mradermacher/Hemlock-Qwen3-Coder-REAP-25B-A3B-GGUF

---

base_model: nbeerbower/Hemlock-Qwen3-Coder-REAP-25B-A3B datasets:

• nbeerbower/hemlock-sft-v0.1

language:

• en

library_name: transformers mradermacher: readme_rev: 1 quantized_by: mradermacher

---

About

static quants of https://huggingface.co/nbeerbower/Hemlock-Qwen3-Coder-REAP-25B-A3B

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Hemlock-Qwen3-Coder-REAP-25B-A3B-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	9.3
GGUF	Q3K_S	10.9
GGUF	Q3K_M	12.1	lower quality
GGUF	Q3K_L	13.1
GGUF	IQ4_XS	13.6
GGUF	Q4K_S	14.3	fast, recommended
GGUF	Q4K_M	15.2	fast, recommended
GGUF	Q5K_S	17.3
GGUF	Q5K_M	17.8
GGUF	Q6_K	20.5	very good quality
GGUF	Q8_0	26.6	fast, best quality

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

!image.png

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.