The US-China AI Race: A Data-Driven Look at Who Leads and Why

US President Donald Trump and Chinese President Xi Jinping are scheduled to meet in Washington, DC on Thursday for a summit expected to address trade, artificial intelligence (AI), Taiwan, and the US-Israel conflict involving Iran.

Ahead of the talks, US Treasury Secretary Scott Bessent announced that Washington has proposed an AI “notification mechanism” with China — essentially a hotline to exchange alerts when AI incidents pose national security risks.

As leading AI firms sound alarms about the technology’s dangers, both superpowers are racing to accelerate development. This visual breakdown compares US and Chinese AI capabilities across computing power, models, investment, and research.

Who has more computing power?

Training and deploying AI demands vast computing resources. The more powerful the chips and hardware a country possesses, the faster it can develop and refine AI models — making computing power a decisive edge in the rivalry.

Computing power is measured in FLOP/s (floating-point operations per second), reflecting how many calculations a system can perform each second.

Aggregating the computing capacity of all AI chips within a country reveals its total AI potential. By that metric, the US leads significantly, accounting for nearly three-quarters of global AI computing power, while China holds slightly over 14 percent, according to Epoch AI, an AI research institute.

The US advantage stems largely from access to cutting-edge chips. US-based Nvidia commands more than 60 percent of global AI computing capacity among major chip designers, while China’s Huawei holds a smaller but growing share, per Stanford University’s 2026 AI Index.

These chips also require infrastructure to run. The US operates more than 5,400 data centres — roughly 10 times as many as any other nation — and leads in dedicated AI data centres with 84, surpassing the combined total of the next eight countries.

Whose AI models are people using?

Frontier models represent the most advanced AI systems — such as OpenAI’s GPT, Anthropic’s Claude, and DeepSeek’s offerings from China. Trained on enormous datasets and computing resources, they can write, reason, and code.

The US has historically led frontier model development, but Chinese models are closing the gap.

As of March 2026, US and Chinese models were nearly tied on Arena, a leaderboard where users compare anonymous models and vote on the better response. US firms Anthropic, xAI, Google, and OpenAI ranked near the top, alongside China’s Alibaba and DeepSeek.

On OpenRouter, a platform ranking models by real-world usage, Chinese models dominate the top spots. DeepSeek, Z.ai, and Tencent hold the first three positions by tokens processed — the units of text AI models read and generate.

This dominance partly reflects lower costs. Many Chinese models are also open-weight, allowing developers to download, modify, and run them independently.

Chinese models can now compete with US ones across many tasks. According to a July analysis by the Centre for Strategic and International Studies (CSIS), Chinese AI models are “months, not years, behind” US frontier models. In May, the US government’s Center for AI Standards and Innovation (CAISI) estimated that DeepSeek V4 Pro, released in April, lagged roughly eight months behind leading US models.

Who is spending more?

The US is investing far more than China in AI infrastructure, giving its tech companies a major edge in the computing power race.

Goldman Sachs estimates that US hyperscalers — the large tech firms running cloud computing and data centres — will spend roughly $764bn in 2026. That includes Amazon, Microsoft, Google, Meta, and Oracle. By comparison, China’s Alibaba, Tencent, Baidu, and ByteDance are projected to spend $102bn.

However, China’s spending is growing faster. TrendForce, a market research firm, expects China’s four hyperscalers’ capital expenditure to rise by more than 80 percent in 2026, compared with a projected 76 percent growth for US hyperscalers, according to Reuters.

The spending gap mirrors the scale of the US tech sector, whose companies have larger revenues to reinvest in chips, data centres, and talent.

Who is leading in AI research and talent?

China is producing more AI research and training more technical talent, but the US continues to attract the world’s leading AI researchers.

China accounted for more than 27 percent of global AI publications in 2024 — including journal articles, conference papers, working papers, and preprints — compared with 12 percent from the US, per the Center for Security and Emerging Technology. These figures cover only publications with an English-language title or abstract.

China also trains a larger share of top researchers. According to a MacroPolo study, 47 percent of the world’s top 20 percent of AI researchers completed their undergraduate studies in China in 2022, up from 29 percent in 2019. The study also found that 72 percent of top AI researchers educated in China were working in the US.

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