China's semiconductor industry is looking to bridge its technology gap with NVIDIA by stacking mature logic nodes with high-bandwidth memory and new compute architectures, according to remarks from Wei Shaojun, vice president of the China Semiconductor Industry Association. Speaking at an event in Shenzhen (via ESM China), Wei said that 14 nm logic chips, far behind the 4 nm-class silicon used in NVIDIA's current AI GPUs, could reach comparable performance if paired with 18 nm DRAM using 3D hybrid bonding and a near-memory computing architecture. The approach reduces data movement and improves energy efficiency by placing compute elements directly beside memory. The concept mirrors Huawei's recent strategy of "stacking and clustering" chips as a workaround to US export controls, which block China's access to advanced nodes such as 5 nm and below. Huawei has argued that performance can still scale by increasing chip integration density instead of relying on cutting-edge lithography .

Wei emphasized that his proposed design uses a fully domestic supply chain, 14 nm logic and 18 nm DRAM are both covered by current US export restrictions, limiting access to foreign production. He also noted that the global AI ecosystem remains heavily dependent on NVIDIA hardware and CUDA software, calling it a "triple dependence" across models, architectures, and development tools. Chinese GPU alternatives are emerging , including Zhonghao Xinying, a startup founded by Google engineer Yanggong Yifa. The company claims its custom ASIC TPU accelerator can reach "up to 1.5x" the compute performance of NVIDIA's older A100 GPU.