A ‘mini DeepSeek moment’ for Chinese AI
GLM-5.2 sparks debate over whether China is closing the gap with OpenAI and Anthropic.
Since DeepSeek shocked markets early last year with its low-cost but powerful AI model, global users have faced a growing choice: Chinese AI systems offering lower prices but often weaker capabilities, or Western rivals such as OpenAI and Anthropic, which have invested billions in development.
A model called GLM-5.2, launched last month by Beijing-based startup Z.ai, may be narrowing that gap in terms of global interest.
GLM-5.2 has generated significant attention in Silicon Valley for its coding and “agent” capabilities, its ability to execute complex tasks with minimal prompting, which in some cases rival leading U.S. models at a fraction of the cost, in what some experts are calling a “mini DeepSeek moment.”
It has quickly climbed usage rankings on third-party AI developer platforms such as OpenRouter, where it now ranks above Anthropic’s models. Executives ranging from Snowflake CEO Sridhar Ramaswamy to venture capitalist Marc Andreessen have praised its performance.
“We now have a Chinese open-weight model that is as good as the currently available models from OpenAI and Anthropic,” said David Sacks, former White House AI adviser, last week before Washington lifted restrictions on Anthropic’s Fable and Mythos models on Tuesday.
Those capabilities have placed Z.ai’s GLM-5.2 at the center of a growing debate over whether China is finally catching up to the U.S. in the AI race, as technology executives warn that Washington’s unpredictable regulation risks slowing America’s lead in frontier AI.
“It is just a tick below Opus 4.8 (from Anthropic) and right up there with GPT-5.5 (from OpenAI),” Sacks said on the All-In podcast, adding that “we cannot afford to do things that slow our companies down.”
Restrictions on Anthropic models and the delayed public rollout of OpenAI’s latest GPT-5.6 have further fueled global interest in the Chinese model, some experts said.
“The international developer community is increasingly aware that relying solely on proprietary, U.S.-based API models carries significant risk,” said Brian Tse, founder and CEO of Concordia AI, a Beijing-based AI safety consultancy.
GLM-5.2’s reception also reflects growing demand for cheaper and more open-source alternatives, as businesses face rising and often unpredictable costs from closed models that consume large volumes of 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 ranks fifth on Artificial Analysis’ large language model (LLM) leaderboard, which evaluates models across benchmarks including reasoning and coding. It also holds second place in Code Arena’s front-end coding rankings, which measure how well models generate websites and applications, while operating at roughly one-sixth the cost of closed U.S. frontier models such as Claude and OpenAI’s GPT series.
Z.ai has not disclosed how much it spent developing 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 comparable to Anthropic’s Fable before the first quarter of next year.
“The shift GLM-5.2 brings is that open-source models have become a plug-and-play, out-of-the-box product,” said Tiezhen Wang, former APAC lead at Hugging Face.
“You can deploy the model without complex fine-tuning systems, and it is already in a highly usable, ready-to-use state. This drastically lowers the barrier to entry for open-source adoption.”
One major hurdle to GLM-5.2’s large-scale adoption remains data security concerns, which have limited the use of Chinese models by U.S. enterprises, particularly in regulated industries such as banking and cybersecurity. Migration and integration of enterprise AI systems typically take 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 U.S., some clients 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 nonprofit RAND, based on website traffic data across 135 countries, found that Chinese LLMs’ global market share rose to 13% from 3% in the two months after DeepSeek launched its R1 model in January last year. The release triggered a global tech selloff due to the contrast between DeepSeek’s low cost and the massive infrastructure spending elsewhere in AI.
Usage gains for Chinese LLMs were most pronounced in developing countries and in nations with close political and economic ties to Beijing.
Some experts argue that concerns over Chinese AI safety are overstated, noting that running models on U.S. cloud providers or on-premise servers can mitigate data risks. While large corporations are slow to adopt, startups and small and medium-sized enterprises are moving more quickly.
“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 an overnight replacement of OpenAI or Anthropic. So yes, it is a mini DeepSeek moment, but in a narrower, developer-centric sense.”
