mradermacher/Devstral-Small-2507-Rebased-Vision-GGUF

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base_model: kmouratidis/Devstral-Small-2507-Rebased-Vision language:

• en
• fr
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• es
• pt
• it
• ja
• ko
• ru
• zh
• ar
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library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags:

• mistral
• vision

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About

static quants of https://huggingface.co/kmouratidis/Devstral-Small-2507-Rebased-Vision

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Devstral-Small-2507-Rebased-Vision-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	0.6	multi-modal supplement
GGUF	mmproj-f16	1.0	multi-modal supplement
GGUF	Q2_K	9.0
GGUF	Q3K_S	10.5
GGUF	Q3K_M	11.6	lower quality
GGUF	Q3K_L	12.5
GGUF	IQ4_XS	13.0
GGUF	Q4K_S	13.6	fast, recommended
GGUF	Q4K_M	14.4	fast, recommended
GGUF	Q5K_S	16.4
GGUF	Q5K_M	16.9
GGUF	Q6_K	19.4	very good quality
GGUF	Q8_0	25.2	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.