mradermacher/cure-med-3b-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/cure-med-3b-gguf overview
About static quants of https://huggingface.co/Aikyam-Lab/CURE-MED-3B For a convenient overview and download list, visit our model page for this model. weighted/imatrix quants are available at https://huggingface.co/mradermacher/CURE-MED-3B-i1-GGUF
Downloads
117
Likes
0
Pipeline
text-generation
Library
transformers
Visibility
Public
Access
Open
Repository Files & Downloads
12 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| CURE-MED-3B.IQ4_XS.gguf | GGUF | IQ4_XS | 1.63 GB | Download |
| CURE-MED-3B.Q2_K.gguf | GGUF | Q2_K | 1.19 GB | Download |
| CURE-MED-3B.Q3_K_L.gguf | GGUF | Q3_K_L | 1.59 GB | Download |
| CURE-MED-3B.Q3_K_M.gguf | GGUF | Q3_K_M | 1.48 GB | Download |
| CURE-MED-3B.Q3_K_S.gguf | GGUF | Q3_K_S | 1.35 GB | Download |
| CURE-MED-3B.Q4_K_M.gguf | GGUF | Q4_K_M | 1.80 GB | Download |
| CURE-MED-3B.Q4_K_S.gguf | GGUF | Q4_K_S | 1.71 GB | Download |
| CURE-MED-3B.Q5_K_M.gguf | GGUF | Q5_K_M | 2.07 GB | Download |
| CURE-MED-3B.Q5_K_S.gguf | GGUF | Q5_K_S | 2.02 GB | Download |
| CURE-MED-3B.Q6_K.gguf | GGUF | Q6_K | 2.36 GB | Download |
| CURE-MED-3B.Q8_0.gguf | GGUF | — | 3.06 GB | Download |
| CURE-MED-3B.f16.gguf | GGUF | F16 | 5.75 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "Aikyam-Lab/CURE-MED-3B",
"datasets": [
"Aikyam-Lab/CUREMED-BENCH"
],
"language": [
"am",
"bn",
"fr",
"ha",
"hi",
"ja",
"ko",
"es",
"sw",
"th",
"tr",
"vi",
"yo"
],
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"tags": [
"reasoning",
"text-generation",
"medical-ai",
"multilingual-ai",
"healthcare",
"LLMs"
],
"frontmatter": {
"base_model": "Aikyam-Lab/CURE-MED-3B",
"datasets": [
"Aikyam-Lab/CUREMED-BENCH"
],
"language": [
"am",
"bn",
"fr",
"ha",
"hi",
"ja",
"ko",
"es",
"sw",
"th",
"tr",
"vi",
"yo"
],
"library_name": "transformers",
"license": "apache-2.0",
"mradermacher": [],
"quantized_by": "mradermacher",
"tags": [
"reasoning",
"text-generation",
"medical-ai",
"multilingual-ai",
"healthcare",
"LLMs"
]
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/Aikyam-Lab/CURE-MED-3B ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/CURE-MED-3B-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: Aikyam-Lab/CURE-MED-3B\ndatasets:\n- Aikyam-Lab/CUREMED-BENCH\nlanguage:\n- am\n- bn\n- fr\n- ha\n- hi\n- ja\n- ko\n- es\n- sw\n- th\n- tr\n- vi\n- yo\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n readme_rev: 1\nquantized_by: mradermacher\ntags:\n- reasoning\n- text-generation\n- medical-ai\n- multilingual-ai\n- healthcare\n- LLMs\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/Aikyam-Lab/CURE-MED-3B\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#CURE-MED-3B-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/CURE-MED-3B-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/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q2_K.gguf) | Q2_K | 1.4 | |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q3_K_S.gguf) | Q3_K_S | 1.6 | |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q3_K_M.gguf) | Q3_K_M | 1.7 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q3_K_L.gguf) | Q3_K_L | 1.8 | |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.IQ4_XS.gguf) | IQ4_XS | 1.9 | |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q4_K_S.gguf) | Q4_K_S | 1.9 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q4_K_M.gguf) | Q4_K_M | 2.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q5_K_S.gguf) | Q5_K_S | 2.3 | |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q5_K_M.gguf) | Q5_K_M | 2.3 | |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q6_K.gguf) | Q6_K | 2.6 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.Q8_0.gguf) | Q8_0 | 3.4 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/CURE-MED-3B-GGUF/resolve/main/CURE-MED-3B.f16.gguf) | f16 | 6.3 | 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",
"reasoning",
"text-generation",
"medical-ai",
"multilingual-ai",
"healthcare",
"LLMs",
"am",
"bn",
"fr",
"ha",
"hi",
"ja",
"ko",
"es",
"sw",
"th",
"tr",
"vi",
"yo",
"dataset:Aikyam-Lab/CUREMED-BENCH",
"base_model:Aikyam-Lab/CURE-MED-3B",
"base_model:quantized:Aikyam-Lab/CURE-MED-3B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 0,
"downloads": 117,
"gated": false,
"private": false,
"last_modified": "2026-01-23T01:23:32.000Z",
"created_at": "2026-01-22T16:22:49.000Z",
"pipeline_tag": "text-generation",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
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"createdAt": "2026-01-22T16:22:49.000Z",
"lastModified": "2026-01-23T01:23:32.000Z",
"author": "mradermacher",
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