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A collection of developer tools in one place in your browser

MacPaw Gemini 2
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SoftOrbits Duplicate Photo Finder
Duplicate and blurry photos, found locally. Nothing else.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | devtoolsadvanced.com | skimrr.com |
| Pricing | — | |
| Platforms | — | |
| Company | — | Startup from France · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of DevTools Advanced yet.
Skimrr finds duplicate photos and blurry shots in a folder — entirely on your computer. What it does Duplicates: exact copies matched by hash, plus near-duplicates (cropped, recompressed, lightly edited) matched by what the picture actually looks like. Similarity threshold adjustable live. Blur:...
What each product offers, as listed by its team.


No features have been listed yet.
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
No analysis of Skimrr yet.
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How to Delete Duplicate & Blurry Photos FAST (2026)
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing DevTools Advanced and Skimrr.
Skimrr's answer:
It grew out of a very ordinary problem: the photo folder nobody opens, years of imports nobody sorted, full of duplicates and near-misses nobody's confident enough to delete by hand. (There's a longer writeup on this: https://medium.com/@admin_53263/the-folder-nobody-opens-1b897eb33eed)
Skimrr's answer:
Most duplicate-finder tools either ask you to upload photos to a cloud service, rely purely on hashing (missing edited near-duplicates or flagging unrelated similar shots), or use a one-size-fits-all blur cutoff that misfires constantly. Skimrr keeps everything on your machine, adds a local vision-model sanity check most competitors skip entirely, and never deletes anything without a review grid and an undo-able trash.
Skimrr's answer:
Every proposed duplicate group is checked by an on-device vision model before it's shown, not just matched by hash, so near-duplicates (cropped, recompressed, lightly edited) get caught without a flood of false positives. The blur score is calibrated per-folder rather than using a fixed threshold, so a soft-focus portrait or a busy, detailed scene doesn't get misjudged. Everything runs 100% locally in Rust, with no account, no cloud, no telemetry, and nothing is ever deleted outright: files go to a reversible local trash first.
Skimrr's answer:
Tauri 2 and Rust for the desktop app and the core scanning, hashing, and clustering engine; a local MobileNetV2 ONNX model run through Candle (a pure-Rust ML framework, keeping the whole app free of Python or native ML dependencies) for duplicate verification; and React with TypeScript and i18next for the six-language UI.
Skimrr's answer:
People sitting on large personal photo libraries built up over years, with multiple phones, cameras, and import sessions, who want to reclaim disk space without handing their personal photos to a cloud service. Photography enthusiasts, people who regularly import from SD cards, and anyone privacy-conscious about where their photos go.
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