base_model: Qwen/Qwen2.5-32B-Instruct
language:
- en
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-32B-Instruct/blob/main/LICENSE
quantized_by: mradermacher
tags:
- chat
About
static quants of https://huggingface.co/Qwen/Qwen2.5-32B-Instruct
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-32B-Instruct-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 | Q2_K | 12.4 | |
| GGUF | IQ3_XS | 13.8 | |
| GGUF | Q3_K_S | 14.5 | |
| GGUF | IQ3_S | 14.5 | beats Q3_K* |
| GGUF | IQ3_M | 14.9 | |
| GGUF | Q3_K_M | 16.0 | lower quality |
| GGUF | Q3_K_L | 17.3 | |
| GGUF | IQ4_XS | 18.0 | |
| GGUF | Q4_0 | 18.7 | fast, low quality |
| GGUF | Q4_0_4_4 | 18.7 | fast on arm, low quality |
| GGUF | Q4_0_4_8 | 18.7 | fast on arm+i8mm, low quality |
| GGUF | Q4_0_8_8 | 18.7 | fast on arm+sve, low quality |
| GGUF | Q4_K_S | 18.9 | fast, recommended |
| GGUF | IQ4_NL | 18.9 | prefer IQ4_XS |
| GGUF | Q4_K_M | 20.0 | fast, recommended |
| GGUF | Q4_1 | 20.7 | |
| GGUF | Q5_0 | 22.7 | |
| GGUF | Q5_K_S | 22.7 | |
| GGUF | Q5_K_M | 23.4 | |
| GGUF | Q5_1 | 24.7 | |
| GGUF | Q6_K | 27.0 | very good quality |
| GGUF | Q8_0 | 34.9 | fast, best quality |
| PART 1 PART 2 | SOURCE | 65.6 | source gguf, only provided when it was hard to come by |
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. Additional thanks to @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.