te complex tasks with minimal prompting, that almost rival leading US offerings at a fraction of the cost, in what some experts are calling a “mini DeepSeek moment.” It has quickly climbed the usage charts on third-party AI developer platforms like OpenRouter, where it now ranks above Anthropic’s models, while executives ranging from Snowflake CEO Sridhar Ramaswamy to venture capitalist Marc Andreessen have lauded its abilities. “We now have a Chinese open-weight model that is as good as the currently available models from OpenAI and Anthropic,” said David Sacks, US President Donald Trump’s former AI czar, last week before Washington lifted curbs on Anthropic’s Fable and Mythos models on Tuesday. Those capabilities have put Z.ai’s GLM-5.2 model at the heart of a growing debate about whether China is finally catching up to the US in the AI race, as technology executives warn that Washington’s unpredictable regulation of the industry risks hampering its lead in the frontier technology. “It is just a tick below Opus 4.8 (from Anthropic) and right up there with GPT 5.5 (from OpenAI),” Sacks said of GLM-5.2 on the All-In podcast, adding that “we cannot afford to do things that slow our companies down.” The Anthropic curbs and the delayed public rollout of OpenAI’s latest GPT-5.6 model have fueled global demand for the Chinese model, some experts said. “The international developer community is increasingly aware that relying solely on proprietary, US-based API models carries significant risk,” said Brian Tse, founder and CEO of Concordia AI, a Beijing-based consultancy focused on AI safety. GLM-5.2’s positive global reception also suggests increased interest in cheaper open-source development because businesses are getting stung by the rising and often unpredictable costs of using AI to complete tasks, as closed-source agentic AI tools consume more tokens, the units used to measure AI usage. Z.ai, also known as Zhipu AI, declined to comment. Anthropic and OpenAI did not immediately respond to requests for comment. GLM-5.2 currently holds fifth place on Artificial Analysis’ large language model (LLM) intelligence leaderboard, which ranks performance across a range of benchmarks designed to measure overall capability, including reasoning and coding skills. It is also in second place on Code Arena’s front-end coding rankings, measuring how well models generate websites and front-end applications, while operating at roughly a sixth of the cost of closed US frontier models like Claude and the GPT series. Z.ai has not disclosed how much it spent to develop GLM-5.2. In a reply to Elon Musk on X last month, Z.ai founder Tang Jie said the Chinese startup could produce a model on par with Anthropic’s Fable before the first quarter of next year. “The shift GLM-5.2 brings is that the open-source model has become a plug-and-play, out-of-the-box product,” said Tiezhen Wang, former Apac lead at Hugging Face, a startup that serves as a hub for developers tinkering with open-source models. “You just deploy the model and, without doing any complex fine-tuning systems, it is in a highly usable, ready-to-use state. This drastically lowers the barrier to entry for open-source adoption.” Convincing American businesses One major hurdle to GLM-5.2’s large-scale adoption remains data security concerns that have limited use of Chinese models by US enterprises, particularly in regulated industries like banking and cybersecurity. The migration and upgrading of enterprise AI systems typically takes several months, Wang said. “I have seen some discussion among European companies about whether it could be used in enterprise settings,” said Wei Sun, principal AI analyst at Counterpoint Research. “In the EU and US, some clients, partners, and regulated industries may simply be unwilling to accept Chinese models in their AI stack, regardless of technical performance or price.” A report earlier this year by non-profit RAND, based on website traffic data across 135 countries, found that Chinese LLMs’ global market share jumped to 13 per cent from 3 per cent in the two months after DeepSeek launched its R1 model in January last year. The release sparked a global tech sell-off because it contrasted DeepSeek’s low cost with massive AI infrastructure spending elsewhere. China’s LLM usage gains were most pronounced in developing countries and those with close political and economic ties to Beijing. Some experts said concerns about the safety of Chinese AI models were overblown, arguing that running them on US cloud providers or on a company’s own servers ensured data security. While major corporations are slow to migrate, tech startups and small and medium-sized enterprises are moving much faster. “Developers tend to care less about where a model comes from than whether it works, how much it costs, and whether they can deploy or access it reliably,” said Poe Zhao, China tech analyst and founder of the Hello China Tech newsletter. “The likely pattern is partial routing, not overnight replacement of OpenAI or Anthropic. So yes, it is a mini DeepSeek moment, but in a narrower, developer-centric sense.” Reporting by Laurie Chen in Beijing and Aditya Soni in Bengaluru. Editing by Eduardo Baptista and Thomas Derpinghaus. All courtesy of Reuters.