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Hao AI Lab releases the ORA (Open Robot-Use Agents) open-source framework, powered by DeepSeek-V4.1-Flash, which operates robots zero-shot from visual input without VLA and can compete with frontier model agents. ORA achieves 69.2% on RoboTwin and 81.4% on LIBERO-Pro; by comparison, RPent achieves 62.4%/58.4% on RoboTwin (GPT-5.5/Opus-4.7) and 82.4% on LIBERO-Pro (Opus-4.7). It works similarly to a coding agent, completing the loop through prompts, perception and action tools, and context management; the same framework can run ARX X5, ALOHA, and Franka, with a model cost of about $0.30–0.35 per solved case. In preliminary real-robot tests, DeepSeek-V4.1-Flash used a low-cost robotic arm, a fixed RGB-D camera, and a wrist camera to pull open a drawer handle and put candy into a box.
Hao AI Lab releases the ORA (Open Robot-Use Agents) open-source framework, powered by DeepSeek-V4.1-Flash, which operates robots zero-shot from visual input without VLA and can compete with frontier model agents. ORA achieves 69.2% on RoboTwin and 81.4% on LIBERO-Pro; by comparison, RPent achieves 62.4%/58.4% on RoboTwin (GPT-5.5/Opus-4.7) and 82.4% on LIBERO-Pro (Opus-4.7). It works similarly to a coding agent, completing the loop through prompts, perception and action tools, and context manage
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