China’s AI Hardware Boom Threatens Nvidia’s Grip on the Market
Nvidia’s China Market Share Set to Plunge
Nvidia, long the leader in AI GPUs, is facing a major shakeup in China. Analysts from Bernstein predict the company’s market share in the country could drop sharply from 66% in 2024 to just 8% in the coming years.
The drop is being driven by a combination of US export restrictions, China’s domestic GPU development, and the rapid adoption of locally produced AI accelerators. Even though Nvidia’s AI processors like Hopper H100 and H200 remain highly sought after, Chinese companies are closing the gap quickly.
Domestic Chinese GPUs Take Center Stage
Chinese firms such as Huawei, Cambricon, Moore Threads, and MetaX are now able to meet about 80% of the local AI hardware demand. Moore Threads recently unveiled its first AI GPU, codenamed Huashan, specifically designed to accelerate AI workloads.
Zhang Jianzhong, CEO of Moore Threads, emphasized the importance of domestic development:
“There will be no more need to wait for advanced products from overseas.”
These new Chinese GPUs can compete with Nvidia’s previous-generation Hopper products, though they still lag behind the latest Blackwell B200 and B300 GPUs, which remain barred from export to China.
Chinese AI Hardware Performance is Rising
Despite the restrictions, Chinese developers are making rapid progress:
- Huawei’s CloudMatrix 384 reportedly outperforms some Nvidia systems in BF16 FLOPS, though it consumes four times more power.
- The next-generation Atlas 950 SuperCluster, expected by 2026-2027, could deliver up to 524 FP8 ExaFLOPS for AI training and 1 FP4 ZettaFLOPS for AI inference, scaling to 4 ZettaFLOPS by 2028.
- For comparison, Oracle’s Blackwell-based OCI Supercluster runs 131,072 B200 GPUs with 2.4 FP4 ZettaFLOPS for inference.
These numbers show that Chinese AI hardware is rapidly catching up, though Nvidia still holds an edge in high-end performance.
The Challenge of Transitioning from Nvidia
Many AI deployments in China still rely heavily on Nvidia hardware and the CUDA software stack. Migrating to domestic GPUs requires rewriting code and adapting software, which is complex and costly.
Despite these challenges, China’s long-term goal is clear: full domestic AI hardware and software independence. A draft five-year plan circulated by the Communist Party in October 2025 emphasizes semiconductor self-reliance and coordination between state bodies, private firms, and financial institutions.
The “Four Little Dragons” of Chinese GPUs
At the forefront of China’s AI hardware push are four domestic GPU companies:
- Moore Threads
- MetaX
- Biren Technology
- Suiyuan Technology (Enflame)
These companies are supported by large hyperscalers like Baidu and Alibaba, both of which are developing custom AI processors to reduce dependence on foreign technology. Baidu’s Kunlunxin unit plans to introduce five AI processors by 2030, while Alibaba is expanding its own AI silicon efforts.
Limitations and Challenges
Despite the rapid rise, China’s AI ambitions face a bottleneck: manufacturing capacity. The country’s leading foundry, SMIC, is limited to producing chips on 7nm-class process technologies, which constrains high-end GPU output.
If production cannot scale, China may either:
- Fall behind the US in AI hardware performance, or
- Find ways to continue importing Nvidia GPUs despite restrictions.
What This Means for Nvidia
Nvidia’s dominance in China is under serious threat. While the company remains a global leader in AI hardware, the combination of export restrictions and domestic innovation could drastically reduce its share of the world’s largest AI market.
Analysts suggest that Nvidia will need to adapt its strategy, either by focusing on higher-end GPUs barred from export or by partnering with Chinese companies to maintain influence in the region.
China’s AI hardware ecosystem is maturing fast. While Nvidia’s products remain technologically advanced, domestic GPUs from Moore Threads, Huawei, Cambricon, and others are meeting local demand. If China achieves full self-reliance, Nvidia could see its market share fall to just 8%, reshaping the AI hardware landscape in the coming years.
