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Ring-1T-GGUF
mradermacher/Ring-1T-GGUF
Ring-1T-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 mit.
static quants of https://huggingface.co/inclusionAI/Ring-1T
Access
Public
Updated Oct 18, 2026
Repo size
6.8 TB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.part01of1196.6 GB · 1%
At a glance
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Oct 29, 2025
- Updated
- Oct 18, 2026
- SHA
- 2658706b
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/inclusionAI/Ring-1T
<!-- 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/Ring-1T-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 | 363.2 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 | Q3_K_S | 430.7 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 | Q3_K_M | 476.6 | lower quality |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 | Q3_K_L | 517.7 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 | IQ4_XS | 536.3 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 | Q4_K_S | 566.6 | fast, recommended |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 | Q4_K_M | 604.3 | fast, recommended |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 | Q5_K_S | 688.1 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16 P17 | Q5_K_M | 709.7 | |
| P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16 P17 | Q6_K | 820.7 | 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 | Q8_0 | 1062.8 | 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.
<!-- end -->- Library
- transformers
- License
- mit
- Languages
- en
- Created
- Oct 29, 2025
- Updated
- Oct 18, 2026