About

static quants of https://huggingface.co/MiniMaxAI/MiniMax-M2.1

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/MiniMax-M2.1-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 83.4
GGUF Q3_K_S 98.8
GGUF Q3_K_M 109.4 lower quality
GGUF Q3_K_L 118.5
GGUF IQ4_XS 123.3
GGUF Q4_K_S 130.1 fast, recommended
GGUF Q4_K_M 138.4 fast, recommended
GGUF Q5_K_S 157.6
GGUF Q5_K_M 162.4
GGUF Q6_K 187.9 very good quality
P1 P2 P3 P4 P5 P6 Q8_0 243.2 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.

Downloads last month
220
GGUF
Model size
229B params
Architecture
minimax-m2
Hardware compatibility
Log In to view the estimation

2-bit

3-bit

4-bit

5-bit

6-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support

Model tree for mradermacher/MiniMax-M2.1-GGUF

Quantized
(21)
this model