Diffusion Model

Diffusion models generate images (and increasingly video or audio) by iteratively denoising from noise toward a sample that matches a prompt.

A prompt conditions the denoising process. Samplers, steps, and guidance scale change speed and look. They are a different family from autoregressive LLMs.