How to review duplicate photos without losing the best copy
Two similar photos are not necessarily interchangeable. The best frame can differ in expression, sharpness, crop or the edit you intended to keep.
By Luke Kevin McLaughlin, IndepApps · Updated
Separate three decisions
Exact duplicates, near-duplicates and unwanted photos are different categories. Exact files can often be checked mechanically. Near-duplicates need visual judgment. A blurred photo can still be the only record of an important moment, so a blur score should not decide for you.
Before cleaning a large library, confirm that you have a backup and understand whether deletion syncs to other devices. Start with a small set of photos whose history you know.
Try the built-in option first
Apple Photos has a Duplicates collection with a merge operation. Read Apple’s duplicate-merging instructions for the behavior of your macOS version. If that resolves your problem, an additional tool may be unnecessary.
Sift adds perceptual grouping, sharpness analysis and a review workflow. Its direct edition requires macOS 14 or later on Apple silicon or Intel. Its suggestions still need your judgment.
Check each candidate group
- Compare full-size images, not only thumbnails.
- Check focus, expression, framing and intentional background blur.
- Inspect resolution, date, location and any edits you want to retain.
- Keep both files when they serve different purposes, such as an original and a finished edit.
- Review the selected removals again before confirming.
For a first test, include an exact copy, an edited version, two similar frames and a unique image. Record which groups the tool suggests. Do not turn a suggested group into an automatic deletion rule.
Confirm recovery before scaling up
Sift documents removals through Recently Deleted. Test recovery with a disposable photo first and follow the recovery period shown by Photos. Do not permanently empty that collection just to prove a cleanup worked.
Use the check sheet to record the expected groups and your observed results. This is a review protocol, not a measured accuracy claim. See Sift versus Photos duplicate merging for the decision between those workflows.