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mradermacher/huihui-nvidia-nemotron-nano-9b-v2-abliterated-i1-gguf Q6_K 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/huihui-nvidia-nemotron-nano-9b-v2-abliterated-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-GGUF

transformersggufnvidiapytorchabliterateduncensoredenesfrdeitjabase_model:huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliteratedbase_model:quantized:huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliteratedlicense:otherendpoints_compatibleregion:usimatrixconversational
mradermacher/huihui-nvidia-nemotron-nano-9b-v2-abliterated-i1-gguf visual
Downloads
586
Likes
10
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

25 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ1_M.gguf GGUF IQ1_M 4.52 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ1_S.gguf GGUF IQ1_S 4.49 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_M.gguf GGUF IQ2_M 4.65 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_S.gguf GGUF IQ2_S 4.62 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_XS.gguf GGUF IQ2_XS 4.61 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_XXS.gguf GGUF IQ2_XXS 4.57 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_M.gguf GGUF IQ3_M 4.85 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_S.gguf GGUF IQ3_S 4.78 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_XS.gguf GGUF IQ3_XS 4.78 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_XXS.gguf GGUF IQ3_XXS 4.73 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ4_NL.gguf GGUF IQ4_NL 4.94 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ4_XS.gguf GGUF IQ4_XS 4.91 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q2_K.gguf GGUF Q2_K 4.66 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q2_K_S.gguf GGUF Q2_K_S 4.71 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q3_K_L.gguf GGUF Q3_K_L 5.11 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q3_K_M.gguf GGUF Q3_K_M 5.01 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q3_K_S.gguf GGUF Q3_K_S 4.78 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_0.gguf GGUF 4.97 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_1.gguf GGUF 5.43 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_K_M.gguf GGUF Q4_K_M 6.08 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_K_S.gguf GGUF Q4_K_S 5.79 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q5_K_M.gguf GGUF Q5_K_M 6.58 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q5_K_S.gguf GGUF Q5_K_S 6.32 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q6_K.gguf GGUF Q6_K 8.51 GB Download
Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.imatrix.gguf GGUF 3.74 MB Download

Model Details Live

Model Slug
mradermacher/huihui-nvidia-nemotron-nano-9b-v2-abliterated-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2026-01-05
Last Modified
2026-01-05
Gated
No
Private
No
HF SHA
438ffd1b6031877fafa8b39588775aae9fd942b4
License
other
Language
en, es, fr, de, it, ja
Base Model
huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated",
    "language": [
      "en",
      "es",
      "fr",
      "de",
      "it",
      "ja"
    ],
    "library_name": "transformers",
    "license": "other",
    "license_link": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/",
    "license_name": "nvidia-open-model-license",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "nvidia",
      "pytorch",
      "abliterated",
      "uncensored"
    ],
    "frontmatter": {
      "base_model": "huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated",
      "language": [
        "en",
        "es",
        "fr",
        "de",
        "it",
        "ja"
      ],
      "library_name": "transformers",
      "license": "other",
      "license_link": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/",
      "license_name": "nvidia-open-model-license",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "nvidia",
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        "abliterated",
        "uncensored"
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    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated\nlanguage:\n- en\n- es\n- fr\n- de\n- it\n- ja\nlibrary_name: transformers\nlicense: other\nlicense_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/\nlicense_name: nvidia-open-model-license\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- nvidia\n- pytorch\n- abliterated\n- uncensored\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags: nicoboss -->\n<!-- ### quants:  Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->\n<!-- ### quants_skip:  -->\n<!-- ### skip_mmproj:  -->\nweighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated\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#Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-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/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ1_S.gguf) | i1-IQ1_S | 4.9 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ1_M.gguf) | i1-IQ1_M | 5.0 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 5.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_XS.gguf) | i1-IQ2_XS | 5.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_S.gguf) | i1-IQ2_S | 5.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ2_M.gguf) | i1-IQ2_M | 5.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q2_K.gguf) | i1-Q2_K | 5.1 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q2_K_S.gguf) | i1-Q2_K_S | 5.2 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 5.2 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_S.gguf) | i1-IQ3_S | 5.2 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_XS.gguf) | i1-IQ3_XS | 5.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q3_K_S.gguf) | i1-Q3_K_S | 5.2 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ3_M.gguf) | i1-IQ3_M | 5.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ4_XS.gguf) | i1-IQ4_XS | 5.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-IQ4_NL.gguf) | i1-IQ4_NL | 5.4 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_0.gguf) | i1-Q4_0 | 5.4 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q3_K_M.gguf) | i1-Q3_K_M | 5.5 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q3_K_L.gguf) | i1-Q3_K_L | 5.6 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_1.gguf) | i1-Q4_1 | 5.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_K_S.gguf) | i1-Q4_K_S | 6.3 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q4_K_M.gguf) | i1-Q4_K_M | 6.6 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q5_K_S.gguf) | i1-Q5_K_S | 6.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q5_K_M.gguf) | i1-Q5_K_M | 7.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF/resolve/main/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated.i1-Q6_K.gguf) | i1-Q6_K | 9.2 | practically like static Q6_K |\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. 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",
    "nvidia",
    "pytorch",
    "abliterated",
    "uncensored",
    "en",
    "es",
    "fr",
    "de",
    "it",
    "ja",
    "base_model:huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated",
    "base_model:quantized:huihui-ai/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated",
    "license:other",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 10,
  "downloads": 586,
  "gated": false,
  "private": false,
  "last_modified": "2026-01-05T07:13:26.000Z",
  "created_at": "2026-01-05T06:15:58.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
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  "id": "mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF",
  "modelId": "mradermacher/Huihui-NVIDIA-Nemotron-Nano-9B-v2-abliterated-i1-GGUF",
  "sha": "438ffd1b6031877fafa8b39588775aae9fd942b4",
  "createdAt": "2026-01-05T06:15:58.000Z",
  "lastModified": "2026-01-05T07:13:26.000Z",
  "author": "mradermacher",
  "downloads": 586,
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  "siblings_count": 27
}