InstantIR is a blind image restoration method based on diffusion models that can handle unknown degradation problems during testing, enhancing the model's generalization capabilities. This technology dynamically adjusts generation conditions by generating reference images during inference, thereby providing robust generation conditions. Key advantages of InstantIR include the ability to restore details in extremely degraded images, delivering realistic textures, and enabling creative image restoration through text descriptions. This technology has been jointly developed by researchers from Peking University, the InstantX team, and The Chinese University of Hong Kong, with sponsorship support from HuggingFace and fal.ai.