PhyAgentOS-core vs rosa
The two are close in size: 2.4k stars for PhyAgentOS-core, 1.6k for rosa. Over the days we have tracked them PhyAgentOS-core moved +36.4% and rosa +3%, so PhyAgentOS-core is growing faster right now.
They split the axes: PhyAgentOS-core leads on noise control, 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 small target adapters so the same agent codebase runs across sim and real robots.
- Stars
- 2.4k
- Tracked growth
- +36.4%
- Maturity
- ●●●●●
- Last commit
- 5d ago
- Language
- Python
- License
- MIT
- Cost to run
- Free, self-hosted (local compute)
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-core | 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-wide protocol | ●●●●● System-level context |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Multi-layer safety | ●●●●● None mentioned |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Plugins + YAML configs | ●●●●● Custom agents & prompts |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Fully self-hosted | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Specific policy endpoints | ●●●●● Bring-your-own LLM |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Quick CLI onboarding | ●●●●● Requires LLM & ROS |
Which one to pick
Pick PhyAgentOS-core if…
Safety-first — built-in multi-layer validation (critic → preflight → target-side SafetyGuard) and auditable file protocols make it suitable for real-robot deployment.
- Noise control: Multi-layer safety (5/5 against 1/5)
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 3/5)
What people want from each one
PhyAgentOS/PhyAgentOS-core
Questions people ask
Is PhyAgentOS-core better than rosa?
They split the axes: PhyAgentOS-core leads on noise control, rosa on model freedom. PhyAgentOS-core is worth picking when safety-first — built-in multi-layer validation (critic → preflight → target-side SafetyGuard) and auditable file protocols make it suitable for real-robot deployment.
Which of PhyAgentOS-core and rosa keeps my code private?
PhyAgentOS-core: Fully self-hosted (5/5). rosa: Self-hostable (4/5).
What does each one cost to run?
PhyAgentOS-core: Free, self-hosted (local compute). rosa: Your LLM/API key (your usage costs).
Full profiles: PhyAgentOS/PhyAgentOS-core and nasa-jpl/rosa. Everything else in Robotics & embodied.