Stable Cascade This model is built upon the Würstchen architecture and its main
difference to other models like Stable Diffusion is that it is working at a much smaller latent space. Why is this
important? The smaller the latent space, the faster you can run inference and the cheaper the training becomes.
How small is the latent space? Stable Diffusion uses a compression factor of 8, resulting in a 1024x1024 image being
encoded to 128x128. Stab