Iris 3b

Generative priors are a promising foundation for downstream vision tasks. In this project we explore pixel-space generative models as an alternative to vision foundation models such as DINOv2. Most image generators work in a compressed "latent" space and rely on a separate decoder to turn that into an image. Iris-3B skips that step: the network itself outputs every pixel, so nothing is lost to a lossy, texture-biased latent. You type a prompt, and you get a 1024-pixel image.