Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

285H Time: 1m 19.28s | total 81.38 pipeline 79.24 te 1.07 callback 0.85 | GPU 18360 MB 15% | RAM 27.86 GB 23%



8163264
CFG=1

Image Added

Image Added

Image Added

CFG=2

Image Added

Image Added

Image Added

CFG=6

Image Added

Image Added

Image Added

Image Added

CFG=8

Image Added

Image Added

Image Added

Image Added

Part 3 - Legs and ribbon

Prompt: Generate a photo of a woman's legs, with her feet crossed and wearing white high-heeled shoes with ribbons tied around her ankles. The shoes should have a pointed toe and a stiletto heel. The woman's legs should be smooth and tanned, with a slight sheen to them. The background should be a light gray color. The photo should be taken from a low angle, looking up at the woman's legs. The ribbons should be tied in a bow shape around the ankles. The shoes should have a red sole. The woman's legs should be slightly bent at the knee.

Parameters: Steps: 32| Size: 1024x1024| Seed: 3286438823| CFG scale: 2| App: SD.Next| Version: 6ea881b| Pipeline: Cosmos2TextToImagePipeline| Operations: txt2img| Model: Cosmos-Predict2-2B-Text2Image


Time: 2m 36.32s | total 159.50 pipeline 156.29 te 2.16 callback 0.83 | GPU 18360 MB 15% | RAM 27.91 GB 23%



81620323264
CFG=1

Image Added

Image Added

Image Added

Image Added

CFG=2

Image Added


CFG=4



CFG=6



CFG=8



System Info

Code Block
Sun Dec  7 14:42:41 2025
app: sdnext.git updated: 2025-12-05 hash: 6ea881b10 url: https://github.com/liutyi/sdnext/tree/pytorch
arch: x86_64 cpu: x86_64 system: Linux release: 6.17.0-7-generic
python: 3.12.3 Torch 2.9.1+xpu
device: Intel(R) Arc(TM) Graphics (1) ipex: 
ram: free:119.61 used:3.46 total:123.07
xformers:  diffusers: 0.36.0.dev0 transformers: 4.57.1
active: xpu dtype: torch.bfloat16 vae: torch.bfloat16 unet: torch.bfloat16
base: nvidia/Cosmos-Predict2-2B-Text2Image refiner: none vae: none te: none unet: none
Backend: ipex; Pipeline: native; Memory optimization: none; Cross-attention: Scaled-Dot-Product

...