About
weighted/imatrix quants of https://huggingface.co/migtissera/Tess-3-Llama-3.1-405B
static quants are available at https://huggingface.co/mradermacher/Tess-3-Llama-3.1-405B-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 |
---|---|---|---|
PART 1 PART 2 | i1-IQ1_S | 86.9 | for the desperate |
PART 1 PART 2 | i1-IQ1_M | 95.2 | mostly desperate |
PART 1 PART 2 PART 3 | i1-IQ2_XXS | 109.1 | |
PART 1 PART 2 PART 3 | i1-IQ2_XS | 121.2 | |
PART 1 PART 2 PART 3 | i1-IQ2_S | 127.5 | |
PART 1 PART 2 PART 3 | i1-IQ2_M | 138.6 | |
PART 1 PART 2 PART 3 PART 4 | i1-Q2_K | 151.3 | IQ3_XXS probably better |
PART 1 PART 2 PART 3 PART 4 | i1-IQ3_XXS | 157.8 | lower quality |
PART 1 PART 2 PART 3 PART 4 | i1-IQ3_XS | 168.2 | |
PART 1 PART 2 PART 3 PART 4 | i1-Q3_K_S | 177.2 | IQ3_XS probably better |
PART 1 PART 2 PART 3 PART 4 | i1-IQ3_S | 177.7 | beats Q3_K* |
PART 1 PART 2 PART 3 PART 4 | i1-IQ3_M | 183.9 | |
PART 1 PART 2 PART 3 PART 4 | i1-Q3_K_M | 197.6 | IQ3_S probably better |
P1 P2 P3 P4 P5 | i1-Q3_K_L | 215.3 | IQ3_M probably better |
P1 P2 P3 P4 P5 | i1-IQ4_XS | 219.2 | |
P1 P2 P3 P4 P5 | i1-Q4_0 | 232.2 | fast, low quality |
P1 P2 P3 P4 P5 | i1-Q4_K_S | 233.0 | optimal size/speed/quality |
P1 P2 P3 P4 P5 | i1-Q4_K_M | 245.8 | fast, recommended |
P1 P2 P3 P4 P5 P6 | i1-Q5_K_S | 282.3 | |
P1 P2 P3 P4 P5 P6 | i1-Q5_K_M | 289.8 | |
P1 P2 P3 P4 P5 P6 P7 | i1-Q6_K | 336.5 | 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.
Model tree for mradermacher/Tess-3-Llama-3.1-405B-i1-GGUF
Base model
meta-llama/Llama-3.1-405B