AuraSR is a newly released open-source upsampler model with 600 million parameters, derived from the GigaGAN paper, designed to upscale low-resolution images to four times their original resolution, with the possibility of repeated application. It stands out for its ability to efficiently upscale images generated by text-to-image models without any constraints on resolution or upscaling factor. By leveraging the speed of GANs, AuraSR offers a significant advantage over diffusion and autoregressive models, producing 1024px images in just 0.25 seconds. This release is credited to the contributions from lucidrains and is part of fal.ai's initiative, which is also seeking individuals interested in training open-source models.