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AI
Jul 8, 2026 · 2 min read

A new leader in background removal tools has arrived — meet Cut It Out

Affmarketingworld
Patric Mirgeschiss
Editor, Affmarketingworld
Cut It Out AI background removal tool

A new free tool called Cut It Out has been released, and it’s quickly being called one of the best background removal options available right now.

The service runs on advanced AI models and handles the job with impressive precision, correctly isolating even genuinely difficult subjects — in one test, it managed to cleanly separate a spider web, a pattern that typically trips up most background removal tools due to its thin, overlapping strands.

Under the hood, Cut It Out uses the U2-Net deep learning model, running via WebAssembly directly in the browser, which means images are processed locally and never get uploaded to a server. This also gives the tool a strong privacy advantage over cloud-based alternatives.

Running U2-Net entirely client-side via WebAssembly is the detail that separates this from the usual background removal tool. Most competitors process images on a remote server, which means uploading full-resolution files to someone else’s infrastructure and trusting them not to retain or misuse that data.

How to use it

The tool can be used two ways: run it locally by grabbing the source code from GitHub, or use it instantly in the browser without installing anything.

Unlike many competing services, Cut It Out does not compress or downscale images during processing, so the final result keeps its original resolution and quality. Best of all, the tool is completely free, requires no account or sign-up, and comes with no usage limits, watermarks, or restrictions of any kind — a rare combination for a tool of this quality.

For affiliates, designers, or content teams handling product photography or creative assets at volume, a free, unlimited, full-resolution tool with no watermark removes a recurring cost line that most workflows currently route through paid APIs.

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The spider web test is a genuinely useful benchmark for this category — thin, overlapping, semi-transparent structures are exactly where most segmentation models fall apart, so a clean result there says more about real-world reliability than a demo on a simple portrait would.

Patric Mirgeschiss
Reviewed by
Patric Mirgeschiss
Editor · Affmarketingworld
Published Jul 8, 2026
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