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GitHub · lz4/lz4↑ +23 today

Ultra-fast data compression tool

Developed in C, lz4 is a lossless data compression algorithm offering speeds of over 500 MB per second per core. Thanks to its architecture, which can reach RAM speed limits on multi-core systems, it provides extremely fast decoding performance.

Updates

  • November 6, 2026: Stars 12,435 → 12,438, latest release v1.11.0 (November 4, 2026).

What you get

  • offers a compression speed of over 500 megabytes per second per core
  • includes the lz4_hc version for an extra-high compression ratio
  • is open source and under a BSD license

Installation

Compilation and Installation
make
make install     # this command may require root permissions

If you don't write code

Paste this into your AI agent (Claude Code · Codex · Antigravity)

I want to quickly compress data with this tool. Help me complete the installation by running the provided make and make install commands.

Repository: https://github.com/lz4/lz4. Follow the official instructions in the README of this repository for setup and execution.

Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.

Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.

Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.

Related dictionary terms

Who it is forYou are working on projects that require data compression and decompression operations at very high speeds.

Links

TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-11-06: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.