Simplifying, stabilizing, and scaling continuous-time consistency models

OpenAI introduced sCM and scaled continuous-time consistency models to 1.5B parameters on ImageNet at 512×512. The post says sCM reaches sample quality comparable to leading diffusion models in 2 sampling steps, with about 50x wall-clock speedup. Its largest model generates one sample in 0.11s on a single A100 at batch size 1 without inference optimization.

Why it matters: This clears HKR-H/K/R: the hook is 2-step sampling with diffusion-like quality, and the paper gives concrete numbers—1.5B params, ImageNet 512x512, ~50x wall-clock speed, and 0.11s per sample on one A100. Strong research release, but not a shipped product, so featured fits better