About
static quants of https://huggingface.co/OpenGVLab/InternVL3_5-241B-A28B
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/InternVL3_5-241B-A28B-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 | mmproj-Q8_0 | 6.1 | multi-modal supplement |
| GGUF | mmproj-f16 | 11.3 | multi-modal supplement |
| PART 1 PART 2 | Q2_K | 85.8 | |
| PART 1 PART 2 PART 3 | Q3_K_S | 101.5 | |
| PART 1 PART 2 PART 3 | Q3_K_M | 112.5 | lower quality |
| PART 1 PART 2 PART 3 | Q3_K_L | 121.9 | |
| PART 1 PART 2 PART 3 | IQ4_XS | 126.8 | |
| PART 1 PART 2 PART 3 | Q4_K_S | 133.8 | fast, recommended |
| PART 1 PART 2 PART 3 | Q4_K_M | 142.3 | fast, recommended |
| PART 1 PART 2 PART 3 PART 4 | Q5_K_S | 162.0 | |
| PART 1 PART 2 PART 3 PART 4 | Q5_K_M | 166.9 | |
| PART 1 PART 2 PART 3 PART 4 | Q6_K | 193.1 | very good quality |
| P1 P2 P3 P4 P5 P6 | Q8_0 | 250.0 | 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.
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Base model
OpenGVLab/InternVL3_5-241B-A28B-Pretrained