China Shifts Computing Power Strategy From Scale to Regional Coordination

A national panorama report released at the 2026 China Computing Power Conference indicates that China's computing infrastructure is transitioning from raw capacity expansion to systemic and refined coordination. As of June 2026, the country operated 15.56 million standard server racks, 2,185 EFLOPS in intelligent computing capacity (FP16), and over 2,000 EB in storage capacity. Using a four-dimensional evaluation framework across 31 provincial jurisdictions, the report maps distinct regional specializations between eastern innovation hubs and resource-rich western provinces, while warning of friction in cross-regional resource scheduling and industrial adoption.

Computing power serves as the core foundational engine for artificial intelligence and the digital economy. The evolution of China's official evaluation framework from raw capacity to a systemic matrix spanning compute, storage, network transmission, and environment signals that the sector is entering a phase focused on operational utilization, model-infrastructure alignment, and interprovincial resource sharing.

China's computing power sector is transitioning from sheer physical expansion toward systemic, coordinated deployment, according to the 2026 Comprehensive Computing Power Panoramic Analysis released at the 2026 China Computing Power Conference, reported by People's Daily. Official figures cited in the report indicate that as of June 2026, China maintained 15.56 million standard operational server racks. In-use intelligent computing capacity reached 2,185 EFLOPS measured at FP16 precision, while national storage capacity exceeded 2,000 exabytes (EB). The study noted concurrent architectural upgrades across access networks, inter-computing pipelines, and intra-cluster fabrics designed to support digital economy workloads. To capture regional variations, the assessment introduced an updated evaluation matrix assessing 31 provincial-level jurisdictions across four core dimensions: computing capacity, storage capacity, network transport capacity, and operational environment. The resulting mapping showed a distinct regional gradient: a small tier of leading provinces at the top, a broad cluster in the middle, and varied differentiation across individual operational metrics. Eastern coastal hubs retain clear leads in market demand, industrial clustering, and foundational research. Beijing, Shanghai, and Guangdong demonstrated particular strength in large language model development, generative artificial intelligence services, and broader ecosystem maturation. Storage infrastructure was concentrated most heavily in Guangdong, Hebei, and Shanghai, while Jiangsu, Zhejiang, and Guangdong scored highest in network transport coordination. Conversely, central and western jurisdictions showed advantages in land availability, climatic cooling conditions, and clean energy supply. Resource and environmental indicators favored regions such as Xinjiang, Gansu, and Qinghai. Notably, Shanxi, Qinghai, and Xinjiang achieved leading positions in rack utilization rates, reflecting active operational occupancy rather than idle capacity. Despite overall expansion, the report acknowledged structural headwinds. Regional development gradients remain stark, integration between raw computing capacity and specific vertical industry applications remains insufficient, and institutional and technical constraints continue to hinder cross-regional computing power scheduling. The report recommended tailored provincial policies, integrated planning across compute, storage, and transport, and improved market mechanisms to convert western natural resource endowments into commercial service delivery.