AGIBOT Unveils Worken Framework to Quantify Robots’ Useful Output

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AGIBOT Unveils Worken Framework to Quantify Robots’ Useful Output

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AGIBOT introduced Worken, a proposed framework for measuring how much productive work robots perform once deployed, at AGIBOT Innovation Day 2026 in Shanghai on October 29, 2026. The company also used the event to unveil its AHA3 integrated hardware platform, debut the GO-3 Preview embodied foundation model and the WITA-Omni interaction model, and formally launch the G2 Max industrial robot and Link-U OS 1.0. The Wor

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ken Framework The name combines the words “Work” and “Token,” and AGIBOT describes the concept as “Effective Intelligent Work Hours.” Under the proposal, Worken equals the number of active robots multiplied by autonomous working hours and by an output efficiency ratio. The first factor counts robots that are actively performing tasks in real-world environments, not units that have merely been manufactured or sit in i

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nventory. The second measures hours spent working autonomously rather than total powered-on time. The third scores output against a reference benchmark for a defined task, such as the amount of acceptable work a human worker completes under established operating standards. Peng Zhihui, co-founder, president and CTO of AGIBOT, presented the framework as an answer to a measurement question he said the industry must add

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ress as robots begin working in factories, warehouses and service environments. “We want to move beyond measuring how many robots are built or delivered and begin measuring how effectively they can perform useful work, autonomously and consistently, in the real world,” he said in the company’s announcement . AGIBOT said it views Worken as an evolving framework that will be refined through real-world deployments and o

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perational data, and that it hopes the measure can eventually become a broadly applicable reference for measuring the productive value of physical AI. The company also presents the measure as a way to examine the economics of robotics: while hardware depreciates over time, improvements in software and AI models may let the same machine perform more useful work during its operating life, so weighing output against tot

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al lifecycle costs could help businesses evaluate the longer-term value of a deployment. Also released at the event was the “2026 Embodied Intelligence Industry Innovation Report,” a study of the industry’s progress toward real-world deployment jointly compiled by China Economic Information Service and the Shanghai Industrial Innovation Center of the China Academy of Information and Communications Technology. Worken

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and AGIBOT’s deployment examples appear in the report’s industry analysis. AHA3 Hardware and New Physical AI Models AHA3, short for AGIBOT Humanoid Architecture, is the company’s third-generation humanoid hardware architecture and, in AGIBOT’s description, its first commercial “Three Intelligences in One” platform, combining the hardware foundations for locomotion, interaction and task execution intelligence in a sin

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