AI Image Upscaler

How to upscale an image

1. 1 Add a small image (JPG, PNG or WebP, up to 1024 px on the long edge). Typical inputs: old photos, game assets, tiny logos, thumbnails.
2. 2 The first use downloads the 63 MB AI model once; your browser keeps it for next time.
3. 3 The image is processed in tiles and you see the tile counter advance. On a graphics-capable browser this takes seconds; on plain CPUs expect a few minutes for large inputs.
4. 4 Compare the 4x result in the preview and download the PNG.

Frequently asked questions

How is this different from simply resizing up?

Classic resizing interpolates pixels, which blurs. Real-ESRGAN is a neural network trained to reconstruct plausible detail: edges stay sharp, textures are rebuilt rather than smeared.

Why is the input limited to 1024 px?

The output has sixteen times the pixel count of the input, and the network's memory use grows with area. 1024 px in means a 4096 px result, which already covers print and wallpaper sizes.

Why is it slow on my device?

Everything runs locally. Browsers with WebGPU use your graphics card and finish quickly; without it the network runs on a single CPU thread. The tile counter shows real progress either way.

Does it help with text or logos?

Yes, sharp-edged graphics upscale especially well. Heavily compressed JPGs also come out cleaner, because the model was trained on exactly that kind of degradation.

Which model is this?

Real-ESRGAN x4plus (BSD-3-Clause license), unmodified, running via onnxruntime in your browser. Your image never leaves your device.