DeepRouteai Accelerates “Physical AI” Rollout as Foundation Model Debuts at Auto China 2026

DeepRouteai featured prominently at Auto China 2026 this week, using the Beijing event to unveil its “Physical AI” paradigm for autonomous driving built around a 40‑billion‑parameter foundation model. The company says this large model replaces manual, rule‑based approaches with a “pure AI evolution” process, claiming a tenfold increase in closed‑loop iteration speed.

Across several communications, DeepRouteai reported deployment of its intelligent driving technology in roughly 300,000 mass‑produced vehicles and 1.3 billion kilometers of validated driving data. Management links this scale to near‑hourly iteration cycles, arguing that each additional kilometer contributes to incremental performance gains and a data‑driven network effect.

The company is targeting “million‑scale” vehicle deployment by 2026, framing the current phase as a transition from pilots and early mass production to broader commercialization. If reached, that level of scale could materially expand recurring software revenue and improve unit economics, though success will depend on OEM partnerships and regulatory approvals.

DeepRouteai also positions its Physical AI framework as an organizational shift, embedding large models as core infrastructure and emphasizing tighter human‑AI collaboration. This software‑first posture aligns with a strategy aimed at higher‑margin offerings such as licensing, data services, and over‑the‑air feature upgrades for passenger vehicles.

The company’s strong presence at the Beijing Auto Show and Auto China 2026 appears designed to deepen engagement with automakers, regulators, and ecosystem partners. While detailed financial metrics and commercialization timelines remain limited, the week’s updates underscore a push to leverage scale, data, and foundation‑model innovation to reinforce DeepRouteai’s competitive standing in autonomous and intelligent mobility.