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

mradermacher/snowflake-arctic-embed-m-v1.5-i1-gguf overview

About weighted/imatrix quants of https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v1.5 For a convenient overview and download list, visit our model page for this model. static quants are available at https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-GGUF

transformersggufsentence-transformersfeature-extractionsentence-similaritymtebarcticsnowflake-arctic-embedtransformers.jsenbase_model:Snowflake/snowflake-arctic-embed-m-v1.5base_model:quantized:Snowflake/snowflake-arctic-embed-m-v1.5license:apache-2.0endpoints_compatibleregion:usimatrix
mradermacher/snowflake-arctic-embed-m-v1.5-i1-gguf visual
Downloads
156
Likes
0
Pipeline
feature-extraction
Library
transformers
Visibility
Public
Access
Open

Repository Files & Downloads

24 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
snowflake-arctic-embed-m-v1.5.i1-IQ1_M.gguf GGUF IQ1_M 36.91 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ1_S.gguf GGUF IQ1_S 35.39 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ2_M.gguf GGUF IQ2_M 45.62 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ2_S.gguf GGUF IQ2_S 43.58 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ2_XS.gguf GGUF IQ2_XS 41.71 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ2_XXS.gguf GGUF IQ2_XXS 39.46 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ3_M.gguf GGUF IQ3_M 57.81 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ3_S.gguf GGUF IQ3_S 55.72 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ3_XS.gguf GGUF IQ3_XS 54.14 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ3_XXS.gguf GGUF IQ3_XXS 48.43 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ4_NL.gguf GGUF IQ4_NL 66.48 MB Download
snowflake-arctic-embed-m-v1.5.i1-IQ4_XS.gguf GGUF IQ4_XS 63.95 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q2_K.gguf GGUF Q2_K 51.61 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q2_K_S.gguf GGUF Q2_K_S 48.02 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q3_K_L.gguf GGUF Q3_K_L 66.16 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q3_K_M.gguf GGUF Q3_K_M 61.24 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q3_K_S.gguf GGUF Q3_K_S 55.72 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q4_0.gguf GGUF 66.62 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q4_1.gguf GGUF 71.54 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q4_K_M.gguf GGUF Q4_K_M 70.83 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q4_K_S.gguf GGUF Q4_K_S 67.04 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q5_K_M.gguf GGUF Q5_K_M 78.85 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q5_K_S.gguf GGUF Q5_K_S 76.60 MB Download
snowflake-arctic-embed-m-v1.5.i1-Q6_K.gguf GGUF Q6_K 87.36 MB Download

Model Details Live

Model Slug
mradermacher/snowflake-arctic-embed-m-v1.5-i1-gguf
Author
mradermacher
Pipeline Task
feature-extraction
Library
transformers
Created
2025-06-08
Last Modified
2025-07-11
Gated
No
Private
No
HF SHA
ae5169a5f6c6341a764c25bb0370479d9ca43659
License
apache-2.0
Language
en
Base Model
Snowflake/snowflake-arctic-embed-m-v1.5

Metadata Inspector

Normalized metadata (stored in metadata_json)
{
  "metadata": {},
  "card_data": {
    "base_model": "Snowflake/snowflake-arctic-embed-m-v1.5",
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "mradermacher": {
      "readme_rev": 1
    },
    "quantized_by": "mradermacher",
    "tags": [
      "sentence-transformers",
      "feature-extraction",
      "sentence-similarity",
      "mteb",
      "arctic",
      "snowflake-arctic-embed",
      "transformers.js"
    ],
    "frontmatter": {
      "base_model": "Snowflake/snowflake-arctic-embed-m-v1.5",
      "language": [
        "en"
      ],
      "library_name": "transformers",
      "license": "apache-2.0",
      "mradermacher": [],
      "quantized_by": "mradermacher",
      "tags": [
        "sentence-transformers",
        "feature-extraction",
        "sentence-similarity",
        "mteb",
        "arctic",
        "snowflake-arctic-embed",
        "transformers.js"
      ]
    },
    "hero_image_url": "https://www.nethype.de/huggingface_embed/quantpplgraph.png",
    "summary": "## About      weighted/imatrix quants of https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v1.5  ***For a convenient overview and download list, visit our model page for this model.*** static quants are available at https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-GGUF",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nbase_model: Snowflake/snowflake-arctic-embed-m-v1.5\nlanguage:\n- en\nlibrary_name: transformers\nlicense: apache-2.0\nmradermacher:\n  readme_rev: 1\nquantized_by: mradermacher\ntags:\n- sentence-transformers\n- feature-extraction\n- sentence-similarity\n- mteb\n- arctic\n- snowflake-arctic-embed\n- transformers.js\n---\n## About\n\n<!-- ### quantize_version: 2 -->\n<!-- ### output_tensor_quantised: 1 -->\n<!-- ### convert_type: hf -->\n<!-- ### vocab_type:  -->\n<!-- ### tags: nicoboss -->\nweighted/imatrix quants of https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v1.5\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#snowflake-arctic-embed-m-v1.5-i1-GGUF).***\n\nstatic quants are available at https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-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/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ1_S.gguf) | i1-IQ1_S | 0.1 | for the desperate |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ1_M.gguf) | i1-IQ1_M | 0.1 | mostly desperate |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ2_S.gguf) | i1-IQ2_S | 0.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ2_M.gguf) | i1-IQ2_M | 0.1 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.2 | very low quality |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.2 | lower quality |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q2_K.gguf) | i1-Q2_K | 0.2 | IQ3_XXS probably better |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ3_S.gguf) | i1-IQ3_S | 0.2 | beats Q3_K* |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q3_K_S.gguf) | i1-Q3_K_S | 0.2 | IQ3_XS probably better |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ3_M.gguf) | i1-IQ3_M | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q3_K_M.gguf) | i1-Q3_K_M | 0.2 | IQ3_S probably better |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ4_XS.gguf) | i1-IQ4_XS | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q3_K_L.gguf) | i1-Q3_K_L | 0.2 | IQ3_M probably better |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-IQ4_NL.gguf) | i1-IQ4_NL | 0.2 | prefer IQ4_XS |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q4_0.gguf) | i1-Q4_0 | 0.2 | fast, low quality |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q4_K_S.gguf) | i1-Q4_K_S | 0.2 | optimal size/speed/quality |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q4_K_M.gguf) | i1-Q4_K_M | 0.2 | fast, recommended |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q4_1.gguf) | i1-Q4_1 | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q5_K_S.gguf) | i1-Q5_K_S | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q5_K_M.gguf) | i1-Q5_K_M | 0.2 |  |\n| [GGUF](https://huggingface.co/mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF/resolve/main/snowflake-arctic-embed-m-v1.5.i1-Q6_K.gguf) | i1-Q6_K | 0.2 | 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",
    "sentence-transformers",
    "feature-extraction",
    "sentence-similarity",
    "mteb",
    "arctic",
    "snowflake-arctic-embed",
    "transformers.js",
    "en",
    "base_model:Snowflake/snowflake-arctic-embed-m-v1.5",
    "base_model:quantized:Snowflake/snowflake-arctic-embed-m-v1.5",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "imatrix"
  ],
  "likes": 0,
  "downloads": 156,
  "gated": false,
  "private": false,
  "last_modified": "2025-07-11T01:09:37.000Z",
  "created_at": "2025-06-08T07:39:46.000Z",
  "pipeline_tag": "feature-extraction",
  "library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
  "_id": "68453e422eaf6095e4231074",
  "id": "mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF",
  "modelId": "mradermacher/snowflake-arctic-embed-m-v1.5-i1-GGUF",
  "sha": "ae5169a5f6c6341a764c25bb0370479d9ca43659",
  "createdAt": "2025-06-08T07:39:46.000Z",
  "lastModified": "2025-07-11T01:09:37.000Z",
  "author": "mradermacher",
  "downloads": 156,
  "likes": 0,
  "gated": false,
  "private": false,
  "pipeline_tag": "feature-extraction",
  "library_name": "transformers",
  "siblings_count": 27
}