": "9ab7627a934ae16e833906dbc751ddfc8e262112",
"createdAt": "2025-02-09T16:16:34.000Z",
"lastModified": "2025-02-11T10:35:57.000Z",
"author": "mradermacher",
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"likes": 1,
"gated": false,
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"pipeline_tag": "",
"library_name": "transformers",
"siblings_count": 14
}