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The Beijing NewsUpdated Nov 4 16:35

AgiBot Releases Embodied Foundation Model GO-3 Preview and Metric Unit Worken

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At the 2026 AgiBot Innovation Day, AgiBot released its next-generation embodied foundation model GO-3 Preview, which adopts the self-developed embodied native architecture WRAM to uniformly model understanding, prediction, and action, achieving cross-task generalization and fine manipulation. The model will be fully open-sourced by the end of 2026. AgiBot co-founder, president, and CTO Peng Zhihui also released Worken (effective intelligent work hours), a metric unit defining the value of physical AI, with the formula: number of active robots × autonomous working hours × output efficiency ratio. He also disclosed that in the first half of this year AgiBot shipped 9,700 robots, its 20,000th robot rolled off the line in September, and overall revenue in the first half approached 2 billion yuan.

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AgiBot released an embodied foundation model and a new value metric unit alongside its shipment and revenue data, allowing readers to understand its technical roadmap and commercialization progress.

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Beijing News Shell Finance Report (Reporter Zhang Xiaohui) On October 29, at the 2026 AgiBot Innovation Day, Peng Zhihui, co-founder, president, and CTO of AgiBot, revealed that in the first half of this year, AgiBot shipped 9,700 robots, and in September the 20,000th robot rolled off the production line; overall revenue in the first half of this year was close to 2 billion yuan.

At the event, Peng Zhihui released Worken (effective intelligent work hours), a unit of measurement introduced by AgiBot to define the value of physical AI, used to measure the actual output of robots' autonomous operations. Peng Zhihui introduced that the calculation formula for Worken is Worken (effective intelligent work hours) = effective intelligent work hours = number of active robots × autonomous working hours × output efficiency ratio. According to the introduction, this indicator aims to go beyond the number of robots manufactured and further measure whether robots can autonomously and continuously complete valuable work, as well as how many results they actually create.

In addition, Yao Maoqing, co-founder, co-president, and president of the Embodied Intelligence System of AgiBot, officially released at the event AgiBot's new-generation embodied foundation model GO-3 Preview. The model adopts the self-developed embodied native architecture WRAM (World Reasoning Action Model), and through unified modeling of understanding, prediction, and action, achieves cross-task generalization and fine manipulation. On this basis, GO-3 Preview relies on the Genie Evolver post-training system that coordinates real machines/simulation/world models and the Genie Master embodied agent framework to form a full-chain large-scale learning system covering pre-training, post-training, and post-deployment, driving robots to continuously improve their capabilities in real operations. It is reported that the model will be fully open-sourced by the end of 2026.

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The Beijing News