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mradermacher/aevum-speedy-0.6b-gguf Q2_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/aevum-speedy-0.6b-gguf overview

About static quants of https://huggingface.co/Aevum-Official/Aevum-Speedy-0.6B For a convenient overview and download list, visit our model page for this model. weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

transformersggufllmcode-generationpythonfinetuned-modelendataset:mbppdataset:deepmind/code_contestsbase_model:Aevum-Official/Aevum-Speedy-0.6Bbase_model:quantized:Aevum-Official/Aevum-Speedy-0.6Blicense:apache-2.0endpoints_compatibleregion:usconversational
mradermacher/aevum-speedy-0.6b-gguf visual
Downloads
187
Likes
0
Pipeline
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

12 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Aevum-Speedy-0.6B.IQ4_XS.gguf GGUF IQ4_XS 352.17 MB Download
Aevum-Speedy-0.6B.Q2_K.gguf GGUF Q2_K 282.52 MB Download
Aevum-Speedy-0.6B.Q3_K_L.gguf GGUF Q3_K_L 351.42 MB Download
Aevum-Speedy-0.6B.Q3_K_M.gguf GGUF Q3_K_M 331.05 MB Download
Aevum-Speedy-0.6B.Q3_K_S.gguf GGUF Q3_K_S 308.11 MB Download
Aevum-Speedy-0.6B.Q4_K_M.gguf GGUF Q4_K_M 378.33 MB Download
Aevum-Speedy-0.6B.Q4_K_S.gguf GGUF Q4_K_S 365.52 MB Download
Aevum-Speedy-0.6B.Q5_K_M.gguf GGUF Q5_K_M 423.83 MB Download
Aevum-Speedy-0.6B.Q5_K_S.gguf GGUF Q5_K_S 416.39 MB Download
Aevum-Speedy-0.6B.Q6_K.gguf GGUF Q6_K 472.17 MB Download
Aevum-Speedy-0.6B.Q8_0.gguf GGUF 609.82 MB Download
Aevum-Speedy-0.6B.f16.gguf GGUF F16 1.12 GB Download

Model Details Live

Model Slug
mradermacher/aevum-speedy-0.6b-gguf
Author
mradermacher
Pipeline Task
Library
transformers
Created
2025-10-17
Last Modified
2025-10-17
Gated
No
Private
No
HF SHA
69a9d92d93584026ee16a24fcecbef6c7db8c487
License
apache-2.0
Language
en
Base Model
Aevum-Official/Aevum-Speedy-0.6B

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "Aevum-Official/Aevum-Speedy-0.6B",
    "datasets": [
      "mbpp",
      "deepmind/code_contests"
    ],
    "language": "en",
    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "llm",
      "code-generation",
      "python",
      "finetuned-model"
    ],
    "frontmatter": {
      "base_model": "Aevum-Official/Aevum-Speedy-0.6B",
      "datasets": [
        "mbpp",
        "deepmind/code_contests"
      ],
      "language": "en",
      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "llm",
        "code-generation",
        "python",
        "finetuned-model"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About         static quants of https://huggingface.co/Aevum-Official/Aevum-Speedy-0.6B  ***For a convenient overview and download list, visit our model page for this model.*** weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: Aevum-Official/Aevum-Speedy-0.6B\ndatasets:\n- mbpp\n- deepmind/code_contests\nlanguage: en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- llm\n- code-generation\n- python\n- finetuned-model\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/Aevum-Official/Aevum-Speedy-0.6B\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#Aevum-Speedy-0.6B-GGUF).***\n\nweighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.\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/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q2_K.gguf) | Q2_K | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q3_K_S.gguf) | Q3_K_S | 0.4 |  |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q3_K_M.gguf) | Q3_K_M | 0.4 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q3_K_L.gguf) | Q3_K_L | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.IQ4_XS.gguf) | IQ4_XS | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q4_K_S.gguf) | Q4_K_S | 0.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q4_K_M.gguf) | Q4_K_M | 0.5 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q5_K_S.gguf) | Q5_K_S | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q5_K_M.gguf) | Q5_K_M | 0.5 |  |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q6_K.gguf) | Q6_K | 0.6 | very good quality |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.Q8_0.gguf) | Q8_0 | 0.7 | fast, best quality |\n| [GGUF](https://huggingface.co/mradermacher/Aevum-Speedy-0.6B-GGUF/resolve/main/Aevum-Speedy-0.6B.f16.gguf) | f16 | 1.3 | 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",
    "llm",
    "code-generation",
    "python",
    "finetuned-model",
    "en",
    "dataset:mbpp",
    "dataset:deepmind/code_contests",
    "base_model:Aevum-Official/Aevum-Speedy-0.6B",
    "base_model:quantized:Aevum-Official/Aevum-Speedy-0.6B",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
  "likes": 0,
  "downloads": 187,
  "gated": false,
  "private": false,
  "last_modified": "2025-10-17T23:46:10.000Z",
  "created_at": "2025-10-17T23:40:06.000Z",
  "pipeline_tag": "",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
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  "id": "mradermacher/Aevum-Speedy-0.6B-GGUF",
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  "sha": "69a9d92d93584026ee16a24fcecbef6c7db8c487",
  "createdAt": "2025-10-17T23:40:06.000Z",
  "lastModified": "2025-10-17T23:46:10.000Z",
  "author": "mradermacher",
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