AI Image Upscaler
Enlarge a photo 2x (or 4x where available) with a small learned model that keeps edges sharper than ordinary resizing, then save it as PNG, JPG or WebP.
- 2x enlargement
- PNG, JPG or WebP
- Zoom to compare detail
Small learned model The upscaler uses FSRCNN, a small learned super-resolution model. In our tests it gave modestly sharper enlargements than standard resizing. It does not invent new detail, so a tiny, blurry photo stays soft when enlarged.
Choose a photo
Before
After
Image Upscaler workspace
Drop your photo here
or choose a file · on a phone you can take a photo or pick one from your gallery
Ready
Working
Preparing your photo…
- Uploading
- Waiting in line
- Processing
- Loading the result
Most photos take under a minute. Larger photos and busy times take longer.
Finished
Compare the result
Drag the divider or use the arrow keys to compare. Zoom in to check fine detail; when zoomed, drag the picture or use the arrow keys on it to move around.
That did not work
What to expect
- Expect a cleaner, slightly sharper enlargement, not a photo with detail that was never captured.
- The enlarged image must stay within the maximum output size; very large photos may be refused for 4x.
- For grainy or scratched photos, clean them up first: the upscaler enlarges defects too.
Your photo is processed on a2z.tools servers. No third-party AI provider receives it, it is not used for training, and the upload and result are deleted automatically 60 minutes after processing finishes.
Related Tools
More tools in the same category
Other Tools
Popular tools from across A2Z
What AI Image Upscaler does
Ordinary resizing makes an enlarged photo look soft, because it only blends neighbouring pixels. A learned upscaler has seen many examples of how edges look at higher resolution and can keep them a little crisper. This page uses a deliberately small model, and it is honest about what that can and cannot do.
Why a small model
The upscaler uses FSRCNN, a compact super-resolution network. We chose it after comparing it with bicubic resizing and several other open models on real photos: among the options whose licences allow commercial use it gave the best measured results, and it is fast enough to run on our servers without long queues. For 4x, the 2x model runs twice, which measured better than a single 4x pass.
In those tests the improvement over standard resizing was real but modest, and on fine fur it was close to none. That is why this page talks about sharper edges rather than new detail. Tools that promise to add detail at large factors are generating content that was not in the photo.
Get the best enlargement
Upscale last. Remove scratches, reduce noise and restore faded colour first, because the upscaler treats every defect as detail worth keeping. Save as PNG if you plan to edit the result further, or WebP or JPG at quality 85 to 95 for sharing.
When to use it
- Making a small scan large enough to print at a bigger size.
- Enlarging an old web-sized family photo for a slideshow or screen.
- The last step after cleaning, denoising and restoring a photo.
How to use it
- Choose or drop the photo you want to enlarge.
- Pick 2x, or 4x if it is offered.
- Choose the file format and quality you want to save.
- Process the photo and zoom to 4x to compare the enlargement with the original.
- Download the enlarged image.
Limitations
- Detail that was never captured cannot be added; faces and text in a tiny photo stay soft.
- Defects such as grain, scratches and JPEG blocks are enlarged too.
- The enlarged image must stay within the maximum output size, so very large photos may be refused.
- Gains are smallest on fine textures such as fur and foliage.
Privacy
Your photo is processed on a2z.tools servers by a model that runs there. It is not sent to any third-party AI provider and is not used for training. The upload and the enlarged result are deleted automatically about 60 minutes after processing finishes, and straight away if processing fails or is cancelled.
Rate this tool
Was this tool useful? Your feedback helps us improve it.
Key facts
- Enlarges by 2x; 4x is offered when enabled and runs the 2x model twice.
- Uses FSRCNN, a small learned super-resolution model released under the Apache-2.0 licence.
- In our tests on photos it measured roughly 0.3 to 1 dB PSNR above bicubic resizing, with little gain on fine fur.
- Does not generate new detail: a small or blurry photo stays soft when enlarged.
- Download as PNG, JPG or WebP, with a quality setting for JPG and WebP.
How to use it
- Choose or drop the photo you want to enlarge.
- Pick 2x, or 4x if it is offered.
- Choose the file format and quality you want to save.
- Process the photo and zoom to 4x to compare the enlargement with the original.
- Download the enlarged image.
Frequently asked questions
Does the upscaler add detail that was not in my photo?
No. It uses a small learned model that predicts how edges look at a higher resolution, which keeps them crisper than ordinary resizing. It does not generate new textures, faces or text, so a tiny or blurry photo will still look soft when enlarged.
Why is 4x enlargement not available?
4x enlargement produces very large images and uses more server time, so the site can switch it off. When it is off, only 2x is offered. You can run 2x again on the result if the output stays within the size limits.
How much sharper is it than normal resizing?
Modestly. In our tests on real photos it measured roughly 0.3 to 1 dB higher PSNR than bicubic resizing, with almost no gain on fine fur. You will notice cleaner edges more than new detail.
Which format should I download the enlargement in?
PNG keeps every pixel exactly and is best if you will edit the image again, but files are large. JPG and WebP are much smaller; a quality of 85 to 95 is a good balance for printing and sharing.
Why was my photo refused for enlarging?
The enlarged image has a maximum size. A photo that is already large can exceed it at 2x or 4x. Crop the photo, or choose 2x instead of 4x.
Why is it called an AI upscaler if the model is small?
Because it uses a trained neural network rather than a fixed resizing formula. It is a small one, chosen for its licence, speed and measured results, and this page describes its effect plainly: sharper enlargements, not invented detail.
Last reviewed: