Enhance Photo Quality — Pro, on our server
Know which of the three problems your photo actually has. Too few pixels shows as visible blockiness when you zoom; the enhancer’s clean-up pass is built for precisely this. Compression damage shows as smudged flat areas and halos around edges — also squarely in the model’s wheelhouse. Softness from a slightly missed focus recovers well; hard motion blur does not, and a page that promised otherwise would be selling you a run that ends in disappointment. Blurry faces are their own case: the photo restorer runs a model trained specifically on faces and checks every result against the original person.
Garbage in still limits gold out. The single cheapest improvement is feeding the model the best copy that exists: the original camera export, not the copy a chat app recompressed. If the photo lives on someone else’s phone, ask for it “as a file” or in “original quality”. The enhancer cleans compression damage well, but information that survived is always better than information reconstructed.
Order matters when quality work is a chain. Crop first, on your device, so the pixel budget goes to the image you keep. Restore faces before enhancing, if faces are the point. Enhance last, because the model faithfully magnifies whatever it is given — flaws included. Every step before this page runs on your own device; only the enhancement itself involves an upload, encrypted, deleted on completion.
Judge the result the way a printer would. View at 100%, look at the highest-frequency detail you care about — eyelashes, serif text, fabric — and compare against the source. The meter costs of a run (one general cloud run, one of the general allowance) are shown before you commit, and a refused or failed run charges neither.
The tool is also described on the AI image enhancer page.