United States President Donald Trump and China’s President Xi Jinping are set to meet in Washington, DC on Thursday for a summit that is expected to cover trade, artificial intelligence (AI), Taiwan and the US-Israel war on Iran.
In advance of the talks, US Treasury Secretary Scott Bessent said Washington had proposed an AI “notification mechanism” with China – effectively a hotline to alert each other when AI incidents threaten national security.
The meeting comes as leading AI companies warn about the technology’s risks, while both superpowers push to accelerate their AI race. In this visual explainer, Al Jazeera compares the US and China’s AI strength in computing power, AI models, spending and research.
Who has more computing power?
Training and running AI requires enormous amounts of computing power. The more powerful chips and computers a country has, the faster it can build and improve AI models, making computing power one of the biggest advantages in the AI race.
Computing power is measured in FLOP/s (floating-point operations per second) – or how many calculations a computer can perform in one second.
Adding up the computing power of all the AI chips a country has gives a sense of its total AI capacity. By that measure, the US is well ahead, accounting for nearly three-quarters of the world’s total AI computing power, while China holds just more than 14 percent, according to Epoch AI, an AI research institute.
The US lead comes largely from its access to the most advanced chips. US company Nvidia accounts for more than 60 percent of global AI computing capacity among major chip designers, while China’s Huawei holds a much smaller, but growing share, according to Stanford University’s 2026 AI Index.
Those chips also need somewhere to run. The US has more than 5,400 data centres – the large buildings which house thousands of computers – about 10 times as many as any other country. It also leads in dedicated AI data centres, with 84, more than the next eight countries combined.
Whose AI models are people using?
Frontier models are the most advanced AI systems, such as OpenAI’s GPT, Anthropic’s Claude and DeepSeek’s models in China. They are trained using vast amounts of data and computing power to write, reason and code.
The US has led the development of these models, but Chinese models are gaining ground.
As of March 2026, US and Chinese AI models were closely matched on Arena, a leaderboard where users compare two anonymous models and vote for the better answer. US companies Anthropic, xAI, Google and OpenAI ranked near the top, alongside China’s Alibaba and DeepSeek.
On OpenRouter, a platform that ranks AI models by real-world use, Chinese models dominate the leaderboard. Models from Chinese companies DeepSeek, Z.ai and Tencent hold the top three spots on OpenRouter by tokens processed, the units of text that AI models read and generate.
This is partly because Chinese models are cheaper to use. Many are also open-weight, meaning developers can download, adapt and run them themselves.
Chinese models can now compete with US ones in many real-world tasks, with Chinese AI models “months, not years, behind US frontier models”, according to a July analysis by the Centre for Strategic and International Studies (CSIS).
In May, the US government’s Center for AI Standards and Innovation (CAISI) estimated that DeepSeek V4 Pro, released in April, was about eight months behind leading US models.
Who is spending more?
The US is spending far more than China on the infrastructure needed to build AI, giving its tech companies a significant advantage in the race for computing power.
Goldman Sachs estimates that US hyperscalers, the giant tech companies that run large-scale cloud computing and data centres, will spend about $764bn in 2026. That includes Amazon, Microsoft, Google, Meta and Oracle. By comparison, China’s Alibaba, Tencent, Baidu and ByteDance are expected to spend $102bn.
But China’s spending is increasing 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 growth of 76 percent for US hyperscalers, according to the news agency Reuters.
The spending gap reflects 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 remains a magnet for the world’s top 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, according to the Center for Security and Emerging Technology. The figures only cover publications with an English-language title or abstract.
China also trains more top researchers. According to a study by MacroPolo, 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 the top AI researchers educated in China were working in the US.
