mradermacher/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-GGUF

🤗 Hugging Face 来源apache-2.0激活 27B187 GBGGUF✓ 13 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo mradermacher/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-GGUF ./model-folder
需要做种者 →

About

static quants of https://huggingface.co/Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF mmproj-Q8_0 0.7 multi-modal supplement
GGUF mmproj-f16 1.0 multi-modal supplement
GGUF Q2_K 10.2
GGUF Q3_K_S 12.2
GGUF Q3_K_M 13.4 lower quality
GGUF Q3_K_L 14.1
GGUF IQ4_XS 14.9
GGUF Q4_K_S 15.7 fast, recommended
GGUF Q4_K_M 16.6 fast, recommended
GGUF Q5_K_S 18.8
GGUF Q5_K_M 19.5
GGUF Q6_K 22.2 very good quality
GGUF Q8_0 28.7 fast, best quality

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.