mradermacher/Mistral-Large-Instruct-2411-GGUF

About

static quants of https://huggingface.co/mistralai/Mistral-Large-Instruct-2411

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Mistral-Large-Instruct-2411-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	45.3
PART 1 PART 2	Q3_K_S	52.9
PART 1 PART 2	Q3_K_M	59.2	lower quality
PART 1 PART 2	Q3_K_L	64.7
PART 1 PART 2	IQ4_XS	66.1
PART 1 PART 2	Q4_K_S	69.7	fast, recommended
PART 1 PART 2	Q4_K_M	73.3	fast, recommended
PART 1 PART 2	Q5_K_S	84.5
PART 1 PART 2	Q5_K_M	86.6
PART 1 PART 2 PART 3	Q6_K	100.7	very good quality
PART 1 PART 2 PART 3	Q8_0	130.4	fast, best quality

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

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.