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About

static quants of https://huggingface.co/Vezora/Mistral-22B-v0.2

No imatrix quants will be coming from me, as the model overflowed after 180k tokens and llama.cpp crashed generating most quants with smaller training data.

weighted/imatrix quants by bartowksi (with smaller training data) can be found at https://huggingface.co/bartowski/Mistral-22B-v0.2-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 8.4
GGUF IQ3_XS 9.3
GGUF Q3_K_S 9.7
GGUF IQ3_S 9.8 beats Q3_K*
GGUF IQ3_M 10.2
GGUF Q3_K_M 10.9 lower quality
GGUF Q3_K_L 11.8
GGUF IQ4_XS 12.1
GGUF Q4_K_S 12.8 fast, recommended
GGUF Q4_K_M 13.4 fast, recommended
GGUF Q5_K_S 15.4
GGUF Q5_K_M 15.8
GGUF Q6_K 18.3 very good quality
GGUF Q8_0 23.7 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.

Downloads last month
500
GGUF
Model size
22.2B params
Architecture
llama
+2
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