Zero-shot cross-embodimentBrowse 296

Zero-shot cross-embodiment

Can the model plan, use tools, and finish a multi-step task?

Version not specifiedExact reported variant
Agents2 ranked models4 reported values1 reportsHigher is better

Top rankings

One row per model, using its best reported score across effort settings.

2
RankModelBest scoreBest reported setting
1Qwen-RobotManipQwen42.9%Reported configurationQwen report2 values · 1 reportJun 15, 2026 · source
2π₀.₅Physical Intelligence24.6%Reported configurationQwen report2 values · 1 reportJun 15, 2026 · source

Effort curve

Every sourced cost-linked effort value for this exact version. Lines connect complete sweeps only.

0
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