Squeez - Bulk Image Optimizer

Project Overview

Squeez is a blazing-fast, 100% offline desktop application for bulk image compression, format conversion, and smart cropping. Built with Tauri v2 and Rust for native performance, it lets you drag in dozens of images at once, optimize them to modern formats, and export - entirely on your machine with no files ever leaving your device.

Why I Built It

Every web project involves a repetitive cycle of compressing and converting images before deployment. Existing tools are either slow, require internet access, or don't support modern formats like AVIF and WebP in bulk. I wanted a lightning-fast native app that handles entire folders in seconds without touching a browser or uploading anything to a server.

Technical Details

• Image Processing (Rust): All compression, resizing, and format conversion logic is written in Rust, giving Squeez native CPU speeds with safe concurrency across multiple images simultaneously.
• UI (React 19 + Vite): The user interface is built with React 19 and bundled with Vite for a snappy, responsive experience with real-time previews and progress feedback.
• Desktop Shell (Tauri v2): Tauri packages the app into a tiny native binary for Windows, macOS, and Linux - no Electron, no bloat, minimal memory footprint.
• Fully Offline: Zero network calls. All processing happens locally, making Squeez safe to use with sensitive or proprietary images.

Key Features

• Lightning fast - Rust-powered native processing speeds for bulk jobs
• 100% offline and privacy-first - no images are ever uploaded to any server
• Bulk import - drag in and process dozens of images at once
• Modern format support - convert to WebP, AVIF, JPEG, and PNG
• Smart cropping - resize and crop images with precise dimension control
• Cross-platform - runs natively on Windows, macOS, and Linux
• Tiny footprint - Tauri v2 produces small, fast native binaries with no Electron overhead
• Open source - MIT licensed and available on GitHub

Download

Squeez is open source and MIT licensed. The latest release (v0.2.0) is available for Windows (.msi), macOS (.dmg), and Linux (.AppImage / .deb) from the GitHub Releases page .