cap-x vs PhyAgentOS
PhyAgentOS is much bigger: 2.1k stars against 769. Over the days we have tracked them cap-x moved +17.2% and PhyAgentOS +30.4%, so PhyAgentOS is growing faster right now.
They split the axes: cap-x leads on model freedom, PhyAgentOS on context depth and noise control and customization.
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 an end-to-end, robotics-focused framework that benchmarks and improves Code-as-Policy agents with interactive robot gym environments, multi-tier benchmarks, a training-free agent, and RL fine-tuning tools bundled together.
- Stars
- 769
- Tracked growth
- +17.2%
- Maturity
- ●●●●●
- Last commit
- 99d ago
- Language
- Python
- License
- MIT
- Cost to run
- Your API key or local GPU
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
- +30.4%
- Maturity
- ●●●●●
- Last commit
- 4h ago
- Language
- Python
- License
- MIT
- Cost to run
- Free, self-hosted; optional external services
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 | cap-x | PhyAgentOS |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Diff only | ●●●●● Workspace-wide context |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● None mentioned | ●●●●● Multi-layer safety |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Config file | ●●●●● Plugins & configs |
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. | ●●●●● Bring-your-own-key | ●●●●● Specific adapters |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Config + API key | ●●●●● Easy CLI start |
Which one to pick
Pick cap-x if…
Robotics-focused — pick CaP-X when you need a comprehensive, open-source benchmark and toolkit for evaluating and improving code-generating agents on robot manipulation tasks with simulation environments and RL support.
- Model freedom: Bring-your-own-key (5/5 against 3/5)
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)
What people want from each one
capgym/cap-x
PhyAgentOS-Dev/PhyAgentOS
Questions people ask
Is cap-x better than PhyAgentOS?
They split the axes: cap-x leads on model freedom, PhyAgentOS on context depth and noise control and customization. cap-x is worth picking when robotics-focused — pick CaP-X when you need a comprehensive, open-source benchmark and toolkit for evaluating and improving code-generating agents on robot manipulation tasks with simulation environments and RL support.
Which of cap-x and PhyAgentOS keeps my code private?
cap-x: Self-hostable (4/5). PhyAgentOS: Self-hostable (4/5).
What does each one cost to run?
cap-x: Your API key or local GPU. PhyAgentOS: Free, self-hosted; optional external services.
Full profiles: capgym/cap-x and PhyAgentOS-Dev/PhyAgentOS. Everything else in Robotics & embodied.