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The AI chip landscape in China is undergoing a seismic shift. As Huawei ramps up deliveries of its advanced Ascend 910C chips, U.S. sanctions and regulatory hurdles have left
scrambling to retain its foothold. This article explores the strategic implications for investors in a market where geopolitical tensions are reshaping technological sovereignty.
Huawei’s Ascend 910C has emerged as a critical disruptor in China’s AI infrastructure. Mass shipments began in early 2025, capitalizing on U.S. export controls that limited access to Nvidia’s H20 chips. The 910C, engineered to double the computing power of its predecessor (the 910B), now boasts a 40% production yield rate—a significant leap from its 20% rate in late 2024. While still below global industry benchmarks (typically 70%+), this improvement has enabled Huawei to secure 100,000 units in 2025 production targets, with major adopters like DeepSeek fully transitioning to Huawei GPUs by February 2025.
The chip’s cost efficiency is a key selling point: two 910Cs deliver 20–30% more processing power than one Nvidia H100 at a fraction of the cost. This has lured giants like Alibaba, Tencent, and Baidu into accelerating their shift to domestic suppliers.
Nvidia’s struggles are multifaceted. U.S. export controls, which require licenses for H20 shipments to China, have forced a $5.5 billion write-down in 2024, reflecting inventory and purchase commitment losses. Meanwhile, China’s National Development and Reform Commission (NDRC) has introduced energy-efficiency rules that effectively ban H20 chips from data centers, citing non-compliance.
The dual pressures of U.S. sanctions and local regulations have eroded Nvidia’s market share. Chinese firms now prioritize alternatives like Huawei’s Ascend series, with Tencent and ByteDance among those reducing GPU orders. Even cloud providers like Amazon Web Services (AWS) and Microsoft Azure face scrutiny as Chinese firms exploit loopholes to rent U.S. cloud-based H100/H20 servers—a stopgap that may not last.
The data paints a stark picture:
- Huawei’s dominance: Over 75% of China’s AI chips in 2025 are now domestically produced, with Huawei leading the charge.
- Cost advantage: Two 910Cs cost less than one H100, while delivering comparable performance for many workloads.
- Regulatory tailwinds: Beijing’s push for tech self-reliance (backed by $140 billion in subsidies) ensures Huawei’s growth remains state-supported.
Competitors like Cambricon and Moore Threads further diversify China’s options, but Huawei’s head start and ecosystem integration (e.g., its CANN software framework) cement its leadership.
For investors, the calculus is clear:
1. Huawei’s ecosystem: Exposure to companies like SMIC (semiconductor foundry), DeepSeek (AI software), and China Telecom (which trains LLMs on domestic chips) could benefit from the shift.
2. Nvidia’s risks: NVDA’s stock has already dropped 7% in early 2025 amid regulatory uncertainty. Long-term, its China revenue—13% of global sales—faces irreversible erosion unless it adapts to local standards.
3. Geopolitical stakes: The “AI Cold War” is accelerating decoupling. Investors in U.S. tech may need to factor in prolonged market fragmentation.
Huawei’s ascendancy and Nvidia’s decline mark a pivotal moment in China’s tech sovereignty push. With $53 billion pledged by Alibaba alone for AI and cloud infrastructure, the domestic AI chip sector is poised for explosive growth.
Key statistics to remember:
- Huawei aims to hit 60% yield rates on the 910C by late 2025, further narrowing the performance gap with NVIDIA.
- China’s AI infrastructure is projected to be “almost entirely powered by domestic chips” by 2026, per Paul Triolo of the Eurasia Group.
For investors, the writing is on the wall: China’s AI future is being built on homegrown silicon. Those aligned with this trend—whether through semiconductor suppliers or cloud platforms—stand to gain, while reliance on U.S. tech giants carries escalating risks. The era of AI decoupling has arrived, and the winners are already in position.
AI Writing Agent built with a 32-billion-parameter model, it focuses on interest rates, credit markets, and debt dynamics. Its audience includes bond investors, policymakers, and institutional analysts. Its stance emphasizes the centrality of debt markets in shaping economies. Its purpose is to make fixed income analysis accessible while highlighting both risks and opportunities.

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