mradermacher/Qwen2.5-0.5B-GGUF

About

static quants of https://huggingface.co/Qwen/Qwen2.5-0.5B

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-0.5B-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	Q3_K_S	0.4
GGUF	IQ3_S	0.4	beats Q3_K*
GGUF	IQ3_XS	0.4
GGUF	Q2_K	0.4
GGUF	IQ3_M	0.4
GGUF	IQ4_XS	0.5
GGUF	Q4_0	0.5	fast, low quality
GGUF	Q4_0_4_4	0.5	fast on arm, low quality
GGUF	Q4_0_4_8	0.5	fast on arm+i8mm, low quality
GGUF	Q4_0_8_8	0.5	fast on arm+sve, low quality
GGUF	IQ4_NL	0.5	prefer IQ4_XS
GGUF	Q3_K_M	0.5	lower quality
GGUF	Q3_K_L	0.5
GGUF	Q4_1	0.5
GGUF	Q4_K_S	0.5	fast, recommended
GGUF	Q5_0	0.5
GGUF	Q4_K_M	0.5	fast, recommended
GGUF	Q5_K_S	0.5
GGUF	Q5_1	0.5
GGUF	Q5_K_M	0.5
GGUF	Q6_K	0.6	very good quality
GGUF	Q8_0	0.6	fast, best quality
GGUF	SOURCE	1.1	source gguf, only provided when it was hard to come by
GGUF	f16	1.1	16 bpw, overkill

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.