Zero-shot cross-embodimentBrowse 284 families
Zero-shot cross-embodiment
Can the model plan, use tools, and finish a multi-step task?
Version / measure
- Domain
- Agents
- Ranked models
- 2
- Reported values
- 4
- Reports
- 1 · lab
- Direction
- Higher is better
- Status
- Version not specified
Rankings
Best reported score per model across effort settings
| # | Model | Best setting | Score |
|---|---|---|---|
| 1 | Qwen-RobotManipQwen | reportedcost n/a2 values · Jun 15 · source | 42.9% |
| 2 | π₀.₅Physical Intelligence | reportedcost n/a2 values · Jun 15 · source | 24.6% |
Effort curve
Score vs. reported cost. Lines connect complete sweeps only.
No cost-linked effort sweep for this version.
Definition and comparison boundarypublic methodology
Can the model plan, use tools, and finish a multi-step task?
Agentic execution across tools, environments, or long-running workflows. Higher is better. The value is the percentage reported in this lab's table.
Harness, tools, prompts, attempt count, and benchmark version can materially change the result. Compare within one reporting context.
Models are trained on AgileX ALOHA data and evaluated on unseen robot embodiments; joint and camera-frame EEF representations remain separate configurations.
Method / source ↗