GitHub - RLinf/RPent: RPent: Agentic Infrastructure for the Physical World

Compare RPent with reference methods on LIBERO, LIBERO-PRO, RoboCasa365 Target50, and RoboTwin C2R. Rankings apply to the methods and evaluation coverage shown; see the Leaderboard for suite results and model configurations.

Codex / GPT-6 Astra / low / reasoning: 92.63% Overall (741/800) across all eight LIBERO-PRO suites. See the suite results and memory-batch explanation, including the separately frozen Long and Spatial/Object/Goal memory batches.

RPent is built for four kinds of users:

git clone https://github.com/RLinf/RPent rpent && cd rpent pip install -e ".[libero-pro]" # Recommended default (LIBERO-PRO) # Other environment configurations: pip install -e ".[robocasa]" # RoboCasa pip install -e ".[robotwin]" # RoboTwin pip install -e ".[franka]" # Franka and dual Franka .[libero-pro] is the recommended default. See the installation docs for other environments.

For RoboCasa setup, task memory, and the Target50 protocol, see the RoboCasa guide.