Consistency models (CMs) are a cutting-edge class of diffusion-based generative models designed for rapid and efficient sampling. However, most existing CMs rely on discretized timesteps, which introduce complex hyperparameter tuning and are susceptible to discretization errors. While continuous-time approaches offer a promising alternative, their adoption has been hindered by significant training instabilities. To overcome these challenges, OpenAI researc