China Sets 2030 AI Computing Target at 9,800 Eflops

China's Ambitious AI Infrastructure Roadmap

China has unveiled plans to more than quadruple its artificial intelligence computing capacity by 2030, setting a target of 9,800 eflops as part of a sweeping five-year infrastructure initiative announced by the Ministry of Industry and Information Technology.

The plan calls for 3.8 trillion yuan ($532 billion) in cumulative information infrastructure investment between 2026 and 2030, with a focus on deploying massive computing clusters containing between 10,000 and 100,000 accelerator cards. The ministry also emphasized adapting infrastructure to support domestically produced computing chips.

Rapid Growth Already Underway

China's intelligent computing capacity reached 2,185 eflops—exa floating-point operations per second—by the end of June, representing a 177 percent increase from the previous year, according to MIIT. The country had already constructed 52 intelligent computing facilities equipped with more than 10,000 accelerator cards each.

By July's end, capacity had climbed further to approximately 2,450 eflops, data from the National Data Administration shows. Reaching the 2030 target will require expanding capacity more than fourfold from the June baseline.

Building on Geographic Strategy

The expansion extends the "East Data, West Computing" project launched in 2022, which aims to relocate power-intensive computing operations from densely populated eastern provinces to western regions where land costs less and energy supplies are more abundant. This initiative has established a network centered on eight national computing hubs, 10 data-center clusters, and three regions dedicated to coordinating computing facilities with power infrastructure.

The new plan emphasizes "orderly deployment" of both large-scale training clusters and inference computing facilities tailored to specific applications, suggesting a strategic approach to balancing different AI workload requirements.

Why it matters

China's commitment to quadrupling AI computing capacity represents one of the world's largest national investments in AI infrastructure at a time when computing power has become a critical bottleneck for developing advanced AI systems. The emphasis on domestic chip adaptation signals Beijing's determination to build self-sufficient AI capabilities amid ongoing technology restrictions. For global technology companies and policymakers, these targets provide concrete metrics for assessing China's progress in the AI competition and may influence decisions about data center investments, chip manufacturing priorities, and international AI governance frameworks.

These details were first reported by the South China Morning Post.