High Quality Diffusion Distillation on a Single GPU with Relative and Absolute Position Matching

RAPM, a single-GPU diffusion distillation method, achieves high-quality generation with efficient training, matching relative and absolute positions using two discriminators. It outperforms the best 1-timestep method with only 4 timesteps, under limited computational resources. The text discusses computational resources for diffusion distillation methods, focusing on SD V1.5, and highlights the use of ODE solvers in diffusion models, noting their struggle with few iterations. The diffusion distillation approach reduces iterations with minimal performance loss.