China’s rapid expansion of advanced chip-stacking technologies has raised fresh questions about whether the country can meaningfully challenge Nvidia’s dominance in the global AI hardware market. While new packaging techniques, including 3D stacking and high-bandwidth chiplet integration, are reshaping China’s semiconductor ambitions, analysts caution that significant technological and supply-chain hurdles remain.
A strategic shift in China’s semiconductor race
Beijing has increasingly prioritised advanced packaging as a way to accelerate progress despite US export controls that restrict access to cutting-edge manufacturing tools. By combining multiple layers of silicon to form denser and more efficient processors, Chinese firms aim to close the performance gap with Western AI chips at a faster pace. This approach has attracted major state investment, with leading Chinese fabs and research institutes expanding facilities dedicated to 3D chip integration.
How chip stacking works — and why it matters
Stacked architectures allow chipmakers to vertically integrate logic, memory, and interconnect layers, enabling improved performance without requiring the most advanced lithography tools. The technique boosts bandwidth and reduces power consumption, crucial factors for AI workloads. For China, the appeal lies in the fact that advanced packaging technologies remain less constrained by export restrictions compared with cutting-edge lithography such as EUV.
Nvidia’s advantage still dominates the high end
Despite progress in China’s domestic development, Nvidia retains a substantial technological lead. Models such as the H100 and Blackwell-class GPUs benefit from highly optimised software ecosystems, advanced interconnects, and deep integration with cloud-scale AI training infrastructure. The firm’s CUDA platform remains the global standard for AI development, giving Nvidia a competitive moat that hardware alone cannot easily erode. Export restrictions also limit China’s access to the high-performance GPUs required for training frontier-scale models.
Challenges for China’s push
China faces several obstacles as it scales its stacking strategy. Domestic fabs still rely heavily on foreign equipment for high-yield production, and local developers have yet to replicate the full software stack that underpins Western AI systems. Moreover, 3D stacking introduces thermal, reliability, and supply-chain complexities that require years of refinement. While local firms have demonstrated competitive designs, mass production at Nvidia-level performance remains elusive.
Long-term implications
Even if China cannot immediately challenge Nvidia at the high end, its chip-stacking approach may significantly boost domestic AI capacity. By focusing on high-bandwidth, energy-efficient accelerators optimised for specific tasks, China could create a parallel ecosystem that supports national AI ambitions while reducing reliance on foreign suppliers. The divergence between Western and Chinese AI hardware pathways is expected to deepen, potentially reshaping global technology markets in the next decade.
Newshub Editorial in Asia – 4 December 2025
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