Model Intelligence Sheet
mradermacher/marco-mini-base-gguf overview
About static quants of https://huggingface.co/AIDC-AI/Marco-Mini-Base For a convenient overview and download list, visit our model page for this model. weighted/imatrix quants are available at https://huggingface.co/mradermacher/Marco-Mini-Base-i1-GGUF
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Pipeline
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Library
transformers
Visibility
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Repository Files & Downloads
11 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Marco-Mini-Base.IQ4_XS.gguf | GGUF | IQ4_XS | 8.77 GB | Download |
| Marco-Mini-Base.Q2_K.gguf | GGUF | Q2_K | 5.96 GB | Download |
| Marco-Mini-Base.Q3_K_L.gguf | GGUF | Q3_K_L | 8.43 GB | Download |
| Marco-Mini-Base.Q3_K_M.gguf | GGUF | Q3_K_M | 7.78 GB | Download |
| Marco-Mini-Base.Q3_K_S.gguf | GGUF | Q3_K_S | 7.05 GB | Download |
| Marco-Mini-Base.Q4_K_M.gguf | GGUF | Q4_K_M | 9.87 GB | Download |
| Marco-Mini-Base.Q4_K_S.gguf | GGUF | Q4_K_S | 9.26 GB | Download |
| Marco-Mini-Base.Q5_K_M.gguf | GGUF | Q5_K_M | 11.54 GB | Download |
| Marco-Mini-Base.Q5_K_S.gguf | GGUF | Q5_K_S | 11.19 GB | Download |
| Marco-Mini-Base.Q6_K.gguf | GGUF | Q6_K | 13.33 GB | Download |
| Marco-Mini-Base.Q8_0.gguf | GGUF | — | 17.25 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "AIDC-AI/Marco-Mini-Base",
"datasets": [
"nvidia/Nemotron-CC-v2",
"nvidia/Nemotron-Pretraining-SFT-v1",
"nvidia/Nemotron-Pretraining-Specialized-v1",
"nvidia/Nemotron-CC-v2.1",
"allenai/dolmino-mix-1124",
"nvidia/Nemotron-CC-Math-v1",
"nvidia/OpenMathInstruct-2",
"HuggingFaceTB/finemath",
"LLM360/MegaMath",
"open-thoughts/OpenThoughts3-1.2M",
"opencsg/Fineweb-Edu-Chinese-V2.1",
"HuggingFaceFW/fineweb-2",
"allenai/dolma3_dolmino_mix-100B-1125"
],
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"library_name": "transformers",
"license": "apache-2.0",
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},
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"frontmatter": {
"base_model": "AIDC-AI/Marco-Mini-Base",
"datasets": [
"nvidia/Nemotron-CC-v2",
"nvidia/Nemotron-Pretraining-SFT-v1",
"nvidia/Nemotron-Pretraining-Specialized-v1",
"nvidia/Nemotron-CC-v2.1",
"allenai/dolmino-mix-1124",
"nvidia/Nemotron-CC-Math-v1",
"nvidia/OpenMathInstruct-2",
"HuggingFaceTB/finemath",
"LLM360/MegaMath",
"open-thoughts/OpenThoughts3-1.2M",
"opencsg/Fineweb-Edu-Chinese-V2.1",
"HuggingFaceFW/fineweb-2",
"allenai/dolma3_dolmino_mix-100B-1125"
],
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},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About static quants of https://huggingface.co/AIDC-AI/Marco-Mini-Base ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Marco-Mini-Base-i1-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: AIDC-AI/Marco-Mini-Base\ndatasets:\n- nvidia/Nemotron-CC-v2\n- nvidia/Nemotron-Pretraining-SFT-v1\n- nvidia/Nemotron-Pretraining-Specialized-v1\n- nvidia/Nemotron-CC-v2.1\n- allenai/dolmino-mix-1124\n- nvidia/Nemotron-CC-Math-v1\n- nvidia/OpenMathInstruct-2\n- HuggingFaceTB/finemath\n- LLM360/MegaMath\n- open-thoughts/OpenThoughts3-1.2M\n- opencsg/Fineweb-Edu-Chinese-V2.1\n- HuggingFaceFW/fineweb-2\n- allenai/dolma3_dolmino_mix-100B-1125\nlanguage:\n- en\n- zh\n- ar\n- de\n- es\n- fr\n- ko\n- ja\n- pt\n- tr\n- id\n- it\n- nl\n- pl\n- ru\n- vi\n- th\n- he\n- uk\n- ms\n- bn\n- cs\n- ur\n- kk\n- el\n- ro\n- hu\n- ne\n- az\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n readme_rev: 1\nquantized_by: mradermacher\ntags:\n- moe\n- mixture-of-experts\n- multilingual\n- upcycling\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/AIDC-AI/Marco-Mini-Base\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#Marco-Mini-Base-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/Marco-Mini-Base-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/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q2_K.gguf) | Q2_K | 6.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q3_K_S.gguf) | Q3_K_S | 7.7 | |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q3_K_M.gguf) | Q3_K_M | 8.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q3_K_L.gguf) | Q3_K_L | 9.1 | |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.IQ4_XS.gguf) | IQ4_XS | 9.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q4_K_S.gguf) | Q4_K_S | 10.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q4_K_M.gguf) | Q4_K_M | 10.7 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q5_K_S.gguf) | Q5_K_S | 12.1 | |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q5_K_M.gguf) | Q5_K_M | 12.5 | |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q6_K.gguf) | Q6_K | 14.4 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Marco-Mini-Base-GGUF/resolve/main/Marco-Mini-Base.Q8_0.gguf) | Q8_0 | 18.6 | 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",
"moe",
"mixture-of-experts",
"multilingual",
"upcycling",
"en",
"zh",
"ar",
"de",
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"fr",
"ko",
"ja",
"pt",
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"dataset:nvidia/Nemotron-CC-v2",
"dataset:nvidia/Nemotron-Pretraining-SFT-v1",
"dataset:nvidia/Nemotron-Pretraining-Specialized-v1",
"dataset:nvidia/Nemotron-CC-v2.1",
"dataset:allenai/dolmino-mix-1124",
"dataset:nvidia/Nemotron-CC-Math-v1",
"dataset:nvidia/OpenMathInstruct-2",
"dataset:HuggingFaceTB/finemath",
"dataset:LLM360/MegaMath",
"dataset:open-thoughts/OpenThoughts3-1.2M",
"dataset:opencsg/Fineweb-Edu-Chinese-V2.1",
"dataset:HuggingFaceFW/fineweb-2",
"dataset:allenai/dolma3_dolmino_mix-100B-1125",
"base_model:AIDC-AI/Marco-Mini-Base",
"base_model:quantized:AIDC-AI/Marco-Mini-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 0,
"downloads": 1356,
"gated": false,
"private": false,
"last_modified": "2026-04-04T15:11:52.000Z",
"created_at": "2026-04-03T18:05:30.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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