Chinese-built AI models are gaining traction among U.S. companies as they narrow the performance gap with leading American rivals while remaining significantly cheaper to use.
Recent model releases from Chinese companies, including DeepSeek and Z.ai, are seen by many as highly competitive compared to leading frontier systems from the likes of Anthropic and OpenAI. Those advances in capability come as token prices for the most advanced models rise at many U.S. AI labs, leaving companies grappling with unexpectedly high costs associated with using the tech.
The share of tokens used by U.S. companies on Chinese AI models via OpenRouter — a platform that enables developers to access a range of AI models — has sat above 30% each week since Feb. 8, with that figure rising as high at 46%. The average across the previous 12 months was just 11%, falling to 4.5% in the first half of 2025.
The rise of Chinese open source and open weight models comes as the U.S. administration increasingly looks to regulate its most powerful AI models and considers how to halt the rapid adoption of alternatives from overseas.
At the end of June, OpenAI said it would limit the rollout of a new set of models on the government’s request. Export controls on Anthropic’s Mythos and Fable models were also lifted that month, after a tense standoff between the Trump administration and the company.
“Chinese AI models are particularly attractive to American companies now as AI costs skyrocket,” Kyle Chan, fellow in the John L. Thornton China Center at think tank Brookings, told CNBC. “Where previously U.S. companies were prioritizing AI adoption regardless of model, now they’re getting more cost-conscious.”
Rising adoption
As companies look to deploy AI models to create new products and bring internal efficiencies, engineers are increasingly experimenting with cheaper open source and open weight models, of which the most capable are made by Chinese companies.
Open-source and open-weight models make different parts of an AI model available for developers to inspect, use and sometimes modify. They differ from closed systems, like many flagship models produced by OpenAI, Anthropic and Google, where code and inner workings remain proprietary.
In June, AI startup Lindy moved 100% of its traffic from Anthropic’s Claude models to DeepSeek, a Chinese company which burst onto the scene with a bombshell release in early 2025 and launched a new model in April.
“We did it, and you could see that cost curve go down, like, crash to the ground,” CEO Flo Crivello told CNBC. He said the decision will save Lindy millions of dollars within months.
DeepSeek saw its share of gateway tokens climb between May and June on Vercel, a platform that allows developers to deploy and run apps and websites.
Z.ai’s GLM 5.2 was released to great fanfare in June and saw the fastest adoption of any model tracked by Vercel in 2026, Harpreet Arora, head of agentic infrastructure at Vercel, told CNBC. “In its first full week after launch, daily token volume grew about 27x and the number of customers using it grew about 80x.”
“Price is doing the work here,” Arora said. “When a task doesn’t need the best model, teams are beginning to route it to the cheapest one that’s good enough, and the recent wave of models coming out of China is winning that trade.”
Open source Chinese models can be “60% to 90% cheaper” than the leading Anthropic and OpenAI models, Justin Summerville, who works on data and analytics at OpenRouter, told CNBC.
OpenAI and Anthropic have been approached for comment.
While Claude and ChatGPT still dominate in terms of usage on LaunchLemonade, an AI agent platform for regulated industries, GLM 5.2 is now in the top five models on the platform, LaunchLemonade CEO and founder Cien Solon told CNBC.
“Chinese models like Z.ai and [Alibaba‘s] Qwen are becoming options for companies [as] they offer an attractive combination of performance and cost for specific workloads,” Cien said. “Businesses with more mature AI strategies are increasingly willing to use them where they make technical or commercial sense.”
Approaching the frontier
The performance of Chinese AI models is also increasing.
While often a “fraction of the cost” of U.S. rivals, they operate “close to the top American frontier models,” said Brookings’ Chan, estimating that they are currently “six to nine months” behind top U.S. rivals.
“The new open source models are performing well and prove capable for all but the most complex LLM tasks,” Summerville said.
GLM 5.2 landed within a percentage point of Anthropic’s Opus 4.8 on one closely watched agentic benchmark, at roughly a fifth of the cost. Some researchers have said GLM 5.2 can perform on par with top U.S. labs on some cyber benchmarks.
Switching to DeepSeek V4 increased performance on many core use cases for Lindy, Crivello said in a post on X.
“We’re seeing companies increasingly motivated to turn to cheaper AI stacks they can control and adapt themselves, and given the state of open-source and open-weight models that often means leveraging Chinese options,” Yacine Jernite, head of machine learning at Hugging Face, told CNBC.
“There is a real risk that users get stuck having to choose between performant but expensive US proprietary models whose price and accessibility can quickly fluctuate, or using Chinese models as the only feasible alternative whenever they want to control costs or own their AI stack.”
