- China plans huge AI computing network backed by domestic chips
- High-bandwidth memory shortage restricts production of advanced AI accelerators in China
- Domestic chipmakers are still several years behind global leaders
China is drafting a plan that could allocate roughly 2 trillion yuan (about $295 billion) to a nationwide artificial intelligence computer network.
The proposal would connect data centers across the country into a unified computer network operated largely by state-backed telecommunications companies.
Officials reportedly want at least 80% of the underlying technology, including AI chips and related infrastructure, to come from Chinese suppliers.
A massive construction focused on local technology
The plan is being developed by the National Development and Reform Commission, while major operators including China Mobile and China Telecom would oversee the operation.
The network would reportedly be linked to a single national computing platform by 2028 through extensive infrastructure deployment.
Financing would rely heavily on sovereign borrowing and ultra-long government bonds, while associated power grid upgrades could substantially increase costs.
The total capital requirement could rise beyond 5 trillion yuan (about $738 billion) when energy infrastructure is included in broader estimates linked to deployment.
The plan comes as Beijing continues to tighten restrictions on foreign semiconductor products used in data centers and artificial intelligence facilities.
In 2025, authorities introduced requirements for data centers to source at least 50% of their chips from domestic manufacturers, and in November of that year, state-funded projects reportedly faced additional restrictions that excluded foreign accelerators from facilities still under construction.
Officials also pushed for compliance measures that required the removal of Nvidia, AMD and Intel components in projects less than 30% complete.
Those measures have increased opportunities for Chinese chip companies, including Huawei, while reducing dependence on suppliers such as Nvidia, AMD and Intel.
The policy ensures that critical AI tools and LLMs run on hardware developed in China, but replacing imported processors remains a difficult task.
Domestic chip supply remains a major challenge
Chinese semiconductor manufacturing capabilities come primarily from SMIC and a small group of state-approved foundries.
SMIC co-chief executive Zhao Haijun warned that excessive infrastructure expansion could leave facilities underutilized.
Reports indicate that SMIC’s most advanced stable manufacturing process remains roughly comparable to 7nm technology and is already operating above 93% utilization levels.
With numerous domestic chip designers competing for the same production resources, rapidly expanding production may be difficult under current wafer allocation limits.
High-bandwidth memory also remains a major limitation, limiting the number of advanced accelerators that can be assembled for AI workloads and the deployment of AI tools.
Industry estimates suggest that domestic suppliers could meet only about 76% of Chinese demand for AI chips by 2030, even as demand expands toward a market size of $67 billion.
Huawei has increased shipments, including about 812,000 chips last year, but supply chain limits continue to affect scaling up production.
Chinese industry executives have acknowledged that domestic AI data center chips are 5 to 10 years behind major international competitors in some categories.
Reports also indicate that DeepSeek returned to Nvidia hardware for certain training tasks after experimenting with Huawei alternatives on heavy workloads.
This suggests that Chinese processors may still struggle with the most demanding AI training environments despite advances in inference performance.
Through Tom Hardware
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