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Massively parallel rigidbody physics simulation on accelerator hardware.

Jupyter Notebook ◇ jax Apache-2.0
★3.2KSTARS
⑂356FORKS
!113ISSUES
🏆#1,594GLOBAL RANK
🔥1DAYS TRENDING
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Star History

Continuous Observations
Interactive star growth chart for google/brax
CSV

Momentum

+81

STARS · LAST 30 DAYS

3

PER DAY

#6

MOST-STARRED Jupyter Notebook

Window7 days30 days90 days
Stars gained+21+81+270
Per day333
Forks gained+2+7+18

brax gained 81 stars in the last 30 days, about 3 a day, and now has 3.2K. It is about 5 years old and has averaged roughly 648 stars a year. It ranks #6 among Jupyter Notebook repositories and #1,594 across all languages on GitHubRepo.

Trending Record

brax has maintained a continuous presence across global trending indexes, peaking at #2155. Below is the 30-day activity profile:

💡 Overview

brax is an open-source project written in Jupyter Notebook: Massively parallel rigidbody physics simulation on accelerator hardware.

Engineered for speed, consistency, and developer ease, it solves common hurdles in jax, physics-simulation, reinforcement-learning. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Jupyter Notebook for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ git clone https://github.com/google/brax.git
cd brax

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Jupyter Notebook environment and standard tooling

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

brax coordinates its core functionality through a modular Jupyter Notebook pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Production System Integration

Embed brax into Jupyter Notebook backend services to handle core application logic.

CI/CD Automated Pipelines

Run automated validation, builds, and integration suites during deployments.

Developer Tooling & Workflows

Accelerate developer onboarding with pre-configured project utilities.

Open Source Extension

Fork and customize internal modules under the repository's open Apache-2.0 license.

🚀 Getting Started

1

Install brax using your package manager: `git clone https://github.com/google/brax.git`

2

Initialize your project workspace or configuration file for brax.

3

Import brax into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `brax --help` to verify successful setup.

👍 Strengths

Active community backing with 3,242 GitHub stars and verified adoption.
Permissive open-source distribution under the Apache-2.0 license.
Built in Jupyter Notebook for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Jupyter Notebook and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

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👥 Who Should Use This

Developers and engineering teams building with Jupyter Notebook, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

google/brax is currently ranked #1,594 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

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Frequently Asked Questions

What does brax do? +

Massively parallel rigidbody physics simulation on accelerator hardware.

What language is brax written in? +

The primary language is Jupyter Notebook. Topics include: jax, physics-simulation, reinforcement-learning, robotics.

Is brax actively maintained? +

Yes, the last recorded push was on Sep 29, 2026 with 113 open issues being tracked.

How many stars does brax have? +

brax has 3,242 stars and 356 forks on GitHub.

How does brax rank among GitHub repositories? +

With 3,242 stars, google/brax is ranked #1,594 globally across all repositories tracked on GitHubRepo and #6 among Jupyter Notebook projects.

What license is brax distributed under? +

The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.

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