ViBT Image Generation: How Brownian Bridge Models Achieve 4× Faster AI Inference

ViBT: Vision Bridge Transformer at Scale – A Practical Deep Dive What is ViBT and why does it achieve up to 4× faster inference than token-heavy conditional diffusion models while maintaining comparable quality? ViBT is the first large-scale realization of Brownian Bridge generative models for vision tasks. Instead of the classic “noise-to-data” paradigm, it directly learns stochastic trajectories from a structured source (image/video) to a structured target, eliminating most conditioning tokens and dramatically reducing compute. Figure: Example results of ViBT across instruction-based editing, stylization, colorization, and frame interpolation. Why the Noise-to-Data Paradigm Feels Wrong for Conditional Generation Most modern image …