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In AI race vs. U.S., China eyes victory in lower prices and broader appeal
Workers assemble and debug AI robots in Beijing. (Yi Haifei/China News Service/VCG/Getty Images) SINGAPORE -- In the competition for global dominance in artificial intelligence, Chinese AI leaders increasingly see themselves running a different race than their American counterparts, focused not on developing the most sophisticated capabilities, but on offering "good enough" models at cheaper prices that will proliferate more widely. In Shanghai and Hangzhou, China's AI hubs, many no longer see the "frontier" as achieving technical benchmarks, said Cherie Shi, global business manager for the Chinese AI company MiniMax, but rather "how many people in the real world are actually using our models every day." Over the past year, Chinese AI firms have gained significant ground in promoting adoption of their models by companies, governments and individual users in places from Southeast Asia to the Persian Gulf region. A government-backed AI initiative in Singapore recently chose to build its capabilities on Alibaba's Qwen. A Malaysian property conglomerate is embarking on a $20 billion "smart city" project featuring an AI research center backed by Chinese tech firms. Saudi Arabia is partnering with ByteDance and Huawei to apply AI in urban infrastructure. U.S. leaders have pitched the battle for AI preeminence as a contest over commanding the future. "Whoever leads that is going to really lead the world to a large extent. That's how big it is," President Donald Trump said earlier this month. The United States, he told reporters, is "leading China by a lot." But analysts and investors in the AI sector say that lead may be misleading -- and short-lived. "Top models may converge near the frontier, but outcomes increasingly depend on prompt quality, tools and domain integration," the JPMorganChase Center for Geopolitics said in a May report. Chinese AI labs, it added, are producing models primed to "win at adoption." After initially scrambling to get employees to incorporate AI into their work, companies are now reeling from the skyrocketing costs of AI use and seeking ways to stretch the utilization of "tokens," which are the basic units of AI data consumption. This has opened opportunities for Chinese AI firms, which offer cheaper rates for tokens and build on models that operate more efficiently, those in the industry said. Many enterprises need "a fraction of the capability" offered by leading U.S. firms like Anthropic and Open AI, said a salesperson at a leading Chinese AI firm, who spoke on the condition of anonymity because he was not authorized to speak to the press. "If we can provide 80 percent of the value at a much lower cost, that's enough. We'll take that market share." Gunja Gargeshwari, chief revenue officer for Bright Data, a Tel Aviv-headquartered tech firm providing web data for AI, said many of his company's clients are experimenting with Chinese AI. "It's undeniable," Gargeshwari said, "the cost efficiency, the token efficiency. It's amazing." Even as the U.S. government amps up its concerns over the national security risks of Chinese AI, Chinese firms "are getting a seat at the table" in many meeting rooms -- a change from just a year ago, Gargeshwari said. "Companies are not biased against China," he added. "They are very open to using the right solution for their enterprises. ... So the future is bright from that perspective for Chinese makers." In mid-June, Zixuan Li, an executive at one of the most promising Chinese artificial intelligence start-ups took to a stage at Singapore's glitzy Marina Bay Sands for a conference called SuperAI. Top U.S. companies are selling Rolls-Royces, while top Chinese firms are selling Mercedes, said Li, the director of product at Z.ai, known in China as Zhipu AI. The standing-room-only audience grasped his point: American AI is better -- for now. But Chinese products are not far behind in capability, more affordable and, eventually, likely to be far more widely sold. Restricted by the U.S. Commerce Department for alleged ties to China's military, Zhipu recently opened offices in Singapore and Dubai, and it is picking up government contracts across Asia, salespeople familiar with the deals said. Zhipu has objected to being on the Commerce Department entity list, which limits designated entities from doing business in the U.S. based on national security concerns. In a blog post last year, Open AI singled out Zhipu for its aggressive overseas expansion, writing that it was working to "lock Chinese systems and standards into emerging markets before U.S. or European rivals can." The company's marquee product is a model called GLM, which is popular among coders. As of March, the company said it had more than 4 million registered users in 218 countries. Chief scientist Tang Jie suggested GLM could match the capabilities of Anthropic's latest model, known as Fable 5, before the end of the year. The Chinese government has poured hundreds of billions into companies like Zhipu in recent years and helped them broker deals with countries along what it calls the "Digital Silk Road" to fuel the outward push on AI. The geopolitical goal is for China to "challenge the West's long-standing dominance over rule-setting" in digital technology, according to researchers at the China Academy of Macroeconomic Research and the Economic Information Network, two state-affiliated think tanks. This push is also ramping up at a time when U.S. policy toward AI diffusion seems increasingly convoluted, analysts say. In mid-June, the Trump administration blocked foreign nationals from using Anthropic's most powerful artificial intelligence models, sending stocks of Chinese AI companies, including Zhipu, soaring as much as 48 percent. Before this, Anthropic had imposed its own restrictions on how Claude, its signature large language model, could be used for military purposes, clashing publicly with the Trump administration. Users are "reasonably concerned" that access to American AI products is unreliable, said Martijn Rasser, a vice president at the Special Competitive Studies Project (SCSP), a nonpartisan initiative on tech leadership based in D.C. "It's not an attractive feature," Rasser said. At a forum in Paris last week, Alibaba's chairman, Joseph Tsai, referenced the curbs on Anthropic and called on Europe to consider China's AI offerings. "The problem is right now all your eggs are in one basket," Tsai said. "Why not choose a second basket and diversify your eggs?" White House spokesperson Liz Huston did not respond to queries on the Trump administration's clashes with Anthropic, saying only that the administration has adopted a "whole-of-government effort" to pursue AI dominance. Apart from affordability, the other major draw of Chinese AI products is that most are open-source, meaning they can be downloaded and used locally instead of over cloud-based services. This appeals to governments that want to deploy AI from local data centers that they control, said Shi at MiniMax. It also attracts entrepreneurs and start-ups handling sensitive information, such as banking details or health metrics, and users who are wary of being beholden to AI companies that can increase their prices at any point. Aleksander Mordvinov, a Russian living in Thailand, said his entire AI banking start-up was built on Qwen because he wanted data to be controlled locally. "All companies who have cloud systems sometimes have accidents where the data leaks. I can't have that," Mordvinov said. "This guy," he said, grinning as he picked up a plushie version of Qwen's capybara mascot, "this guy is what works for me." By focusing on achieving technological advances at the frontier of AI development, and neglecting the commercial application and spread of their products known as diffusion, American AI companies risk ceding "soft power and economic clout" to China that could ultimately give Beijing greater influence in shaping the global AI sector, Rasser said. If China can capture greater market share, it can also pour those profits back into advancing its tech, as it has done with solar equipment, rare earth processing, electric vehicles and other industries, said William "Chip" Usher, another SCSP analyst. But others in Washington and in Silicon Valley think it is still more worthwhile to focus on the cutting edge. Their argument, Usher said, is that there are capabilities beyond the frontier that will be transformative once achieved. Bo Bai, a Chinese-born U.S. citizen, said his Singapore-based fintech company MetaComp initially started building its AI capabilities on open-source Chinese models. But in October, Anthropic released a powerful new feature called "Skills," which allows users to teach Claude repeatable workflows. The update stunned Bo and his engineers. "We threw away everything," he said. "And then we restarted using Anthropic's Claude system."
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China's AI progress strains U.S. alliance pitch
Why it matters: Chinese models don't have to beat OpenAI or Anthropic to reshape the global AI order. They just have to be useful, available and widely adopted. Between the lines: Experts argue that two key things are kneecapping the U.S. government's desire to export American AI: * An erratic export controls strategy that involves making decisions about access to advanced models on the fly. * Not paying sufficient attention to China's efforts to spread its open-source AI models abroad while deploying AI at scale across manufacturing, health care and other industries domestically. Driving the news: The State Department this week expanded its Pax Silica initiative, an effort to build a U.S.-led AI and chip supply-chain bloc and reduce reliance on Chinese technology. * The move came as the AI industry continues to grapple with the fallout of the government's decision to put export controls on Anthropic's newest AI models. * Meanwhile, Chinese AI is closing the capability gap, as Axios' Sam Sabin has reported, and the models are much cheaper. What they're saying: "I think we're seeing another example of the Huawei strategy in the context of open-source AI models," Emily Weinstein, a former Commerce Department staffer now at the U.S.-China Economic and Security Review Commission, told Axios. * "China is able to offer not even just the models, but often the underlying or associated infrastructure at either no cost or significantly lower cost," said Weinstein during a panel discussion held by the Center for a New American Security this week. * Widespread adoption of Chinese AI in the Global South could create a "Huawei model on steroids" where countries are reliant on Chinese infrastructure that is not interoperable with the U.S., Weinstein said. Following the Anthropic decision, "the entire industry is kind of frozen in place, waiting for something that seems kind of more coherent," CNAS' Daniel Remler, a former State Department technology adviser, said during the panel. * "That's concerning when the Chinese are trying to move as fast as possible," he said. * "You're seeing many more calls now for AI sovereignty. I think it will mean that much of the rest of the world will likely, at least on the margin, prefer Chinese open-weight models" over U.S. frontier models, said Saif Khan, former counselor for critical and emerging technologies to the Secretary of Commerce. Yes, but: The Trump administration is trying to counter that trend by getting allies on board with American AI instead. * This week, undersecretary of state for economic affairs Jacob Helberg announced that 35 countries signed the "Declaration on AI Opportunity" as part of Pax Silica. * Helberg also criticized digital sovereignty -- the push for homegrown AI infrastructure -- as "backward and counterproductive" and "synchronized mediocrity." Reality check: Some U.S. partners are walking a tightrope, embracing the administration's vision while also pursuing greater technological sovereignty. * The European Union notably touted the importance of digital sovereignty following the Anthropic decision. * In an interview with Axios while in Washington for government meetings and the Pax Silica event, Omran Sharaf, the United Arab Emirates' assistant foreign minister for advanced science and technology, said the country's goal is achieving "strategic autonomy through international collaboration with trusted partners." * "For the U.S. to be able also to maintain its global position, its economic weight and posture, even national security, it's important for the U.S. to be able to have their technology deployed around the world," Sharaf said. * Sharaf added that it's "too early to tell" what export control decisions like the Anthropic directive will mean for that goal. The bottom line: The next challenge for the U.S. isn't just staying out front on frontier AI. It's convincing the rest of the world to keep building on American AI.
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Chinese AI companies are redefining the US China AI race by prioritizing widespread adoption through affordable models rather than technical superiority. Firms like Zhipu AI and Alibaba are gaining contracts across Asia and the Middle East, offering 80% of leading US capabilities at significantly lower costs while US export restrictions create market openings.
The global AI landscape is witnessing a strategic shift as China AI leaders abandon the pursuit of technical supremacy in favor of a pragmatic approach centered on affordability and widespread deployment. Chinese AI firms are no longer fixated on matching the sophisticated capabilities of American counterparts like OpenAI and Anthropic. Instead, they're building their competitive advantage on low-cost AI models that deliver what industry insiders describe as "good enough" performance at prices that make them accessible to a broader range of enterprise needs
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.Cherie Shi, global business manager for Chinese AI company MiniMax, explained that in Shanghai and Hangzhou—China's AI hubs—the frontier is no longer defined by technical benchmarks but by "how many people in the real world are actually using our models every day"
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. This philosophy is already yielding tangible results. A government-backed AI initiative in Singapore recently selected Alibaba's Qwen model to build its capabilities. Meanwhile, a Malaysian property conglomerate is launching a $20 billion smart city project featuring an AI research center backed by Chinese tech firms, and Saudi Arabia is partnering with ByteDance and Huawei to integrate AI into urban infrastructure1
.The economic calculus behind China's advancements in AI is compelling for businesses grappling with skyrocketing AI implementation costs. A salesperson at a leading Chinese AI firm noted that many enterprises need only "a fraction of the capability" offered by leading US firms. "If we can provide 80 percent of the value at a much lower cost, that's enough. We'll take that market share," the salesperson said
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. Gunja Gargeshwari, chief revenue officer for Tel Aviv-based Bright Data, confirmed this trend, stating that many of his company's clients are experimenting with Chinese AI. "It's undeniable, the cost efficiency, the token efficiency. It's amazing," Gargeshwari said, adding that Chinese AI firms "are getting a seat at the table" in corporate meeting rooms—a significant change from just a year ago1
.Source: Washington Post
Zhipu AI, one of China's most promising startups, exemplifies this approach. At a Singapore conference, company executive Zixuan Li described the competitive landscape using an automotive analogy: top US companies are selling Rolls-Royces while Chinese firms offer Mercedes—slightly less prestigious but more affordable and likely to achieve far wider adoption
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. Despite being restricted by the US Commerce Department for alleged ties to China's military, Zhipu recently opened offices in Singapore and Dubai and is securing government contracts across Asia. The company's GLM model is particularly popular among coders, with more than 4 million registered users in 218 countries as of March1
.The US China AI race is increasingly complicated by geopolitical tensions and what experts describe as an erratic export controls strategy. The State Department recently expanded its Pax Silica initiative to build a US-led AI and chip supply-chain bloc, but the effort comes as the AI industry grapples with fallout from the government's decision to impose export controls on Anthropic's newest models
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. Emily Weinstein, a former Commerce Department staffer now at the US-China Economic and Security Review Commission, warned of a "Huawei model on steroids" where countries become reliant on Chinese infrastructure that isn't interoperable with US systems2
.Daniel Remler, a former State Department technology adviser at the Center for a New American Security, observed that following the Anthropic decision, "the entire industry is kind of frozen in place, waiting for something that seems kind of more coherent. That's concerning when the Chinese are trying to move as fast as possible"
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. The uncertainty is driving many countries toward digital sovereignty and technological autonomy, with growing preference for Chinese open-weight models over US frontier AI systems, particularly in the Global South2
.The Trump administration is attempting to counter Chinese expansion through diplomatic efforts. Undersecretary of state for economic affairs Jacob Helberg announced that 35 countries signed the "Declaration on AI Opportunity" as part of Pax Silica, while criticizing digital sovereignty as "backward and counterproductive" and "synchronized mediocrity"
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. However, US partners are walking a delicate balance. The European Union emphasized digital sovereignty following the Anthropic decision, and the United Arab Emirates' assistant foreign minister Omran Sharaf stated his country's goal is achieving "strategic autonomy through international collaboration with trusted partners"2
. The JPMorganChase Center for Geopolitics noted in a May report that while top models may converge near the frontier, "outcomes increasingly depend on prompt quality, tools and domain integration," with Chinese AI labs producing models primed to "win at adoption"1
. This suggests the next challenge for the US isn't just maintaining its lead in frontier AI capabilities—it's convincing the rest of the world to keep building on American AI infrastructure.Summarized by
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