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Design

Image Compressor

Optimize, compress, and resize images locally in your browser. No data ever leaves your device.

Drag & drop an image or click to browse

Supports PNG, JPEG & WebP • up to 50 MB

PNG JPEG WebP

All processing is executed locally on your machine using standard browser Canvas APIs. No images are uploaded to any server. Your privacy is 100% guaranteed.

How to Use the Image Compressor

  1. Upload — Drag & drop or click to choose a PNG, JPEG or WebP image from your device.
  2. Choose Format & Quality — Select output format (WebP, JPEG, PNG). Adjust quality slider for WebP or JPEG to set the savings-to-clarity balance.
  3. Scale Dimensions (Optional) — Toggle resizer inside the compressor to scale dimensions down if required.
  4. Compare & Download — Review savings metrics, check the side-by-side output preview, and download or copy base64/image instantly.

Key Features

  • Three Export Formats

    Export to WebP (best default), standard JPEG, or lossless PNG with full transparency support.

  • Real-time Visual Preview

    Inspect the compression result side-by-side with original details before saving.

  • Active Savings Progress Bar

    See immediate visual cues representing original vs compressed ratio sizes.

  • Clipboard Copy Support

    Directly copy the optimized PNG image blob or raw Base64 data URL to clipboard.

Frequently Asked Questions

Is my image secure and private?
Yes. The entire workflow occurs directly inside your browser window. No files are uploaded to any server. You can even run the page completely offline.
Which output format is best?
For web applications, WebP offers the best compromise between visual compression and file size. JPEG works universally but lacks transparency. PNG is recommended only for diagrams or assets where crisp, lossless rendering is required.
Why does my PNG become larger when converting?
If you select PNG output, it will apply lossless processing. Since WebP and JPEG use lossy compression, converting them back or forcing PNG output can result in larger file footprints due to how pixel matrices are stored.

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