AI Image Upscaler

Traditional image resizing (bilinear, bicubic interpolation) simply stretches pixels, producing blurry results. AI upscaling uses neural networks trained on millions of image pairs (low-res and high-res) to learn what detail should exist at higher resolutions. This tool offers two model families: Swin2SR uses a Shifted Window Transformer architecture that processes the image in overlapping patches, generating sharp details while maintaining consistency across patch boundaries. APISR uses a GAN (Generative Adversarial Network) trained specifically for anime and photographic super-resolution, producing perceptually sharper results. All models run via ONNX Runtime in your browser using WebAssembly — no server processing, no upload, complete privacy.

Use 2x Fast (Swin2SR, 3.9MB) for quick previews, social media images, and batch workflows where speed matters more than maximum quality. Use 2x Quality (APISR GAN, 8.6MB) for photos you plan to print, portfolio images, or any case where perceptual sharpness is important — the GAN model adds realistic texture detail that the fast model smooths over. Use 4x Enlarge (APISR, 5.0MB) when you need to dramatically increase resolution — turning a 256x256 thumbnail into a usable 1024x1024 image. Note that 4x upscaling works best on images with clear subjects and good original quality. Very noisy or heavily compressed source images may show artifacts at 4x.