Mr Trump’s hosting the next day of the launch of “the largest AI infrastructure project in history” shows he grasps the potential. But so does the rest of the world—and most of all, China. Even as Mr Trump was giving his inaugural oration, a Chinese firm released the latest impressive large language model (LLM). Suddenly, America’s lead over China in AI looks smaller than at any time since ChatGPT became famous.
China’s catch-up is startling because it had been so far behind—and because America had set out to slow it down. Joe Biden’s administration feared that advanced ai could secure the Chinese Communist Party (CCP) military supremacy. So America has curtailed exports to China of the best chips for training ai and cut off China’s access to many of the machines needed to make substitutes. Behind its protective wall, Silicon Valley has swaggered. Chinese researchers devour American papers on ai; Americans have rarely returned the compliment.
Yet China’s most recent progress is upending the industry and embarrassing American policymakers. The success of the Chinese models, combined with industry-wide changes, could turn the economics of AI on its head. America must prepare for a world in which Chinese AI is breathing down its neck.
China’s LLMs are not the very best. But they are far cheaper to make. QwQ, owned by Alibaba, an e-commerce giant, was launched in November and is less than three months behind America’s top models. DeepSeek, whose creator was spun out of an investment firm, ranks seventh by one benchmark. It was apparently trained using 2,000 second-rate chips—versus 16,000 first-class chips for Meta’s model, which DeepSeek beats on some rankings. The cost of training an American LLM is tens of millions of dollars and rising. DeepSeek’s owner says it spent under $6m.
American firms can copy DeepSeek’s techniques if they want to, because its model is open-source. But cheap training will change the industry at the same time as model design is evolving. China’s inauguration-day release was DeepSeek’s “reasoning” model, designed to compete with a state-of-the-art offering by OpenAI. These models talk to themselves before answering a query. This “thinking” produces a better answer, but it also uses more electricity. As the quality of output goes up, the costs mount.
The result is that, just as China has brought down the fixed cost of building models, so the marginal cost of querying them is going up. If those two trends continue, the economics of the tech industry would invert. In web search and social networking, replicating a giant incumbent like Google involved enormous fixed costs of investment and the capacity to bear huge losses. But the cost per search was infinitesimal. This—and the network effects inherent to many web technologies—made such markets winner-takes-all.
If good-enough AI models can be trained relatively cheaply, then models will proliferate, especially as many countries are desperate to have their own. And a high cost-per-query may likewise encourage more built-for-purpose models that yield efficient, specialised answers with minimal querying.
The other consequence of China’s breakthrough is that America faces asymmetric competition. It is now clear that China will innovate around obstacles such as a lack of the best chips, whether by efficiency gains or by compensating for an absence of high-quality hardware with more quantity. China’s homegrown chips are getting better, including those designed by Huawei, a technology firm that a generation ago achieved widespread adoption of its telecoms equipment with a cheap-and-cheerful approach.
If China stays close to the frontier, it could be the first to make the leap to superintelligence. Should that happen, it might gain more than just a military advantage. In a superintelligence scenario, winner-takes-all dynamics may suddenly reassert themselves. Even if the industry stays on today’s track, the widespread adoption of Chinese AI around the world could give the ccp enormous political influence, at least as worrying as the propaganda threat posed by TikTok, a Chinese-owned video-sharing app whose future in America remains unclear.
What should Mr Trump do? His infrastructure announcement was a good start. America must clear legal obstacles to building data centres. It should also ensure that hiring foreign engineers is easy, and reform defence procurement to encourage the rapid adoption of ai.
Some argue that he should also repeal the chip-industry export bans. The Biden administration conceded that the ban failed to contain Chinese AI. Yet that does not mean it accomplished nothing. In the worst case, AI could be as deadly as nuclear weapons. America would never ship its adversaries the components for nukes, even if they had other ways of getting them. Chinese AI would surely be stronger still if it now regained easy access to the very best chips.
Agencies or agency
More important is to pare back Mr Biden’s draft “AI diffusion rule”, which would govern which countries have access to American technology. This is designed to force other countries into America’s ai ecosystem, but the tech industry has argued that, by laying down red tape, it will do the opposite. With every Chinese advance, this objection becomes more credible. If America assumes that its technology is the only option for the likes of India or Indonesia, it risks overplaying its hand. Some tech whizzes promise the next innovation will once again put America far in front. Perhaps. But it would be dangerous to take America’s lead for granted.
For subscribers only: to see how we design each week’s cover, sign up to our weekly Cover Story newsletter.
© 2025, The Economist Newspaper Limited. All rights reserved. From The Economist, published under licence. The original content can be found on www.economist.com