GoKawiilChina is drafting a plan to spend roughly 2 trillion yuan ($295 billion) over five years on a nationwide web of AI data centers. The goal is for at least 80% of the underlying technology, AI chips included, to be sourced from domestic suppliers such as Huawei, according to a Bloomberg report citing people familiar with the discussions.
The National Development and Reform Commission is responsible for the blueprint of this network, while state carriers China Mobile and China Telecom will operate most of the facilities and link them up to a single computing grid by 2028. The build-out of this grid leans heavily on sovereign debt and ultra-long special government bonds. Folding in power grid upgrades could push the total capital requirement beyond 5 trillion yuan, those sources told Bloomberg.
Funding the build-out is easy, though; filling them with domestic accelerators is a different story. The 80% domestic sourcing requirement effectively locks out Nvidia and AMD accelerators, so China will be capped by whatever amount of chips SMIC can physically produce. The foundry’s most advanced stable node remains its N+2 process, which is roughly equivalent to 7nm and is currently running above 93% utilization, leaving little headroom as every government-certified Chinese chipmaker competes for the same wafer slots.
Latest Videos From Watch full video here:
Another major chokepoint is high-bandwidth memory. Highly limited domestic HBM supply constrains how many Ascend-class accelerators Huawei can assemble. Huawei alone shipped around 812,000 chips last year and projects some $12 billion in processor revenue for 2026, a pace that its own supply chain has struggled to sustain. It’s estimated that China’s domestic suppliers will cover only around 76% of all Chinese AI chip demand by 2030, even as that market grows toward $67 billion.
Beijing has massively tightened its restrictions on foreign silicon in a series of new controls. Last August, Beijing introduced a requirement that data centers source at least 50% of chips locally, and by November, state-funded projects were barred from foreign accelerators entirely, with builds less than 30% complete reportedly told to strip out Nvidia, AMD, and Intel parts.
China's own industry has questioned whether domestic hardware can keep pace. SMIC co-CEO Zhao Haijun has cautioned that the rush to add capacity risks leaving data centers idle, comparing it to building highways ahead of the traffic. Chinese chip executives have separately conceded the country trails the leading edge in AI data center silicon by five to 10 years. When DeepSeek was steered toward Huawei hardware for model training, it eventually reverted to Nvidia hardware, lending credence to the idea that domestic parts still struggle with the heaviest training workloads, even where they suffice for inference.
Follow Tom's Hardware on Google News, or add us as a preferred source, to get our latest news, analysis, & reviews in your feeds.