googlechromelabs/squoosh

Make images smaller using best-in-class codecs, right in the browser.

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Summary Information

Updated 41 minutes ago
Added to GitGenius on September 2nd, 2026
Created on March 7th, 2018
Open Issues & Pull Requests: 261 (+0)
GitHub issues: Enabled
Number of forks: 2,156
Total Stargazers: 25,842 (+1)
Total Subscribers: 253 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 8.1 hours
Mean response time: 145.9 days
90th percentile: 360.2 days
Tracked items: 39

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 87% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 2% of issues opened in the past year have been closed. Three people close 67% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 39
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,164 days
Stale 30+ days: 30
Stale 90+ days: 28

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 1
Events in 7 days: 1

Top labels

  • good first issue (8)
  • help wanted (8)
  • UI (7)
  • feature request (5)
  • codec (2)
  • project infra (1)
  • wontfix (1)

Most active issues this week

Detailed Description

Squoosh is a browser-based image compression tool that applies modern codecs to reduce file sizes directly in the client.

The tool addresses the problem of image optimization by bringing compression capabilities into the browser rather than requiring server-side processing or desktop applications. It leverages best-in-class codecs to achieve effective size reduction while maintaining visual quality. Users can upload images and apply various compression algorithms without uploading their data elsewhere, keeping the process local and private.

Squoosh suits developers and content creators who need quick, accessible image optimization without installing software or running command-line tools. It works well for anyone preparing images for web use, as the browser-based approach eliminates friction in the optimization workflow. The tool is particularly valuable for those concerned with data privacy, since images remain on the user's machine throughout the compression process.

The project maintains active development with regular updates to its compression capabilities and user interface. The codebase shows consistent refinement of the codec implementations and browser integration. Development activity reflects ongoing attention to performance optimization and codec selection, ensuring the tool continues to leverage current best practices in image compression.