squish vs reubah
Browser-based file conversion and optimization compared
squish compresses and converts batches of images in the browser using WebAssembly, without server uploads. reubah handles image conversion and optimization as well as document conversion, and can be run locally or deployed with Docker.
squish: Compress and Convert Images in Your Browser
Squish is a browser-based tool for compressing batches of images and converting between popular formats. It processes files locally with WebAssembly, making it useful for people who want quick optimization without uploading images to a server.
reubah: Convert Documents and Process Images in a Web App
Reubah is a web-based tool for converting common image and document formats, with batch processing and image optimization. It suits people who want a simple interface they can run locally or deploy with Docker.
| squish | reubah | |
|---|---|---|
| Language | TypeScript | HTML |
| License | MIT | MIT |
| Stars | 1.1k | 705 |
| Forks | 114 | 42 |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- squish focuses on image compression and conversion, while reubah also converts common document formats.
- squish processes images locally in the browser; reubah describes isolated processing with no file storage and automatic cleanup.
- squish supports AVIF and JPEG XL alongside JPEG, PNG, and WebP; reubah lists formats including GIF, BMP, and HEIC/HEIF, and optimizes JPG/JPEG images.
- squish is written in TypeScript, while reubah is listed as HTML and requires Go, LibreOffice, and GCC/G++ for local development.
- Both use the MIT license and are not archived. squish has 1.1k stars and 114 forks; reubah has 705 stars and 42 forks.
Choose squish if you…
- need browser-based image compression without uploading files to a server.
- want to adjust quality, preview results, and compare size reductions for image batches.
- work with formats such as AVIF or JPEG XL.
Choose reubah if you…
- need to convert common document formats as well as images.
- want to run a conversion app locally or deploy it with Docker.
- need batch image processing, JPG/JPEG optimization, or a dark mode.
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.