Perceptual Flow Matching Cuts Sampling From 35–50 Steps to 4–8 Across Image, Video, and Editing — No Teacher Model

A 5–10x inference step reduction in flow-matching models — which underlie leading image and video generators — achieved without a teacher model or auxiliary network would cut cost and latency across the entire generative-media production stack, with a training-pipeline-compatible drop-in.