Gemma4-26B-A4B-Korean-Opus-4.6-Distilled-GGUF – AI Model by mradermacher | AlphaNeural AI

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mradermacher/
Gemma4-26B-A4B-Korean-Opus-4.6-Distilled-GGUF

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Jongsim/claude-opus-4.6-reasoning-12k-ko-filtered-v2

jiwon9703/KoGemopus-4-26B-A4B-experimental

endpoints_compatible

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About

static quants of https://huggingface.co/jiwon9703/KoGemopus-4-26B-A4B-experimental

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Gemma4-26B-A4B-Korean-Opus-4.6-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	0.9	multi-modal supplement
GGUF	mmproj-f16	1.3	multi-modal supplement
GGUF	Q2_K	10.7
GGUF	Q3_K_S	12.3
GGUF	Q3_K_M	13.4	lower quality
GGUF	Q3_K_L	13.9
GGUF	IQ4_XS	14.2
GGUF	Q4_K_S	15.6	fast, recommended
GGUF	Q4_K_M	16.9	fast, recommended
GGUF	Q5_K_S	18.1
GGUF	Q5_K_M	19.2
GGUF	Q6_K	22.7	very good quality
GGUF	Q8_0	27.0	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.