Free AI Image Upscaler

Super-resolution is memory heavy because the model processes every pixel and outputs four times as many. Running that in a browser tab on large inputs can exhaust available memory and crash the tab. Capping the input at 1024 pixels on the longest side keeps memory use reasonable across laptops and phones. If your image is larger, resize it down first, then upscale the smaller version back up.

It uses Swin2SR, a super-resolution model based on the Swin Transformer architecture, converted to ONNX and run through Hugging Face Transformers.js. Specifically it loads the classical 2x super-resolution variant. Swin2SR was designed for image restoration and super-resolution tasks and is released under the permissive Apache 2.0 license, the same license as Transformers.js itself.

No installation is needed. It is a pure web tool that runs in any modern browser. The only thing that downloads is the Swin2SR model itself, which Transformers.js fetches on first use and caches in your browser. There is no extension, no desktop app, and no Python or Node environment to set up.

You can upload common web image formats including JPG, PNG, and WebP. The tool reads the file directly in your browser, runs the upscaler, and exports the enhanced result as a lossless PNG so no additional compression is added on the way out. Animated formats and unusual color profiles may not process cleanly, so a standard JPG or PNG is the safest choice.

Once the model has been downloaded and cached, upscaling runs without an internet connection because everything happens on-device. It also works on mobile browsers that support WebAssembly, though phones have less memory and are slower than a laptop, so stick to smaller images on mobile. For the smoothest experience, load the model once over Wi-Fi and start with modest input sizes.

This tool applies a single 2x pass per run, which doubles the width and height. If you need a larger result you can upscale once, download the PNG, then upscale that result again, though quality gains diminish with each pass and processing time grows. For very large final sizes, a dedicated desktop tool with higher upscale factors will be more efficient.

Swin2SR is trained for super-resolution, so it sharpens edges and adds plausible detail as it enlarges, which reduces the soft look of an upscaled image. It is not a dedicated denoiser or deblur tool, so heavy motion blur or strong compression artifacts may still be visible in the result. Cleaner source images produce noticeably better output than very degraded ones.

For small to medium enlargements, the 2x result is often clean enough for web use and modest prints, since the model preserves edges better than a plain resize. For large format or professional print work you may still prefer a dedicated tool with higher upscale factors and print-specific tuning. Always review the before and after preview at full size before committing the result to print.

The first upscale has to download the Swin2SR model files (about 50MB) from the Hugging Face Hub and initialize the WebAssembly runtime, which takes a moment. After that, the model is cached by your browser and kept in memory for the session, so subsequent upscales skip the download and start almost immediately. Loading the model once over a fast connection makes the whole session smoother.

Yes. The model scales both dimensions by the same 2x factor, so the aspect ratio of your image is preserved exactly. A portrait stays a portrait and a landscape stays a landscape, just at twice the resolution. The before and after preview shows the exact pixel dimensions so you can confirm the output size before downloading.