YOUR EVERYDAY IMAGE WORKSPACE

Resize Images by Percentage

Scale both dimensions of a whole batch by the same percentage, without cropping or changing proportions.

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01 / PIXELSAAZ

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Drop your images here, or choose a batch from your device.

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EXPORT SETTINGSJPEG · 92% quality

Percentage resizing is useful when files have different original sizes but all need the same proportional reduction. This page starts at 75% of both original dimensions, JPEG output and 92% quality. For example, a 4000 × 2000 photo becomes 3000 × 1500. This is dimension scaling, not a promise to reduce the file's byte size by 25% or 75%.

How it works

  1. Review the selected 75% scale and enter another value from 1 to 100 if needed.
  2. Choose an output format, add the batch and check each ready image's width and height.
  3. Compare detail before downloading; use Apply & re-compress if you change the percentage for an existing batch.

What percentage scaling means

Compare source settings and export behavior
FeatureOriginal width × heightPercentage-scaled dimensions
75% scale4000 × 2000 px3000 × 1500 px
50% scale4000 × 2000 px2000 × 1000 px
Aspect ratioOriginal image proportionsPreserved; no crop or stretched axis
File bytesOriginal encoding and contentDepends on the new dimensions, format and quality

Frequently asked questions

Does 75% mean removing 75% of the width?

No. It means keeping 75% of each original dimension. A 4000px width becomes 3000px. A 25% scale would keep one quarter of the original width and height.

Does 50% scale halve the number of pixels?

Both width and height are halved, so total pixel count becomes one quarter. File bytes do not follow a guaranteed matching ratio.

Can I enlarge images above 100%?

No. The current percentage control is limited to 1–100% to avoid artificial enlargement. Very small results are clamped to at least one pixel per dimension.

Can the same percentage produce different output dimensions?

Yes. The percentage applies to each image's own original width and height. Use maximum width or a platform canvas when matching a specific dimension is more important than a shared scale factor.