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BlazeDiff is a high-performance diff ecosystem. Originally built in JavaScript as a pixel-perfect image comparison library that's 1.5x faster than pixelmatch. Now, BlazeDiff has evolved into a comprehensive suite of blazing-fast diff tools including image comparison, image diff analysis deterministically + agent-in-the-loop verdict, object diffing, perceptual quality metrics, framework-agnostic UI renderers, and React components for visualizing differences.

• @blazediff/core-native - The fastest single-threaded image diff in the world (Rust + SIMD, 3-4x faster than odiff on 4K images)
• @blazediff/core-wasm - WebAssembly build of the same Rust algorithm (wasm32 + v128 SIMD, ~58% faster than pixelmatch). For browsers, edge runtimes, and any wasm host.
• @blazediff/core - Pixel-perfect image comparison (1.5x faster than pixelmatch)
• @blazediff/object - High-performance object diffing with detailed change tracking
• @blazediff/ssim - SSIM, MS-SSIM, and Hitchhiker's SSIM for perceptual quality assessment
• @blazediff/gmsd - Gradient Magnitude Similarity Deviation metric

• blazediff - The Rust crate powering @blazediff/core-native: block-based image diffing with SIMD (source)
• blazediff-png - From-scratch PNG codec in Rust, single-threaded and SIMD-first, with byte-exact decode parity to libspng and faster on every fixture (source)

• blazediff - Python bindings (via maturin) for the Rust diff core (source)

• @blazediff/cli - JS CLI with multiple algorithms (diff, GMSD, SSIM, MS-SSIM, Hitchhiker's SSIM)
• @blazediff/agent - Agentic visual regression. Auto-discovers routes, captures deterministic screenshots, and hands ambiguous diffs back to your coding agent (Claude Code, Cursor, Codex) to judge.

• @blazediff/react - React components for diff visualization
• @blazediff/ui - Headless engine + framework-agnostic renderer for image-diff UIs

• Documentation - Complete API reference and guides
• Examples - Interactive demos and code samples
• Benchmarks - Performance comparisons and metrics

BlazeDiff packages are dual-published. Install from whichever registry fits your runtime.

# Node / Bun via npm
npm install @blazediff/core
bun i @blazediff/core

# Deno / Bun via JSR
deno add jsr:@blazediff/core
bunx jsr add @blazediff/core

# Rust via Cargo
cargo add blazediff

# Python via pip
pip install blazediff

Every package above is available on both registries except the test-runner adapters (@blazediff/vitest, @blazediff/jest, @blazediff/bun) and the UI libraries (@blazediff/ui, @blazediff/react), which remain NPM-only - the adapters augment each runner's Matchers types and the UI packages have browser-DOM and React type surfaces that JSR's publish-time slow-types check doesn't allow. Native-binary sub-packages under @blazediff/core-native-* are also NPM-only; Deno consumers resolve them transparently via npm: specifiers declared inside @blazediff/core-native.

BlazeDiff delivers significant performance improvements across all components:

• Native (Rust): 3-4x faster than odiff, 8x faster than pixelmatch on 4K images
• WASM: ~58% faster than pixelmatch, up to ~5x on 4K (browser, edge, any wasm host)
• Image Pixel-by-Pixel (JS): ~50% faster than pixelmatch (up to 88% on identical images)
• SSIM: ~25% faster than ssim.js, ~70% faster with Hitchhiker's SSIM
• Object Diff: ~55% faster than microdiff (up to 96% on identical arrays)

View Detailed Benchmarks - Complete performance data, test methodology, and hardware specifications.

Contributions are welcome! Please see the Contributing Guide for details.

MIT License - see LICENSE file for details.

The @blazediff/ssim and @blazediff/gmsd packages implement perceptual quality metrics based on published research. See the licenses folder for detailed attribution and licensing information:

• SSIM - Zhou Wang et al., IEEE 2004
• MS-SSIM - Zhou Wang et al., Asilomar 2003
• Hitchhiker's SSIM - Venkataramanan et al., IEEE Access 2021

• Image diffing built on the excellent pixelmatch algorithm
• SSIM and MS-SSIM based on groundbreaking research by Zhou Wang, Alan C. Bovik, and colleagues
• Hitchhiker's SSIM based on research by Venkataramanan, Wu, Bovik, Katsavounidis, and Shahid
• GMSD based on research by Xue, Zhang, Mou, and Bovik

Built for high-performance difference detection across images and data structures