Model Intelligence Sheet
mradermacher/olmo-2-0425-1b-instruct-i1-gguf overview
About weighted/imatrix quants of https://huggingface.co/allenai/OLMo-2-0425-1B-Instruct static quants are available at https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-GGUF
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transformers
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Repository Files & Downloads
24 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| OLMo-2-0425-1B-Instruct.i1-IQ1_M.gguf | GGUF | IQ1_M | 439.96 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ1_S.gguf | GGUF | IQ1_S | 419.71 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ2_M.gguf | GGUF | IQ2_M | 568.36 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ2_S.gguf | GGUF | IQ2_S | 541.36 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ2_XS.gguf | GGUF | IQ2_XS | 502.71 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ2_XXS.gguf | GGUF | IQ2_XXS | 473.71 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ3_M.gguf | GGUF | IQ3_M | 710.15 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ3_S.gguf | GGUF | IQ3_S | 688.90 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ3_XS.gguf | GGUF | IQ3_XS | 664.90 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ3_XXS.gguf | GGUF | IQ3_XXS | 609.86 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ4_NL.gguf | GGUF | IQ4_NL | 850.93 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 812.80 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q2_K.gguf | GGUF | Q2_K | 603.99 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q2_K_S.gguf | GGUF | Q2_K_S | 572.49 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 787.90 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 742.90 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 688.90 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q4_0.gguf | GGUF | — | 852.93 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q4_1.gguf | GGUF | — | 927.18 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 892.18 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 856.93 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 1.00 GB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 1003.43 MB | Download |
| OLMo-2-0425-1B-Instruct.i1-Q6_K.gguf | GGUF | Q6_K | 1.14 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": "allenai/OLMo-2-0425-1B-Instruct",
"datasets": [
"allenai/RLVR-MATH"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher",
"frontmatter": {
"base_model": "allenai/OLMo-2-0425-1B-Instruct",
"datasets": [
"allenai/RLVR-MATH"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "apache-2.0",
"quantized_by": "mradermacher"
},
"hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
"summary": "## About weighted/imatrix quants of https://huggingface.co/allenai/OLMo-2-0425-1B-Instruct static quants are available at https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-GGUF",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: allenai/OLMo-2-0425-1B-Instruct\ndatasets:\n- allenai/RLVR-MATH\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\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: nicoboss -->\nweighted/imatrix quants of https://huggingface.co/allenai/OLMo-2-0425-1B-Instruct\n\n<!-- provided-files -->\nstatic quants are available at https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-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/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ1_S.gguf) | i1-IQ1_S | 0.5 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ1_M.gguf) | i1-IQ1_M | 0.6 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.6 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.6 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ2_S.gguf) | i1-IQ2_S | 0.7 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ2_M.gguf) | i1-IQ2_M | 0.7 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.7 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q2_K.gguf) | i1-Q2_K | 0.7 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.7 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.8 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ3_S.gguf) | i1-IQ3_S | 0.8 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q3_K_S.gguf) | i1-Q3_K_S | 0.8 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ3_M.gguf) | i1-IQ3_M | 0.8 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q3_K_M.gguf) | i1-Q3_K_M | 0.9 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q3_K_L.gguf) | i1-Q3_K_L | 0.9 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ4_XS.gguf) | i1-IQ4_XS | 1.0 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-IQ4_NL.gguf) | i1-IQ4_NL | 1.0 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q4_0.gguf) | i1-Q4_0 | 1.0 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q4_K_S.gguf) | i1-Q4_K_S | 1.0 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q4_K_M.gguf) | i1-Q4_K_M | 1.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q4_1.gguf) | i1-Q4_1 | 1.1 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q5_K_S.gguf) | i1-Q5_K_S | 1.2 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q5_K_M.gguf) | i1-Q5_K_M | 1.2 | |\n| [GGUF](https://huggingface.co/mradermacher/OLMo-2-0425-1B-Instruct-i1-GGUF/resolve/main/OLMo-2-0425-1B-Instruct.i1-Q6_K.gguf) | i1-Q6_K | 1.3 | practically like static Q6_K |\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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.\n\n<!-- end -->\n",
"related_quantizations": []
},
"tags": [
"transformers",
"gguf",
"en",
"dataset:allenai/RLVR-MATH",
"base_model:allenai/OLMo-2-0425-1B-Instruct",
"base_model:quantized:allenai/OLMo-2-0425-1B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 0,
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"gated": false,
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"last_modified": "2025-05-03T07:00:06.000Z",
"created_at": "2025-05-03T06:12:45.000Z",
"pipeline_tag": "",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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