Faced with less compute and fewer tokens, Chinese AI labs are tightening the gap with the U.S. by just being more efficient

The race between the world’s two biggest economies to dominate AI recently escalated with new accusations and raised the question of how China came to rival the U.S.’s AI capabilities.

Six Chinese AI companies, U.S. officials alleged earlier this week, found a shortcut to closing the gap with American AI labs by buying bulk subscriptions to their American rivals and then training on the outputs.

The FBI, the National Security Agency, and the Cybersecurity and Infrastructure Security Agency said Tuesday that DeepSeek, Moonshot, and four others extracted “capabilities worth billions” in this way since 2024, a method the agencies claimed let DeepSeek understate its $5.6 million training cost.

China’s foreign affairs ministry said the country’s AI development “is a result of high-level scientific and technological self-reliance” and called the accusations “groundless.” The allegations are one potential explanation for why Chinese AI models are estimated to be neck-and-neck with their U.S. counterparts, with a report from Stanford putting Anthropic’s top model ahead of DeepSeek’s by just 2.7% earlier this year.

But analysts say there’s a different advantage Chinese labs developed to compete: squeezing out more value from limited resources.

More value for fewer tokens There’s a technique Chinese labs perfected that stems from “attention,” the mechanism Google researchers introduced in a landmark 2017 paper that underlies every large language model.

Attention is what lets a model look at each piece of text in relation to all the others and decide which connections matter most.

That helps it understand context, but it gets computationally more expensive the longer the context window gets.

Brendan Burke, the semiconductors and supply chain analyst at tech research firm Futurum Group, told Fortune that Chinese labs figured out a shortcut to make the attention mechanism cheaper and more efficient.

“Chinese labs found algorithms that reduce the complexity of those calculations by an order of magnitude, and then achieve better results because they’re able to summarize the most relevant tokens,” he said.

Necessity was the mother of invention, as the U.S. restricted China’s access to Nvidia’s best chips , pushing it toward domestic alternatives like Huawei , which limited China’s access to the highest-performing compute available in the U.S.

Meanwhile, the U.S. has 74% of the world’s compute, according to a White House report , and it also has hyperscalers pouring billions into generating more through data centers.

“Because they had less compute to work with, they found that computationally efficient method instead of just throwing more compute at an inefficient technique, as U.S. labs initially did,” Burke said about China.

By contrast, U.S.