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Kimi-K2-Instruct-0905-GGUF
mradermacher/Kimi-K2-Instruct-0905-GGUF
Kimi-K2-Instruct-0905-GGUF is a machine learning model from mradermacher. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
static quants of https://huggingface.co/moonshotai/Kimi-K2-Instruct-0905
Access
Public
Updated Sep 10, 2025
Repo size
7 TB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.part01of1393.4 GB · 1%
At a glance
- Library
- transformers
- License
- other
- Access
- Public
- Created
- Sep 5, 2025
- Updated
- Sep 10, 2025
- SHA
- aa243f07
Base models
Model card
From the Hugging Face model README
About
<!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> <!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: -->static quants of https://huggingface.co/moonshotai/Kimi-K2-Instruct-0905
<!-- provided-files -->For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Kimi-K2-Instruct-0905-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 |
|---|---|---|---|
| P1 P2 P3 P4 P5 P6 P7 P8 | Q2_K | 373.0 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 | Q3_K_S | 442.2 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 | Q3_K_M | 489.2 | lower quality |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 | Q3_K_L | 530.6 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 | IQ4_XS | 551.6 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 | Q4_K_S | 582.6 | fast, recommended |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 | Q4_K_M | 620.7 | fast, recommended |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 | Q5_K_S | 706.5 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16 P17 | Q5_K_M | 728.3 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16 P17 P18 | Q6_K | 842.7 | very good quality |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16 P17 P18 P19 P20 P21 P22 P23 P24 P25 | Q8_0 | 1091.2 | 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.
<!-- end -->- Library
- transformers
- License
- other
- Languages
- en
- Created
- Sep 5, 2025
- Updated
- Sep 10, 2025