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mradermacher/aquif-grounding-7b-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/aquif-grounding-7b-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/aquif-ai/aquif-Grounding-7B For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/aquif-Grounding-7B-GGUF

transformersggufvlmaquifqwencuaocrcomputeruseagentsotaclaudeendeitptfrhiesthzhjalicense:mitendpoints_compatibleregion:usimatrixconversational
mradermacher/aquif-grounding-7b-i1-gguf visual
Downloads
220
Likes
1
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

25 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
aquif-Grounding-7B.i1-IQ1_M.gguf GGUF IQ1_M 1.90 GB Download
aquif-Grounding-7B.i1-IQ1_S.gguf GGUF IQ1_S 1.77 GB Download
aquif-Grounding-7B.i1-IQ2_M.gguf GGUF IQ2_M 2.59 GB Download
aquif-Grounding-7B.i1-IQ2_S.gguf GGUF IQ2_S 2.42 GB Download
aquif-Grounding-7B.i1-IQ2_XS.gguf GGUF IQ2_XS 2.30 GB Download
aquif-Grounding-7B.i1-IQ2_XXS.gguf GGUF IQ2_XXS 2.12 GB Download
aquif-Grounding-7B.i1-IQ3_M.gguf GGUF IQ3_M 3.33 GB Download
aquif-Grounding-7B.i1-IQ3_S.gguf GGUF IQ3_S 3.26 GB Download
aquif-Grounding-7B.i1-IQ3_XS.gguf GGUF IQ3_XS 3.12 GB Download
aquif-Grounding-7B.i1-IQ3_XXS.gguf GGUF IQ3_XXS 2.90 GB Download
aquif-Grounding-7B.i1-IQ4_NL.gguf GGUF IQ4_NL 4.13 GB Download
aquif-Grounding-7B.i1-IQ4_XS.gguf GGUF IQ4_XS 3.93 GB Download
aquif-Grounding-7B.i1-Q2_K.gguf GGUF Q2_K 2.81 GB Download
aquif-Grounding-7B.i1-Q2_K_S.gguf GGUF Q2_K_S 2.64 GB Download
aquif-Grounding-7B.i1-Q3_K_L.gguf GGUF Q3_K_L 3.81 GB Download
aquif-Grounding-7B.i1-Q3_K_M.gguf GGUF Q3_K_M 3.55 GB Download
aquif-Grounding-7B.i1-Q3_K_S.gguf GGUF Q3_K_S 3.25 GB Download
aquif-Grounding-7B.i1-Q4_0.gguf GGUF 4.14 GB Download
aquif-Grounding-7B.i1-Q4_1.gguf GGUF 4.54 GB Download
aquif-Grounding-7B.i1-Q4_K_M.gguf GGUF Q4_K_M 4.36 GB Download
aquif-Grounding-7B.i1-Q4_K_S.gguf GGUF Q4_K_S 4.15 GB Download
aquif-Grounding-7B.i1-Q5_K_M.gguf GGUF Q5_K_M 5.07 GB Download
aquif-Grounding-7B.i1-Q5_K_S.gguf GGUF Q5_K_S 4.95 GB Download
aquif-Grounding-7B.i1-Q6_K.gguf GGUF Q6_K 5.82 GB Download
aquif-Grounding-7B.imatrix.gguf GGUF 4.35 MB Download

Model Details Live

Model Slug
mradermacher/aquif-grounding-7b-i1-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2025-11-14
Last Modified
2025-12-08
Gated
No
Private
No
HF SHA
4a3e59f0b9b86f2c6d7f5182d25816566dd6cb85
License
mit
Language
en, de, it, pt, fr, hi, es, th, zh, ja
Base Model
aquif-ai/aquif-Grounding-7B

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "aquif-ai/aquif-Grounding-7B",
    "language": [
      "en",
      "de",
      "it",
      "pt",
      "fr",
      "hi",
      "es",
      "th",
      "zh",
      "ja"
    ],
    "library_name": "transformers",
    "license": "mit",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "vlm",
      "aquif",
      "qwen",
      "cua",
      "ocr",
      "computer",
      "use",
      "agent",
      "sota",
      "claude"
    ],
    "frontmatter": {
      "base_model": "aquif-ai/aquif-Grounding-7B",
      "language": [
        "en",
        "de",
        "it",
        "pt",
        "fr",
        "hi",
        "es",
        "th",
        "zh",
        "ja"
      ],
      "library_name": "transformers",
      "license": "mit",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "vlm",
        "aquif",
        "qwen",
        "cua",
        "ocr",
        "computer",
        "use",
        "agent",
        "sota",
        "claude"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         weighted/imatrix quants of https://huggingface.co/aquif-ai/aquif-Grounding-7B  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/aquif-Grounding-7B-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: aquif-ai/aquif-Grounding-7B\nlanguage:\n- en\n- de\n- it\n- pt\n- fr\n- hi\n- es\n- th\n- zh\n- ja\nlibrary_name: transformers\nlicense: mit\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- vlm\n- aquif\n- qwen\n- cua\n- ocr\n- computer\n- use\n- agent\n- sota\n- claude\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/aquif-ai/aquif-Grounding-7B\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#aquif-Grounding-7B-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/aquif-Grounding-7B-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/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ1_S.gguf) | i1-IQ1_S | 2.0 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ1_M.gguf) | i1-IQ1_M | 2.1 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.6 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ2_S.gguf) | i1-IQ2_S | 2.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ2_M.gguf) | i1-IQ2_M | 2.9 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 2.9 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q2_K.gguf) | i1-Q2_K | 3.1 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.2 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.6 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ3_S.gguf) | i1-IQ3_S | 3.6 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ3_M.gguf) | i1-IQ3_M | 3.7 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.9 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.2 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.3 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-IQ4_NL.gguf) | i1-IQ4_NL | 4.5 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q4_0.gguf) | i1-Q4_0 | 4.5 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.6 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.8 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q4_1.gguf) | i1-Q4_1 | 5.0 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/aquif-Grounding-7B-i1-GGUF/resolve/main/aquif-Grounding-7B.i1-Q6_K.gguf) | i1-Q6_K | 6.4 | 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",
    "vlm",
    "aquif",
    "qwen",
    "cua",
    "ocr",
    "computer",
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    "agent",
    "sota",
    "claude",
    "en",
    "de",
    "it",
    "pt",
    "fr",
    "hi",
    "es",
    "th",
    "zh",
    "ja",
    "license:mit",
    "endpoints_compatible",
    "region:us",
    "imatrix",
    "conversational"
  ],
  "likes": 1,
  "downloads": 220,
  "gated": false,
  "private": false,
  "last_modified": "2025-12-08T23:49:28.000Z",
  "created_at": "2025-11-14T17:44:43.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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