Bulk Image Resizer

Resize many photos to the same width at once and download them as a ZIP — free, entirely on your device.

How to resize many images at once

Drop several photos into the box above, type the target width, and click resize — every image is scaled to that width proportionally (each keeping its own original aspect ratio) and packaged into a ZIP file.

For example, a batch of blog post images at inconsistent original sizes can all be normalized to an 800px width here in one pass, ready to drop into a CMS.

Resizing a whole folder at once

Resizing images one at a time becomes tedious fast once you're past three or four files — a product catalog, an event photo set, or a batch of screenshots for documentation. This tool applies the exact same target size to every file you drop in, processing the whole batch in one pass instead of repeating the same steps over and over.

Because every file gets identical treatment, this works best when your batch should all end up at the same final size — if some images need different treatment than others, splitting them into separate batches, or using the single-image Resize tool for the outliers, will give you more control than trying to force one setting to fit every file.

How the whole batch processes at once

Every file you drop in gets resized using the same Canvas API process the single-image tool uses, just looped across your whole batch automatically — there's no meaningful limit on how many files you can process in one go beyond your device's own memory and processing speed.

Because everything runs locally, a large batch of personal or work photos never needs to be uploaded anywhere just to get resized — each file is read, resized and made available for download entirely on your own device.

Checking results across a mixed batch

Since the same target dimensions get applied to every file, it's worth glancing through the results if your batch mixed portrait and landscape photos together — the same width and height setting will crop or letterbox each orientation differently, so a batch with a consistent orientation to begin with tends to give the most uniform-looking set of results.

Frequently asked questions