PhyAgentOS vs rai
PhyAgentOS is much bigger: 2.1k stars against 583. Over the days we have tracked them PhyAgentOS moved +34% and rai +5%, so PhyAgentOS is growing faster right now.
They split the axes: PhyAgentOS leads on context depth and noise control and customization and setup ease, rai 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
Provides a session-centered runtime that decouples cognition from physical targets so the same agent workflows run across simulation and real hardware via small target adapters.
- Stars
- 2.1k
- Tracked growth
- +34%
- Maturity
- ●●●●●
- Last commit
- 2h ago
- Language
- Python
- License
- MIT
- Cost to run
- Free, self-hosted; optional external services
A ROS2-native, vendor-agnostic embodied agent framework focused on integrating multi-modal and agentic capabilities directly on robots.
- Stars
- 583
- Tracked growth
- +5%
- Maturity
- ●●●●●
- Last commit
- 9m ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Open-source, self-hosted; model API costs may apply
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 | rai |
|---|---|---|
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 context | ●●●●● Diff only |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Multi-layer safety | ●●●●● None |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Plugins & configs | ●●●●● Config file |
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. | ●●●●● Specific adapters | ●●●●● Bring-your-own-key |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Easy CLI start | ●●●●● Manual setup |
Which one to pick
Pick PhyAgentOS if…
Hardware-agnostic — pick PhyAgentOS when you need a self-hostable, auditable runtime that runs identical sessions across sim and real targets with strict multi-layer safety.
- Context depth: Workspace-wide context (4/5 against 1/5)
- Noise control: Multi-layer safety (5/5 against 1/5)
- Customization: Plugins & configs (5/5 against 3/5)
- Setup ease: Easy CLI start (4/5 against 2/5)
Pick rai if…
Robot-first — pick RAI when you need a ROS2-integrated, extensible framework to add multi-agent, multi-modal AI capabilities to physical robots.
- Model freedom: Bring-your-own-key (5/5 against 3/5)
What people want from each one
PhyAgentOS-Dev/PhyAgentOS
RobotecAI/rai
Questions people ask
Is PhyAgentOS better than rai?
They split the axes: PhyAgentOS leads on context depth and noise control and customization and setup ease, rai on model freedom. PhyAgentOS is worth picking when hardware-agnostic — pick PhyAgentOS when you need a self-hostable, auditable runtime that runs identical sessions across sim and real targets with strict multi-layer safety.
Which of PhyAgentOS and rai keeps my code private?
PhyAgentOS: Self-hostable (4/5). rai: Self-hostable (4/5).
What does each one cost to run?
PhyAgentOS: Free, self-hosted; optional external services. rai: Open-source, self-hosted; model API costs may apply.
Full profiles: PhyAgentOS-Dev/PhyAgentOS and RobotecAI/rai. Everything else in Robotics & embodied.