Diffusion Models Beat GANs on Image Synthesis
Why broadly claim an entire class of generative model outperforms another?  They simply show that their particular implementation of a diffusion model attains better performance (for some metric) than the current best implementation of a GAN.  Almost inevitably (and likely in the very near future) someone will invest the time and tuning to squeeze out some more performance from a GAN/VAE/flow, and this title will be outdated.