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codegemma-7b-GGUF/README.md
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Model: mradermacher/codegemma-7b-GGUF
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2026-06-13 07:16:16 +08:00

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About

static quants of https://huggingface.co/google/codegemma-7b

weighted/imatrix quants are available at https://huggingface.co/mradermacher/codegemma-7b-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 Q4_0_4_4 5.1 fast on arm, low quality
PART 1 PART 2 Q2_K 7.1
PART 1 PART 2 Q3_K_S 8.1
PART 1 PART 2 Q3_K_M 8.8 lower quality
PART 1 PART 2 Q3_K_L 9.5
PART 1 PART 2 IQ4_XS 9.7
PART 1 PART 2 Q4_K_S 10.2 fast, recommended
PART 1 PART 2 Q4_K_M 10.8 fast, recommended
PART 1 PART 2 Q5_K_S 12.1
PART 1 PART 2 Q5_K_M 12.4
PART 1 PART 2 Q6_K 14.1 very good quality
PART 1 PART 2 Q8_0 18.3 fast, best quality
PART 1 PART 2 f16 34.3 16 bpw, overkill

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.