How AI Image Upscaler Works
2× and 4× super-resolution upscaling via Swin2SR neural network or high-quality Lanczos — no cloud API, no upload.
Try it free →Step-by-step process
- 1
Model and scale selection
Choose AI mode (Swin2SR — true detail synthesis) or Instant mode (Lanczos + unsharp mask — fast geometric upscale). AI mode synthesises new detail for photos and faces. Then select 2× or 4× scale.
- 2
Tile-based processing
For AI mode, the image is divided into overlapping tiles (512 px each with 32 px overlap). Each tile runs through the neural network independently and the results are assembled with seamless blending at tile boundaries to avoid visible seams.
- 3
Export at full resolution
The upscaled image is exported as PNG preserving full detail without lossy compression. Output resolution is capped at 4096 px per side for 4× mode, or 8192 px for 2× mode.
Frequently asked questions
What is the difference between AI mode and Instant mode?
AI mode uses a neural network (Swin2SR) to synthesise new pixels — it produces sharper, more detailed results especially for faces, text, and fine textures. Instant mode uses Lanczos mathematical upscaling plus an unsharp mask — it is much faster but does not add new detail.
How long does 4× upscaling take?
A 1000 × 1000 px image at 4× takes approximately 30–90 seconds in AI mode on a modern GPU via WebGPU. Larger images take longer proportionally due to the tile count.
Is transparency preserved?
Yes. The upscaler processes the RGB channels and applies the same upscale to the alpha channel separately, preserving transparency in PNG output.
Why does the output look identical to the original?
This can happen if your image was already high resolution — upscaling a sharp 2000 px image to 4000 px adds size but not visible detail. AI upscaling is most impactful on low-resolution or compressed source images.