ByteDance, Alibaba, and Tencent have placed $35 billion in orders for Nvidia’s RTX PRO 5500 cards after US export curbs limited access to top-tier AI processors. With global demand far exceeding Nvidia’s production capacity, investors should watch for potential impacts on AI hardware availability and rising infrastructure costs across the global tech sector.
Major Chinese internet conglomerates, including ByteDance, Alibaba, and Tencent, have placed orders exceeding $35 billion for Nvidia’s RTX PRO 5500 graphics cards. This move reflects a strategic pivot by these firms as US export controls continue to restrict access to Nvidia’s flagship AI data-center processors, such as the Blackwell-based B300 and Hopper-based H200 models. To maintain their development of chatbot and industrial AI models, these companies are now turning to workstation-grade hardware as the most powerful, export-compliant alternative available for AI inference tasks.
A Workaround for Export-Restricted Markets
The scale of this procurement is significant, involving over 3 million units at an estimated price of roughly $11,400 per card. While these workstation cards were not originally designed for massive data-center deployment, they have become essential assets for firms struggling to build AI infrastructure under the current regulatory climate. Previously, many Chinese tech entities held out hope for a potential relaxation in Washington’s export policies, but the persistence of these restrictions has forced a shift toward securing whatever compliant hardware is available, regardless of the higher cost and lower capability compared to top-tier data-center chips.
Supply Constraints and Manufacturing Priorities
Investors should note that securing these orders does not guarantee delivery. Nvidia has reportedly signaled to partners that it cannot meet this level of demand due to significant manufacturing constraints. Current production forecasts suggest that Nvidia may produce only about 3 million units globally in 2027. With demand from China alone estimated to be double that amount, industry projections suggest that buyers might receive only a fraction of their requested quantities, potentially as low as 5% to 10%.
The supply crunch is further complicated by Nvidia’s manufacturing strategy at Taiwan Semiconductor Manufacturing Co. (TSMC). A significant portion of production capacity is reportedly being diverted toward the upcoming Rubin platform, which is designed for large-scale data centers. This reallocation of manufacturing bandwidth puts additional pressure on the supply of workstation-grade hardware, creating a bottleneck that affects not just the Chinese buyers, but the global availability of high-end graphics processing units.
For investors, this situation highlights the ongoing vulnerability of the global AI supply chain. As companies worldwide scramble for compute power, supply shortages can lead to increased costs for cloud services and delays in AI project rollouts. The primary monitorables for the sector will be Nvidia’s actual fulfillment rates and whether persistent chip scarcity begins to impact the timelines for AI infrastructure development globally. The ability of major tech firms to scale their AI operations will remain closely tied to their success in securing hardware amid these manufacturing and regulatory pressures.