Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
⚡ Executive Summary & Quick Facts
Authoritative Sourcephysicsnemo is physicsnemo is an open-source project written in Python: Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), NVIDIA/physicsnemo has accumulated 3,314 GitHub stars and 806 forks. It is written in Python, licensed under Apache-2.0, and ranks #3,684 globally. It is actively maintained with the latest commit recorded on Oct 6, 2026.”
| Repository | NVIDIA/physicsnemo ↗ |
|---|---|
| Primary Category | deep learning |
| Language & Stack | Python |
| Software License | Apache-2.0 |
| Community Traction | ★ 3.3K stars · ⑂ 806 forks · #3,684 globally |
| Maintenance | ● Active (Last commit: Oct 6, 2026) · 100 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 92/100 · Grade AYes, physicsnemo is actively maintained. Continuous telemetry recorded the last code commit on Oct 6, 2026 (29 days ago). Supported by 3,314 stars and 806 community forks, this repository holds a calculated health index of 92/100, reflecting regular maintenance (29 days ago) and healthy issue cadence.
Star History
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+83
STARS · LAST 30 DAYS
3
PER DAY
#550
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +83 | +270 |
| Per day | 1 | 3 | 3 |
| Forks gained | +0 | +16 | +40 |
physicsnemo gained 83 stars in the last 30 days, about 3 a day, and now has 3.3K. It is about 4 years old and has averaged roughly 829 stars a year. It ranks #550 among Python repositories and #3,684 across all languages on GitHubRepo.
Trending Record
27
DAYS ON TRENDING
#4170
BEST RANK
Oct 6, 2026
FIRST APPEARANCE
Active
STATUS TODAY
physicsnemo has maintained a continuous presence across global trending indexes, peaking at #4170. Below is the 30-day activity profile:
💡 Overview
physicsnemo is an open-source project written in Python: Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods.
Engineered for speed, consistency, and developer ease, it solves common hurdles in deep-learning, machine-learning, nvidia-gpu. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install physicsnemo⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
physicsnemo coordinates its core functionality through a modular Python 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 physicsnemo into Python 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
Install physicsnemo using your package manager: `pip install physicsnemo`
Initialize your project workspace or configuration file for physicsnemo.
Import physicsnemo into your codebase or invoke it directly from your terminal.
Execute your test suite or run `physicsnemo --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
NVIDIA/physicsnemo is currently ranked #3,684 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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| #3,684 | NVIDIA/physicsnemo This Project | Python | ★ 3.3K | |
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Frequently Asked Questions
What does physicsnemo do? +
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
Is physicsnemo actively maintained in 2026? +
Yes, physicsnemo is actively maintained. The latest code push was recorded on Oct 6, 2026 (29 days ago). It holds a calculated Maintenance Health Score of 92/100 (A rating) with 3,314 stars and 100 open issues.
What language is physicsnemo written in? +
The primary language is Python. Topics include: deep-learning, machine-learning, nvidia-gpu, nvidia-warp, physics.
How many stars does physicsnemo have? +
physicsnemo has 3,314 stars and 806 forks on GitHub.
How does physicsnemo rank among GitHub repositories? +
With 3,314 stars, NVIDIA/physicsnemo is ranked #3,684 globally across all repositories tracked on GitHubRepo and #550 among Python projects.
What license is physicsnemo distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
