mmnga-o/qwen3-swallow-8b-sft-v0.2-gguf Q3_K_L 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.
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mmnga-o/qwen3-swallow-8b-sft-v0.2-gguf overview
tokyotech-llmさんが公開しているQwen3-Swallow-8B-SFT-v0.2のggufフォーマット変換版です。 imatrixのデータはTFMC/imatrix-dataset-for-japanese-llmを使用して作成しました。
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Repository Files & Downloads
13 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Qwen3-Swallow-8B-SFT-v0.2-IQ3_M.gguf | GGUF | IQ3_M | 3.63 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-IQ4_NL.gguf | GGUF | IQ4_NL | 4.46 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-IQ4_XS.gguf | GGUF | IQ4_XS | 4.25 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q3_K_L.gguf | GGUF | Q3_K_L | 4.13 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q3_K_M.gguf | GGUF | Q3_K_M | 3.84 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q4_0.gguf | GGUF | — | 4.45 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q4_K_M.gguf | GGUF | Q4_K_M | 4.68 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q4_K_S.gguf | GGUF | Q4_K_S | 4.47 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q5_0.gguf | GGUF | — | 5.33 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q5_K_M.gguf | GGUF | Q5_K_M | 5.45 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q5_K_S.gguf | GGUF | Q5_K_S | 5.33 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q6_K.gguf | GGUF | Q6_K | 6.26 GB | Download |
| Qwen3-Swallow-8B-SFT-v0.2-Q8_0.gguf | GGUF | — | 8.11 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"license": "apache-2.0",
"language": [
"ja"
],
"datasets": [
"TFMC/imatrix-dataset-for-japanese-llm"
],
"base_model": [
"tokyotech-llm/Qwen3-Swallow-8B-SFT-v0.2"
],
"frontmatter": {},
"hero_image_url": "",
"summary": "tokyotech-llmさんが公開しているQwen3-Swallow-8B-SFT-v0.2のggufフォーマット変換版です。 imatrixのデータはTFMC/imatrix-dataset-for-japanese-llmを使用して作成しました。",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "\n---\nlicense: apache-2.0\nlanguage:\n- ja\ndatasets:\n- TFMC/imatrix-dataset-for-japanese-llm\nbase_model:\n- tokyotech-llm/Qwen3-Swallow-8B-SFT-v0.2\n---\n\n# Qwen3-Swallow-8B-SFT-v0.2-gguf\n[tokyotech-llmさんが公開しているQwen3-Swallow-8B-SFT-v0.2](https://huggingface.co/tokyotech-llm/Qwen3-Swallow-8B-SFT-v0.2)のggufフォーマット変換版です。 \n\nimatrixのデータは[TFMC/imatrix-dataset-for-japanese-llm](https://huggingface.co/datasets/TFMC/imatrix-dataset-for-japanese-llm)を使用して作成しました。 \n \n## Usage\n\n```\ngit clone https://github.com/ggml-org/llama.cpp.git\ncd llama.cpp\ncmake -B build -DGGML_CUDA=ON\ncmake --build build --config Release\nbuild/bin/llama-cli -m 'Qwen3-Swallow-8B-SFT-v0.2-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv\n```\n",
"related_quantizations": []
},
"tags": [
"gguf",
"ja",
"dataset:TFMC/imatrix-dataset-for-japanese-llm",
"base_model:tokyotech-llm/Qwen3-Swallow-8B-SFT-v0.2",
"base_model:quantized:tokyotech-llm/Qwen3-Swallow-8B-SFT-v0.2",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 1,
"downloads": 455,
"gated": false,
"private": false,
"last_modified": "2026-02-20T05:44:23.000Z",
"created_at": "2026-02-20T05:16:09.000Z",
"pipeline_tag": "",
"library_name": ""
}
Source payload excerpt (from Hugging Face API)
{
"_id": "6997ee19f0b5adaaf02b1676",
"id": "mmnga-o/Qwen3-Swallow-8B-SFT-v0.2-gguf",
"modelId": "mmnga-o/Qwen3-Swallow-8B-SFT-v0.2-gguf",
"sha": "70d77c73962e9e7571ee3c4f25324f270fcdbe53",
"createdAt": "2026-02-20T05:16:09.000Z",
"lastModified": "2026-02-20T05:44:23.000Z",
"author": "mmnga-o",
"downloads": 455,
"likes": 1,
"gated": false,
"private": false,
"pipeline_tag": "",
"library_name": "",
"siblings_count": 15
}