PhyAgentOS vs rosa
The two are close in size: 2.4k stars for PhyAgentOS, 1.6k for rosa. Over the days we have tracked them PhyAgentOS moved +146.7% and rosa +3%, so PhyAgentOS is growing faster right now.
They split the axes: PhyAgentOS leads on noise control and setup ease, rosa on model freedom.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Decouples cognition from physical hardware with a session-centered runtime and adapter/bridge architecture that lets the same sessions run unchanged across simulation and real robots while enforcing multi-layer safety and auditable execution.
- Stars
- 2.4k
- Tracked growth
- +146.7%
- Maturity
- ●●●●●
- Last commit
- 5d ago
- Language
- Python
- License
- MIT
- Cost to run
- Free, self-hosted
Integrates LangChain LLMs with live ROS1/ROS2 systems to let developers inspect, diagnose, and operate robots via natural language.
- Stars
- 1.6k
- Tracked growth
- +3%
- Maturity
- ●●●●●
- Last commit
- 183d ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Your LLM/API key (your usage costs)
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | PhyAgentOS | rosa |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Workspace & protocols | ●●●●● System-level context |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Multi-layer validation | ●●●●● None mentioned |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Extensive configs & plugins | ●●●●● Custom agents & prompts |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Self-hostable | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● OpenPI-focused | ●●●●● Bring-your-own LLM |
Setup ease What it takes to get a first useful run out of it. | ●●●●● 5-minute quickstart | ●●●●● Requires LLM & ROS |
Which one to pick
Pick PhyAgentOS if…
Hardware-agnostic — one codebase to run identical sessions across sim and real robots with small target adapters, built-in safety layers, and auditable state/action logs.
- Noise control: Multi-layer validation (4/5 against 1/5)
- Setup ease: 5-minute quickstart (5/5 against 3/5)
Pick rosa if…
Robot-focused — use ROSA when you need a customizable, LangChain-based agent that directly interacts with ROS1/ROS2 robot state using your preferred LLM.
- Model freedom: Bring-your-own LLM (5/5 against 2/5)
What people want from each one
PhyAgentOS/PhyAgentOS
Questions people ask
Is PhyAgentOS better than rosa?
They split the axes: PhyAgentOS leads on noise control and setup ease, rosa on model freedom. PhyAgentOS is worth picking when hardware-agnostic — one codebase to run identical sessions across sim and real robots with small target adapters, built-in safety layers, and auditable state/action logs.
Which of PhyAgentOS and rosa keeps my code private?
PhyAgentOS: Self-hostable (4/5). rosa: Self-hostable (4/5).
What does each one cost to run?
PhyAgentOS: Free, self-hosted. rosa: Your LLM/API key (your usage costs).
Full profiles: PhyAgentOS/PhyAgentOS and nasa-jpl/rosa. Everything else in Robotics & embodied.