Nvidia’s Dominance in AI and Emerging Threats from China’s Self-Sufficiency Drive

Nvidia’s reign as the undisputed leader in the AI chip market has been built on a combination of cutting-edge hardware, the CUDA software ecosystem, and strategic partnerships with cloud providers and hyperscalers. As of 2025, the company controls 86% of the AI GPU market, with its Blackwell product line generating $27 billion in sales and accounting for 70% of data center revenue [1]. However, this dominance is now under threat from a confluence of factors: rising competition from U.S. rivals, the fragmentation of the AI chip market by hyperscalers, and China’s aggressive push for self-sufficiency in semiconductor technology. These dynamics raise critical questions about the long-term sustainability of Nvidia’s valuation and the vulnerabilities embedded in its supply chain.

The Fragility of Nvidia’s Supply Chain

Nvidia’s AI chip supply chain is deeply intertwined with global geopolitical tensions. The company relies on a tripartite ecosystem: NVIDIA for design, ASML for EUV lithography equipment, and TSMC for manufacturing [2]. This concentration creates significant risks. For instance, U.S. export controls on advanced EUV machines to China have stifled TSMC’s ability to produce cutting-edge chips for Chinese clients, indirectly limiting the scalability of domestic alternatives [3]. Meanwhile, China’s control over 98% of gallium—a critical material for semiconductor production—has introduced a potential chokehold on global supply chains [4].

The U.S.-China trade war has further exacerbated these vulnerabilities. In 2025, Nvidia faced an $8 billion revenue hit due to export restrictions on its H20 chips to China, a market that historically contributed 13% of its revenue [5]. While the Trump administration’s partial reversal of these restrictions in July 2025 allowed H20 sales to resume, the company now shares 15% of its China revenue with the U.S. government, eroding gross margins by 8–10 percentage points [6]. This regulatory uncertainty has forced Nvidia to diversify its geographic footprint, with partnerships in Saudi Arabia and Europe now accounting for a growing share of its growth strategy [7].

China’s Self-Sufficiency Drive: A Looming Challenge

China’s push for semiconductor self-reliance has accelerated under U.S. export controls and state-led industrial policies. By 2025, the country’s AI chip localization rate has surged to 55%, up from 17% in 2023 [8]. Huawei’s Ascend 910D, for example, matches the H100’s FP16 performance (1.2 PFLOPS) and offers a 44% lower total cost of ownership (TCO) for Chinese enterprises [9]. While the 910D lags in memory bandwidth (800 GB/s vs. H100’s 3 TB/s), its adoption by firms like ByteDance and SenseTime signals growing traction in domestic markets [10].

Cambricon, another Chinese contender, has seen a 44x revenue surge in H1 2025, driven by government subsidies and partnerships with AI models like DeepSeek [11]. The company’s Siyuan 690 chip is now competing directly with the H100, and Bernstein forecasts Nvidia’s market share in China could drop to 54% in 2025 from 66% in 2024 [12]. These developments are compounded by China’s investment in RISC-V architectures and DUV lithography, which aim to bypass U.S. technological dominance [13].

Strategic Vulnerabilities and Valuation Risks

Nvidia’s valuation, which has grown from $46.7 billion in Q2 2025 to a $3 trillion market cap, hinges on sustained demand for its AI infrastructure. However, three key vulnerabilities threaten this trajectory:
1. Geopolitical Exposure: China’s $50 billion AI market remains a critical growth driver, yet U.S. sanctions and cybersecurity scrutiny of Nvidia’s H20 chips have created regulatory headwinds [14].
2. Ecosystem Fragmentation: Hyperscalers like Google and Amazon are developing proprietary AI chips (e.g., TPUs, Trainium2) to reduce dependency on third-party suppliers, fragmenting the market [15].
3. Software Ecosystem Challenges: While CUDA dominates 75% of China’s AI model training, local alternatives like Huawei’s MindSpore and Cambricon’s frameworks are gaining traction, threatening long-term software lock-in [16].

Conclusion: A Reassessment of Long-Term Valuation

Nvidia’s dominance in AI is underpinned by its full-stack advantage and first-mover status. However, the company’s valuation sustainability depends on its ability to navigate geopolitical risks, adapt to a fragmented market, and defend its software ecosystem against rising local competitors. While the Blackwell B200 and strategic partnerships in Saudi Arabia offer short-term relief, the long-term outlook remains clouded by China’s self-sufficiency drive and the emergence of alternative architectures like RISC-V. Investors must weigh these factors against Nvidia’s historical resilience, but the growing complexity of the AI chip supply chain suggests a more cautious approach to its valuation.

Source:
[1] PatentPC. [2] AInvest. [3] ASML Press Release. [4] Sourceability. [5] AInvest. [6] AInvest. [7] AInvest. [8] AInvest. [9] Semiconductors Insight. [10] Bitrue. [11] Morningstar. [12] AInvest. [13] WEF. [14] AInvest. [15] TechInsights. [16] AInvest.