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mradermacher/arc-base-8b-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/arc-base-8b-gguf overview

About static quants of https://huggingface.co/LoganResearch/ARC-Base-8B For a convenient overview and download list, visit our model page for this model. weighted/imatrix quants are available at https://huggingface.co/mradermacher/ARC-Base-8B-i1-GGUF

transformersggufllamahermescognitive-controldecode-time-interventionrepetition-suppressionbehavioral-controlcontrastive-learninginterpretabilityactivation-engineeringcf-hotarcrlhf-analysisresearchenbase_model:LoganResearch/ARC-Base-8Bbase_model:quantized:LoganResearch/ARC-Base-8Blicense:cc-by-4.0endpoints_compatibleregion:usconversational
mradermacher/arc-base-8b-gguf visual
Downloads
175
Likes
2
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

12 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
ARC-Base-8B.IQ4_XS.gguf GGUF IQ4_XS 4.18 GB Download
ARC-Base-8B.Q2_K.gguf GGUF Q2_K 2.96 GB Download
ARC-Base-8B.Q3_K_L.gguf GGUF Q3_K_L 4.03 GB Download
ARC-Base-8B.Q3_K_M.gguf GGUF Q3_K_M 3.74 GB Download
ARC-Base-8B.Q3_K_S.gguf GGUF Q3_K_S 3.41 GB Download
ARC-Base-8B.Q4_K_M.gguf GGUF Q4_K_M 4.58 GB Download
ARC-Base-8B.Q4_K_S.gguf GGUF Q4_K_S 4.37 GB Download
ARC-Base-8B.Q5_K_M.gguf GGUF Q5_K_M 5.34 GB Download
ARC-Base-8B.Q5_K_S.gguf GGUF Q5_K_S 5.21 GB Download
ARC-Base-8B.Q6_K.gguf GGUF Q6_K 6.14 GB Download
ARC-Base-8B.Q8_0.gguf GGUF 7.95 GB Download
ARC-Base-8B.f16.gguf GGUF F16 14.97 GB Download

Model Details Live

Model Slug
mradermacher/arc-base-8b-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2026-01-18
Last Modified
2026-01-20
Gated
No
Private
No
HF SHA
a7c734a8de41b06eda983c21f1d8349ad7c977e2
License
cc-by-4.0
Language
en
Base Model
LoganResearch/ARC-Base-8B

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "LoganResearch/ARC-Base-8B",
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "cc-by-4.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "llama",
      "hermes",
      "cognitive-control",
      "decode-time-intervention",
      "repetition-suppression",
      "behavioral-control",
      "contrastive-learning",
      "interpretability",
      "activation-engineering",
      "cf-hot",
      "arc",
      "rlhf-analysis",
      "research"
    ],
    "frontmatter": {
      "base_model": "LoganResearch/ARC-Base-8B",
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "cc-by-4.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "llama",
        "hermes",
        "cognitive-control",
        "decode-time-intervention",
        "repetition-suppression",
        "behavioral-control",
        "contrastive-learning",
        "interpretability",
        "activation-engineering",
        "cf-hot",
        "arc",
        "rlhf-analysis",
        "research"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/LoganResearch/ARC-Base-8B  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/ARC-Base-8B-i1-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: LoganResearch/ARC-Base-8B\nlanguage:\n- en\nlibrary_name: transformers\nlicense: cc-by-4.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- llama\n- hermes\n- cognitive-control\n- decode-time-intervention\n- repetition-suppression\n- behavioral-control\n- contrastive-learning\n- interpretability\n- activation-engineering\n- cf-hot\n- arc\n- rlhf-analysis\n- research\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/LoganResearch/ARC-Base-8B\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#ARC-Base-8B-GGUF).***\n\nweighted/imatrix quants are available at https://huggingface.co/mradermacher/ARC-Base-8B-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/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q2_K.gguf) | Q2_K | 3.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q3_K_S.gguf) | Q3_K_S | 3.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q3_K_L.gguf) | Q3_K_L | 4.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.IQ4_XS.gguf) | IQ4_XS | 4.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q5_K_S.gguf) | Q5_K_S | 5.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q5_K_M.gguf) | Q5_K_M | 5.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q6_K.gguf) | Q6_K | 6.7 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/ARC-Base-8B-GGUF/resolve/main/ARC-Base-8B.f16.gguf) | f16 | 16.2 | 16 bpw, overkill |\n\nHere is a handy graph by ikawrakow comparing some lower-quality quant\ntypes (lower is better):\n\n![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)\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",
    "llama",
    "hermes",
    "cognitive-control",
    "decode-time-intervention",
    "repetition-suppression",
    "behavioral-control",
    "contrastive-learning",
    "interpretability",
    "activation-engineering",
    "cf-hot",
    "arc",
    "rlhf-analysis",
    "research",
    "en",
    "base_model:LoganResearch/ARC-Base-8B",
    "base_model:quantized:LoganResearch/ARC-Base-8B",
    "license:cc-by-4.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 2,
  "downloads": 175,
  "gated": false,
  "private": false,
  "last_modified": "2026-01-20T02:04:02.000Z",
  "created_at": "2026-01-18T02:45:16.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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  "id": "mradermacher/ARC-Base-8B-GGUF",
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  "sha": "a7c734a8de41b06eda983c21f1d8349ad7c977e2",
  "createdAt": "2026-01-18T02:45:16.000Z",
  "lastModified": "2026-01-20T02:04:02.000Z",
  "author": "mradermacher",
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