GraySoft
Projects Models About FAQ Contact Download guIDE →
Model Intelligence Sheet

mradermacher/redsage-qwen3-8b-base-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/RISys-Lab/RedSage-Qwen3-8B-Base For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-GGUF

transformersggufgenerated_from_trainercybersecuritycontinual-pretrainingtargeted-pretrainingtext-generationcasual-lmrisys-labenbase_model:RISys-Lab/RedSage-Qwen3-8B-Basebase_model:quantized:RISys-Lab/RedSage-Qwen3-8B-Baseendpoints_compatibleregion:usimatrix
mradermacher/redsage-qwen3-8b-base-i1-gguf visual
Downloads
182
Likes
0
Pipeline
text-generation
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

25 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
RedSage-Qwen3-8B-Base.i1-IQ1_M.gguf GGUF IQ1_M 2.10 GB Download
RedSage-Qwen3-8B-Base.i1-IQ1_S.gguf GGUF IQ1_S 1.97 GB Download
RedSage-Qwen3-8B-Base.i1-IQ2_M.gguf GGUF IQ2_M 2.84 GB Download
RedSage-Qwen3-8B-Base.i1-IQ2_S.gguf GGUF IQ2_S 2.67 GB Download
RedSage-Qwen3-8B-Base.i1-IQ2_XS.gguf GGUF IQ2_XS 2.51 GB Download
RedSage-Qwen3-8B-Base.i1-IQ2_XXS.gguf GGUF IQ2_XXS 2.32 GB Download
RedSage-Qwen3-8B-Base.i1-IQ3_M.gguf GGUF IQ3_M 3.63 GB Download
RedSage-Qwen3-8B-Base.i1-IQ3_S.gguf GGUF IQ3_S 3.53 GB Download
RedSage-Qwen3-8B-Base.i1-IQ3_XS.gguf GGUF IQ3_XS 3.38 GB Download
RedSage-Qwen3-8B-Base.i1-IQ3_XXS.gguf GGUF IQ3_XXS 3.14 GB Download
RedSage-Qwen3-8B-Base.i1-IQ4_NL.gguf GGUF IQ4_NL 4.46 GB Download
RedSage-Qwen3-8B-Base.i1-IQ4_XS.gguf GGUF IQ4_XS 4.25 GB Download
RedSage-Qwen3-8B-Base.i1-Q2_K.gguf GGUF Q2_K 3.06 GB Download
RedSage-Qwen3-8B-Base.i1-Q2_K_S.gguf GGUF Q2_K_S 2.87 GB Download
RedSage-Qwen3-8B-Base.i1-Q3_K_L.gguf GGUF Q3_K_L 4.13 GB Download
RedSage-Qwen3-8B-Base.i1-Q3_K_M.gguf GGUF Q3_K_M 3.84 GB Download
RedSage-Qwen3-8B-Base.i1-Q3_K_S.gguf GGUF Q3_K_S 3.51 GB Download
RedSage-Qwen3-8B-Base.i1-Q4_0.gguf GGUF 4.46 GB Download
RedSage-Qwen3-8B-Base.i1-Q4_1.gguf GGUF 4.89 GB Download
RedSage-Qwen3-8B-Base.i1-Q4_K_M.gguf GGUF Q4_K_M 4.68 GB Download
RedSage-Qwen3-8B-Base.i1-Q4_K_S.gguf GGUF Q4_K_S 4.47 GB Download
RedSage-Qwen3-8B-Base.i1-Q5_K_M.gguf GGUF Q5_K_M 5.45 GB Download
RedSage-Qwen3-8B-Base.i1-Q5_K_S.gguf GGUF Q5_K_S 5.33 GB Download
RedSage-Qwen3-8B-Base.i1-Q6_K.gguf GGUF Q6_K 6.26 GB Download
RedSage-Qwen3-8B-Base.imatrix.gguf GGUF 5.10 MB Download

Model Details Live

Model Slug
mradermacher/redsage-qwen3-8b-base-i1-gguf
Author
mradermacher
Pipeline Task
text-generation
Library
transformers
Created
2026-02-03
Last Modified
2026-02-03
Gated
No
Private
No
HF SHA
b1eecdbd4f14b7500a12057b08d863555be7b2ff
License
Unknown
Language
en
Base Model
RISys-Lab/RedSage-Qwen3-8B-Base

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "RISys-Lab/RedSage-Qwen3-8B-Base",
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "generated_from_trainer",
      "cybersecurity",
      "continual-pretraining",
      "targeted-pretraining",
      "text-generation",
      "casual-lm",
      "risys-lab"
    ],
    "frontmatter": {
      "base_model": "RISys-Lab/RedSage-Qwen3-8B-Base",
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "generated_from_trainer",
        "cybersecurity",
        "continual-pretraining",
        "targeted-pretraining",
        "text-generation",
        "casual-lm",
        "risys-lab"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/RISys-Lab/RedSage-Qwen3-8B-Base  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: RISys-Lab/RedSage-Qwen3-8B-Base\nlanguage:\n- en\nlibrary_name: transformers\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- generated_from_trainer\n- cybersecurity\n- continual-pretraining\n- targeted-pretraining\n- text-generation\n- casual-lm\n- risys-lab\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/RISys-Lab/RedSage-Qwen3-8B-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#RedSage-Qwen3-8B-Base-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-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/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ1_S.gguf) | i1-IQ1_S | 2.2 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ1_M.gguf) | i1-IQ1_M | 2.4 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ2_S.gguf) | i1-IQ2_S | 3.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ2_M.gguf) | i1-IQ2_M | 3.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q2_K_S.gguf) | i1-Q2_K_S | 3.2 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q2_K.gguf) | i1-Q2_K | 3.4 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.5 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.9 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ3_S.gguf) | i1-IQ3_S | 3.9 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ3_M.gguf) | i1-IQ3_M | 4.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.2 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.5 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q4_0.gguf) | i1-Q4_0 | 4.9 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-IQ4_NL.gguf) | i1-IQ4_NL | 4.9 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.9 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.1 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q4_1.gguf) | i1-Q4_1 | 5.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.8 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q5_K_M.gguf) | i1-Q5_K_M | 6.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF/resolve/main/RedSage-Qwen3-8B-Base.i1-Q6_K.gguf) | i1-Q6_K | 6.8 | 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",
    "generated_from_trainer",
    "cybersecurity",
    "continual-pretraining",
    "targeted-pretraining",
    "text-generation",
    "casual-lm",
    "risys-lab",
    "en",
    "base_model:RISys-Lab/RedSage-Qwen3-8B-Base",
    "base_model:quantized:RISys-Lab/RedSage-Qwen3-8B-Base",
    "endpoints_compatible",
    "region:us",
    "imatrix"
  ],
  "likes": 0,
  "downloads": 182,
  "gated": false,
  "private": false,
  "last_modified": "2026-02-03T19:00:09.000Z",
  "created_at": "2026-02-03T07:29:03.000Z",
  "pipeline_tag": "text-generation",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
  "_id": "6981a3bf529b264bc8d64ab5",
  "id": "mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF",
  "modelId": "mradermacher/RedSage-Qwen3-8B-Base-i1-GGUF",
  "sha": "b1eecdbd4f14b7500a12057b08d863555be7b2ff",
  "createdAt": "2026-02-03T07:29:03.000Z",
  "lastModified": "2026-02-03T19:00:09.000Z",
  "author": "mradermacher",
  "downloads": 182,
  "likes": 0,
  "gated": false,
  "private": false,
  "pipeline_tag": "text-generation",
  "library_name": "transformers",
  "siblings_count": 27
}