China is positioning itself as the global leader in nuclear-powered artificial intelligence infrastructure, deploying small modular reactors (SMRs) to solve one of AI's most pressing challenges: massive, reliable electricity demand. As the token economy becomes the latest buzzword in tech, where tokens represent the fundamental units of data processed by AI large language models, companies worldwide are racing to secure stable power sources for their computing centers. The convergence of nuclear energy and AI is no longer theoretical,it's happening now, with China's Linglong One reactor nearing commercial operation and tech giants like Microsoft and Google actively exploring SMR technology (Source 1, 2).

What Makes Small Modular Reactors Different From Traditional Nuclear Plants?

Traditional nuclear reactors are massive, centralized facilities that take years to build and require enormous upfront investment. Small modular reactors flip this model on its head. Linglong One, developed by CNNC Hainan Nuclear Power Co, represents a fundamental shift in how we think about nuclear power generation. The reactor is the world's first onshore commercial SMR to pass a safety review by the International Atomic Energy Agency (IAEA), marking a watershed moment for the technology (Source 1, 2).

"It's like the evolution from desktop computers to laptops. Traditional large reactors are like desktop computers with separate components. Linglong One is an all-in-one laptop, compact, convenient and safe," said Wei Zhigang, chairman of CNNC Hainan Nuclear Power Co.

Wei Zhigang, Chairman of CNNC Hainan Nuclear Power Co

The comparison is apt. SMRs can be deployed precisely where computing power is needed, enabling what Wei calls "close load-matching." This flexibility is revolutionary for data center operators who have historically been constrained by the location of large power plants. With SMRs, the power source comes to the computing center, not the other way around (Source 1, 2).

How Are SMRs Solving AI's Energy Crisis?

• Flexible Placement: SMRs can be installed directly at data center sites or industrial facilities, eliminating transmission losses and enabling precise power matching to computing demand.
• Carbon-Free Baseload Power: Unlike renewable energy sources that depend on weather conditions, SMRs provide round-the-clock, stable electricity without carbon emissions, critical for AI infrastructure that runs continuously.
• Industrial Heat Applications: Beyond electricity, SMRs can provide industrial steam and process heat, making them valuable for manufacturing facilities like Dow's Seadrift Operations in Texas, which is planning to deploy four 80-megawatt SMR units.
• Scalability and Modularity: Multiple SMR units can be deployed together to meet growing demand, offering a scalable alternative to building new large reactors.

Linglong One will generate 1 billion kilowatt-hours annually upon completion, sufficient to power 526,000 households while reducing carbon dioxide emissions by 880,000 metric tons, equivalent to planting 7.5 million trees (Source 1, 2). But the real significance lies in what this reactor enables: a pathway to nuclear-powered AI infrastructure that can scale globally.

The International Atomic Energy Agency's director-general, Rafael Mariano Grossi, has become a vocal advocate for this convergence. He stated that nuclear energy is destined to be the energy partner of the AI revolution, emphasizing that only nuclear power can meet five critical needs simultaneously (Source 1, 2).

"Only nuclear energy can meet the five needs of low-carbon power generation, round-the-clock reliability, ultra-high power density, grid stability and true scalability," said Rafael Mariano Grossi, director-general of the IAEA.

Rafael Mariano Grossi, Director-General of the International Atomic Energy Agency

Why Is China Moving Faster Than the West on This Front?

China's government has made computing-electricity synergy a national priority in its 2026 Government Work Report, signaling that nuclear-powered AI infrastructure is now a strategic imperative. This top-down commitment is accelerating deployment timelines and attracting international attention. More than 1,000 visitors from almost 90 countries and regions have traveled to Hainan to inspect Linglong One, including the IAEA director-general, underscoring the global significance of this project (Source 1, 2).

The numbers tell a compelling story about China's growing dominance in the AI token economy. According to OpenRouter, a platform widely used by overseas developers to access AI models, global weekly usage of Chinese AI models reached 12.96 trillion tokens from March 30 onwards, up 31.5 percent week-on-week, while US AI models logged only 3.03 trillion tokens, rising just 0.76 percent. Chinese AI models have outpaced their US counterparts in global usage for five consecutive weeks, underscoring a growing token economy in China defined by scale, pricing, and computing infrastructure (Source 1, 2).

Wei Zhigang emphasized the strategic importance of this moment: "As AI triggers unprecedented global demand for computing power, the ultimate constraint has become clear: the need for vast, stable electricity supplies." This insight captures why nuclear power is suddenly central to the AI race. Computing power is no longer the bottleneck; electricity is (Source 1, 2).

Wei Zhigang

What's Happening in the United States?

The US is not sitting idle. Irving-based Fluor Corporation has partnered with Maryland-based X-energy to support an advanced nuclear project at Dow's UCC Seadrift Operations in South Texas. The project involves developing four 80-megawatt SMR units to supply the facility with safe, reliable, carbon-free electricity and industrial steam, replacing aging energy infrastructure .

This project, supported by the US Department of Energy's Advanced Reactor Demonstration Program, is expected to become the first grid-scale advanced nuclear reactor deployed to serve an industrial facility in North America. Fluor is currently delivering Front-End Loading Stage 2 (FEL-2) services, which focus on project definition, strategic planning, feasibility assessment, cost control, and risk mitigation. A construction permit application was submitted in March 2025 and is currently under review by the US Nuclear Regulatory Commission .

Pierre Bechelany, Fluor's business group president of energy solutions, noted that X-energy's technology "offers a powerful pathway for small modular reactors to deliver safe, reliable and fit-for-purpose baseload power in an industrial setting." With eight decades of nuclear experience, Fluor brings proven expertise to help advance this landmark project .

Pierre Bechelany, Fluor's business group president of energy solutions

What Does This Mean for the Future of AI Infrastructure?

The convergence of nuclear power and AI represents a fundamental shift in how we think about computing infrastructure. For decades, data centers have been constrained by available power sources, forcing companies to build in locations with cheap electricity or abundant renewable resources. SMRs break this constraint by bringing reliable, carbon-free power directly to where it's needed.

China's Linglong One and the US Seadrift project represent two different approaches to the same problem: how to power the next generation of AI computing without relying on fossil fuels or intermittent renewable energy. Both projects are moving forward rapidly, signaling that nuclear-powered AI infrastructure is transitioning from concept to reality. The token economy is reshaping global tech competition, and the companies that secure reliable, abundant electricity will have a decisive advantage in the race to build and deploy advanced AI systems.