What Are Diffusion Transformers (DiTs)? The Architecture Behind Modern Media Models

Diffusion transformers integrate transformer architectures within diffusion-based generative models to process noisy image, video, or latent tokens using scalable attention mechanisms. This approach distinguishes itself from convolutional U-Net diffusion models by its operational characteristics and impact on performance, cost, and control. The article outlines a five-stage process defining diffusion transformers' input, transformation, and output stages.