Model Intelligence Sheet
mradermacher/qwenstral-small-3.1-0.5b-gguf overview
About static quants of https://huggingface.co/alamios/Qwenstral-Small-3.1-0.5B For a convenient overview and download list, visit our model page for this model. weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Downloads
108
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 |
|---|---|---|---|---|
| Qwenstral-Small-3.1-0.5B.IQ4_XS.gguf | GGUF | IQ4_XS | 381.06 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q2_K.gguf | GGUF | Q2_K | 368.82 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q3_K_L.gguf | GGUF | Q3_K_L | 398.15 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q3_K_M.gguf | GGUF | Q3_K_M | 384.90 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q3_K_S.gguf | GGUF | Q3_K_S | 368.49 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q4_K_M.gguf | GGUF | Q4_K_M | 439.28 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q4_K_S.gguf | GGUF | Q4_K_S | 427.51 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q5_K_M.gguf | GGUF | Q5_K_M | 467.52 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q5_K_S.gguf | GGUF | Q5_K_S | 460.49 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q6_K.gguf | GGUF | Q6_K | 584.21 MB | Download |
| Qwenstral-Small-3.1-0.5B.Q8_0.gguf | GGUF | — | 608.36 MB | Download |
| Qwenstral-Small-3.1-0.5B.f16.gguf | GGUF | F16 | 1.11 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "alamios/Qwenstral-Small-3.1-0.5B",
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"tags": [
"qwen",
"qwen2.5",
"mistral",
"mistral-small",
"mistral-small-3.1"
],
"frontmatter": {
"base_model": "alamios/Qwenstral-Small-3.1-0.5B",
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": [],
"quantized_by": "mradermacher",
"tags": [
"qwen",
"qwen2.5",
"mistral",
"mistral-small",
"mistral-small-3.1"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/alamios/Qwenstral-Small-3.1-0.5B ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: alamios/Qwenstral-Small-3.1-0.5B\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n readme_rev: 1\nquantized_by: mradermacher\ntags:\n- qwen\n- qwen2.5\n- mistral\n- mistral-small\n- mistral-small-3.1\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/alamios/Qwenstral-Small-3.1-0.5B\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#Qwenstral-Small-3.1-0.5B-GGUF).***\n\nweighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.\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/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q3_K_S.gguf) | Q3_K_S | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q2_K.gguf) | Q2_K | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.IQ4_XS.gguf) | IQ4_XS | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q3_K_M.gguf) | Q3_K_M | 0.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q3_K_L.gguf) | Q3_K_L | 0.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q4_K_S.gguf) | Q4_K_S | 0.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q4_K_M.gguf) | Q4_K_M | 0.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q5_K_S.gguf) | Q5_K_S | 0.6 | |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q5_K_M.gguf) | Q5_K_M | 0.6 | |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q6_K.gguf) | Q6_K | 0.7 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.Q8_0.gguf) | Q8_0 | 0.7 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/Qwenstral-Small-3.1-0.5B-GGUF/resolve/main/Qwenstral-Small-3.1-0.5B.f16.gguf) | f16 | 1.3 | 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",
"qwen",
"qwen2.5",
"mistral",
"mistral-small",
"mistral-small-3.1",
"en",
"base_model:alamios/Qwenstral-Small-3.1-0.5B",
"base_model:quantized:alamios/Qwenstral-Small-3.1-0.5B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 1,
"downloads": 108,
"gated": false,
"private": false,
"last_modified": "2025-07-11T08:50:39.000Z",
"created_at": "2025-03-18T20:46:37.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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"sha": "06e35809fc5cfd9de87922f72a81b468d0a45f67",
"createdAt": "2025-03-18T20:46:37.000Z",
"lastModified": "2025-07-11T08:50:39.000Z",
"author": "mradermacher",
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