Simplifying, stabilizing, and scaling continuous-time consistency models

OpenAI Blog · 1 year ago

Researchers improved continuous-time consistency models to match the sample quality of leading diffusion models while requiring only two sampling steps instead of many. The models achieved this through simplified architecture, enhanced training stability, and improved scaling methods. This reduces the computational cost of image generation, making the approach more practical for deployment.