When Chinese company DeepSeek released its open-source R1 model in January 2025, it made headlines around the world. The large language model (LLM) was reported to rival some of the most powerful AIs from US companies, but it was completely free for anyone to download. A trillion dollars was wiped off the value of US tech companies and US lawmakers on government devices.
When another Chinese firm, Z.ai, released GLM-5.2 last month, there were similar claims about performance but, surprisingly, none of the panic. The AI arms race between the US and China appears to have taken an unexpected turn.
The US and China have been racing to develop a stream of new, more capable AI models, and to create the chips and data centres necessary to train and run them. The US government has also introduced and strengthened export controls on chips to countries like China in recent years, as well as switching on and off .
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Proponents believe the technology can revolutionise everything from drug discovery to materials science, potentially giving economies a shot in the arm. Its increasing use in war to select targets and deploy weapons means it has become a matter of national security too. There is even talk from US President Donald Trump of taking a to ensure their goals align.
However, the way the US and China are approaching it is very different. Chinese firms tend to release models so that users can download and run them locally, at no cost, which is in stark contrast to how most US firms host them in the cloud, provide access for a fee and closely guard their inner workings.
Open-source AIs, including those from China, don’t tend to perform quite as well as the most expensive premium models, but many people find them adequate. As one UK software developer told 91av: “I used a local model [from Z.ai] and a cloud model [from OpenAI] for the same task – it took 30 per cent longer with local, but was fully free.”
Soon after Z.ai released GLM-5.2 last month it was ranked the most intelligent open-source AI available on the market by , an AI benchmarking company. Z.ai says that it outperforms OpenAI’s GPT-5.5 on a common benchmark used to test AI software engineering skills. However, Artificial Analysis found that GLM-5.2 performed slightly worse than on its intelligence tests – symptomatic of a problem across the AI industry where there are no standard tests of performance.
Nevertheless, it appears GLM-5.2 is finding an audience. It currently ranks as the , which captures only a tiny fraction of AI use but is one of the few public sources of such data. DeepSeek’s latest model sits at the number one spot with more than twice as much use. Seven of the top 10 are AIs built by Chinese companies.
New normal
That GLM-5.2 didn’t cause the economic shock waves that DeepSeek’s previous model did is perhaps testament to how quickly we can adapt to the idea that China has simply caught up on AI, just as it has done dozens of times over with other technology like smartphones, electric cars and robotics.
“It traditionally has been the case that Silicon Valley has been more innovative and China has been a fast follower that scales very effectively,” says at the University of Copenhagen, Denmark. “And there’s this new dimension to that, which involves the aggressive open-source aspect – kind of attempting to shame the closed-model frontier labs and really put pressure on the West in that regard.”
at the University of California, San Diego, says that Chinese open-source models are highly capable – perhaps equivalent to the best US models from six to nine months ago – and may even be more stable. American models can be withdrawn or modified at any time, whereas Chinese models can be run by anyone with a sufficiently powerful server, he says.
at Imperial College London says the company that ends up dominant in AI is likely to benefit from a £60 trillion market, but there are political and tactical benefits for governments in taking part in the race too. “The Chinese models give you different answers to certain questions about political or other sensitive subjects than the US models,” says Shrier.
The US could play into China’s hands if it continues to react to new US models with market-leading performance by withdrawing foreign access. “It could actually be counterproductive because you’re forcing people to develop their own ecosystems and own technology,” says at the University of Oxford. “You saw it with Huawei and Android: cut them off from Google’s ecosystem and they built their own.”
Shrier is concerned that China can continue to narrow the performance gap between its own models and those from the US by picking apart how Western models operate just as . “What this means from a practical perspective is that any US advantage gets eroded rapidly,” says Shrier.
What may save the large US firms in this race is the inertia and caution of business – red tape, says Belongie. Chinese open-source models might be free, run on a laptop and do a decent job, but for big companies with IT departments, risk analysts and cautious boards, a Chinese model downloaded from the internet feels like an unmanageable risk. That’s where the big, established technology firms that already supply industry-standard email, office and support software may be well placed.
“Why is it that Microsoft is so successful in the enterprise and so many universities and companies use it? It’s not because they have the best technology, but they really speak that language of compliance,” says Belongie.
Torr says Europe, lacking the AI activity of China and the US, is sleepwalking into a national security problem more serious than the nuclear arms race. AI is, he believes, the single most important technology that the human race has ever developed.
“We need to have our own Microsofts and Googles, and big tech firms within Europe, within European legislation, paying European taxes, to level the playing field,” says Torr. “Do we want to be an AI colony, totally dependent on systems which we don’t necessarily have full control over, or do we want to run our own?”
