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SPECIFICTION
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Background Gone

github.com

Free plan WebSelf-hosted
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Spec score 8.0 #45 of 94 in AI Background Removers

Spec sheet

Purpose
Background Gone is a free AI tool for removing image backgrounds in a browser.Read 11 Oct 2026 · github.com
Free plan
YesRead 22 Sep 2026 · github.com
AI engines
It offers three engines: ISNet Precision, ISNet Lightweight, and RMBG-1.4.Read 11 Oct 2026 · github.com
Background options
Results can use a transparent, solid color, gradient, or custom image background.Read 11 Oct 2026 · github.com
Batch processing
It can process up to 20 images at once and download the results as a ZIP.Read 11 Oct 2026 · github.com
Browser requirements
The README lists Chrome 91+, Edge 91+, Firefox 89+, and Safari 16.4+; engines fall back to WebAssembly when WebGPU is unavailable.Read 11 Oct 2026 · github.com
Export
The documented download result is a lossless transparent PNG with optional background replacement.Read 11 Oct 2026 · github.com
Export formats
PNGRead 22 Sep 2026 · github.com
Input methods
Images can be added by drag and drop, click, or clipboard paste; listed formats include JPEG, PNG, WebP, and HEIC.Read 11 Oct 2026 · github.com
Integrations and security
The README describes client-side processing and a first-load model download from Hugging Face CDN, and does not list third-party app integrations or security certifications.Read 11 Oct 2026 · github.com
Local processing
Image inference runs locally in the browser using WebAssembly or WebGPU, and the README says images do not leave the device.Read 11 Oct 2026 · github.com
No account required
The README says the tool requires no signup or cloud dependency.Read 11 Oct 2026 · github.com
Offline use
The tool works offline after the first model download, which is cached in IndexedDB.Read 11 Oct 2026 · github.com
Replacement backgrounds
YesRead 22 Sep 2026 · github.com
Self-hosting
The project is designed to be self-hosted and requires no backend, database, or API keys.Read 11 Oct 2026 · github.com

Plans and prices

Free forever Free Up to 20 images per batch · no watermarks Read 11 Oct 2026 · github.com

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