This post originally appeared on Recode China AI.
For more than a decade, Nvidia’s chips have been the beating heart of China’s AI ecosystem. Its GPUs powered search engines, video apps, smartphones, electric vehicles, and the current wave of generative AI models. Even as Washington tightened export rules for advanced AI chips, Chinese companies kept settling for and buying “China-only” Nvidia chips stripped of their most advanced features—H800, A800, and H20.
But by 2025, patience in Beijing had seemingly snapped. State media began labeling Nvidia’s China-compliant H20 as unsafe and possibly compromised with hidden “backdoors.” Regulators summoned company executives for questioning, while reports from The Financial Times surfaced that tech companies like Alibaba and ByteDance were quietly told to cancel new Nvidia GPU orders. The Chinese AI startup DeepSeek also signaled in August that its next model will be designed to run on China’s “next-generation” domestic AI chips.
The message was clear: China could no longer bet its AI future on an U.S. supplier. If Nvidia wouldn’t—or couldn’t—sell its best hardware in China, domestic alternatives must fill the void by designing specialized chips for both AI training (building models) and AI inference (running them).
That’s difficult—in fact, some say it’s impossible. Nvidia’s chips set the global benchmark for AI computing power. Matching them requires not just raw silicon performance but memory, interconnection bandwidth, software ecosystems, and above all, production capacity at scale.
Still, a few contenders have emerged as China’s best hope: Huawei, Alibaba, Baidu, and Cambricon. Each tells a different story about China’s bid to reinvent its AI hardware stack.
Huawei’s AI Chips Are in the Lead
Huawei is betting on rack-scale supercomputing clusters that pool thousands of chips together for massive gains in computing power. VCG/Getty Images
If Nvidia is out, Huawei, one of China’s largest tech companies, looks like the natural replacement. Its Ascend line of AI chips has matured under the U.S. sanctions, and in September 2025 the company laid out a multi-year public roadmap:
Ascend 950, expected in 2026 with a performance target of 1 petaflop in the low-precision FP8 format that’s commonly used in AI chips. It will have 128 to 144 gigabytes of on-chip memory, and interconnect bandwidths (a measure of how fast it moves data between components) of up to 2 terabytes per second.
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