Key on-screen metrics reported during and after the stream included:
Agibot's central claim was that these robots were operating in a real, active mass-production factory — not a staged lab environment — making the livestream a direct rebuttal to Figure AI's earlier controlled-lab broadcast .
The two companies represent fundamentally different design philosophies for humanoid robots. Agibot's G2 is a purpose-built industrial wheeled robot optimized for factory throughput, while Figure AI's Figure 03 is a more general-purpose bipedal walking platform designed for eventual home use .
Key difference: Agibot stressed that its livestream came from a real high-volume manufacturing line already in production, while Figure AI's demonstrations — though technically impressive with bipedal locomotion and the Helix AI model — were conducted in lab or pilot settings . Figure AI's Figure 03 is a bipedal platform with home-use ambitions, whereas the G2 is a wheeled industrial robot optimized for factory throughput
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The G2 uses 7-DoF force-controlled arms with integrated force-torque sensing, allowing it to handle delicate electronics components without damage . It is designed for automotive-grade industrial standards and intended for 24/7 continuous factory operation
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Agibot's manufacturing ramp has been aggressive:
"Deployment Year One" (2026): Agibot's leadership explicitly framed 2026 as the year the company moves from lab demonstrations to large-scale commercial deployment of embodied AI across multiple manufacturing verticals . The Longcheer tablet line is the flagship reference case.
Industry vertical expansion: Prior to the tablet factory deployment, Agibot demonstrated G2 in auto parts production (seatbelt lock cylinder assembly, material handling) and precision task workflows . The company aims to penetrate automotive, consumer electronics, and general manufacturing sectors.
L1–L5 autonomy roadmap: Agibot publicly defined a capability ladder with Level 3 as current state (conditional automation in bounded factory zones), targeting higher levels for less constrained environments .
Data at scale thesis: Agibot has emphasized that high-quality real-world operational data — not just hardware — is the core competitive moat, and is aggressively scaling data collection from deployed production units to feed its AI training pipeline .
Production capability as a differentiator: Having already surpassed 10,000 units produced, Agibot claims a massive manufacturing volume advantage over most competitors, which it argues enables faster iteration cycles and lower per-unit costs .
Global PR battle with Figure AI: The June livestream was explicitly timed and framed as a response to Figure AI's lab-based demos, with Agibot asserting that "real factory deployment" versus "corporate lab demonstration" is the meaningful benchmark for the industry .
The Agibot G2 livestream marked a shift in the humanoid robotics narrative from "can it work?" to "is it working in production?" While Figure AI continues to advance bipedal locomotion and general-purpose AI, Agibot's bet is that the first-mover advantage in real factory throughput — at 310 units per hour with 99%+ reliability — will define the near-term competitive landscape. Whether that bet pays off depends on how quickly both companies can scale and iterate. For now, the cameras in Nanchang showed one version of the future: humanoid robots earning their keep on a live assembly line.