Hyper-SD is an innovative image synthesis framework that achieves efficient image synthesis through the advantages of trajectory segmentation consistency modeling and low-step inference. The framework combines the advantages of ODE trajectory preservation and reconstruction, while further enhancing performance through human feedback learning and strengthening low-step generation capabilities through score distillation. Hyper-SD achieves SOTA performance in 1 to 8 step inference steps, making it particularly suitable for application scenarios requiring fast and high-quality image generation.