base_model, language, library_name, quantized_by, tags

base_model	language	library_name	quantized_by	tags
DavidAU/DeepThought-MOE-8X3B-R1-Llama-3.2-Reasoning-18B	en	transformers	mradermacher	Llama 3.2 8 X 3B 128k context moe 8 experts reasoning thinking r1 cot deepseek mixture of experts mergekit merge llama-3 llama-3.2

About

weighted/imatrix quants of https://huggingface.co/DavidAU/DeepThought-MOE-8X3B-R1-Llama-3.2-Reasoning-18B

static quants are available at https://huggingface.co/mradermacher/DeepThought-MOE-8X3B-R1-Llama-3.2-Reasoning-18B-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	i1-IQ1_S	4.2	for the desperate
GGUF	i1-IQ1_M	4.6	mostly desperate
GGUF	i1-IQ2_XXS	5.3
GGUF	i1-IQ2_XS	5.8
GGUF	i1-IQ2_S	5.9
GGUF	i1-IQ2_M	6.4
GGUF	i1-Q2_K_S	6.6	very low quality
GGUF	i1-Q2_K	7.1	IQ3_XXS probably better
GGUF	i1-IQ3_XXS	7.5	lower quality
GGUF	i1-IQ3_XS	7.9
GGUF	i1-IQ3_S	8.4	beats Q3_K*
GGUF	i1-Q3_K_S	8.4	IQ3_XS probably better
GGUF	i1-IQ3_M	8.7
GGUF	i1-Q3_K_M	9.1	IQ3_S probably better
GGUF	i1-Q3_K_L	9.7	IQ3_M probably better
GGUF	i1-IQ4_XS	10.1
GGUF	i1-IQ4_NL	10.7	prefer IQ4_XS
GGUF	i1-Q4_0	10.7	fast, low quality
GGUF	i1-Q4_K_S	10.8	optimal size/speed/quality
GGUF	i1-Q4_K_M	11.4	fast, recommended
GGUF	i1-Q4_1	11.8
GGUF	i1-Q5_K_S	12.9
GGUF	i1-Q5_K_M	13.3
GGUF	i1-Q6_K	15.3	practically like static Q6_K

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.