NVIDIA’s dominance in China’s AI chip market has significantly weakened over the last few years, dropping from around 95% share before U.S. export controls to about 55% by 2025, according to recent IDC‑based industry reports. This shift reflects a broader transition where Chinese data centers and AI companies are actively adopting domestically developed accelerators instead of relying almost entirely on NVIDIA’s GPUs. Domestic brands now account for roughly 41% of China’s AI accelerator card shipments, with Huawei leading the pack at around 20% of the total market and over half of the domestic volume.
For NVIDIA, this decline is both structural and symbolic: even though it still ships the largest absolute number of units (close to 2.2 million cards), its leadership rests increasingly on inference‑oriented and mid‑range chips, while its most advanced training hardware has been cut off by export restrictions. The Chinese government’s push for “self‑reliance” in semiconductors, combined with purchases from local cloud and internet giants, has given homegrown vendors such as Huawei, Cambricon, and others a solid foothold. These vendors are not just filling gaps left by sanctions; they are beginning to compete on performance and software ecosystem, at least within the Chinese market.
From a strategic perspective, this erosion of NVIDIA’s monopoly in China reshapes the global AI hardware landscape. For the U.S., it means that one of the most profitable AI markets can no longer be treated as a given, and that American policy choices such as export controls directly accelerate foreign competitors. At the same time, it does not yet translate into a clear global defeat for NVIDIA: outside China, its GPUs still anchor most high‑end AI training clusters. The real question is whether Chinese AI chip stacks can match or surpass NVIDIA’s full software‑hardware ecosystem in the long run, or if they will remain strong mainly within China’s own digital‑economy orbit.
