By Laurie Chen<\/p>\n
BEIJING, June 25 (Reuters) – Chinese AI startup Z.ai said on Thursday it plans to use domestic listing proceeds to fund a quest for artificial general intelligence, after its latest model scored close to leading U.S. models from Anthropic and OpenAI on public \u200cbenchmarks.<\/p>\n
Z.ai’s flagship GLM-5.2 model, released a day after Anthropic disabled worldwide access to its most advanced models, stunned global users after its performance benchmarks \u200cnarrowly trailed leading closed-source models.<\/p>\n
“Our mission is to obtain AGI, so right now our focus is how to improve our model to achieve the upper bound of intelligence. So all these resources \u200bare helping us,” said Qinkai Zheng, technical lead of the firm’s CodeGeeX team.<\/p>\n
The accompanying surge in investor interest sent shares rallying more than 2,000% from their blockbuster Hong Kong debut in January, to cross a threshold of HK$1 trillion ($128 billion) in market capitalisation this week.<\/p>\n
“This model is comparable to the top closed models,” Zheng told reporters at its head office in Beijing.<\/p>\n
“It’s the first time that an open-source model really delivers very solid coding and agent performance that can compare with the leading proprietary \u200cAI companies like Anthropic and OpenAI.”<\/p>\n
GLM-5.2 now holds fourth \u2060place on Artificial Analysis’ LLM intelligence leaderboard and the second spot on Code Arena’s front-end coding leaderboard, operating at roughly a sixth of the cost of closed U.S. frontier models.<\/p>\n
The sudden “unplugging” of closed U.S. frontier models has unleashed severe anxiety among global \u2060allies such as Canada and France, whose leaders heavily criticised over-reliance on U.S.-controlled AI infrastructure at a G7 summit last week.<\/p>\n
For the first time a Chinese open-source AI model has come close to bridging the frontier gap with heavily-funded Western AI labs, after previously surpassing U.S. open-source models such as Google’s Gemma and Meta’s Llama series despite constraints \u200bon \u200bcomputing power.<\/p>\n
Analysts previously estimated that the performance capabilities of top Chinese AI models were four \u200bto six months behind leading U.S. models.<\/p>\n
Z.ai, also known as Zhipu \u200cAI, said this month it plans a dual listing in the commercial hub Shanghai but did not disclose how much it aimed to raise.<\/p>\n
SPECIALISING IN CODING, COMPLEX TASKS<\/p>\n
Specialising in coding and complex long-horizon tasks, the model has 750 billion total parameters and a massive 1-million token context window.<\/p>\n
It was released with inference adaptation to a wide variety of domestic chip infrastructure users, including Huawei Ascend clusters, the company said in a blog post.<\/p>\n
Since February, Z.ai’s GLM-5 series has been adapted to run on domestic semiconductors after the U.S. tightened China’s access to advanced Nvidia chips.<\/p>\n
“We are trying our best to improve our infrastructure and to make the \u200cmodel more efficient on different kinds of chips,” said Zheng, without disclosing whether it was \u200btrained on domestic or foreign chips.<\/p>\n
Despite fierce domestic price competition, Z.ai has successfully hiked prices \u200bfor its frontier models multiple times this year, reflecting its strong enterprise \u200badoption in China, where it is also widely used in public sector procurement.<\/p>\n
In a post on X, co-founder Tang Jie emphasised \u200cZ.ai’s commitment to open-source and described the abrupt pulling of \u200bAnthropic’s Fable and Mythos models as “deeply regrettable”.<\/p>\n
JP \u200bMorgan projected the firm’s revenue to balloon by this year and for it to turn profitable in 2028 – but Z.ai only earns a fraction of the revenue of its U.S. counterparts, stock exchange filings show.<\/p>\n
“We are trying to lower the cost, but because the demand is too large, maybe \u200bin the future we will still need to increase \u200cthe price,” said Zheng. “But we want the model accessible to everyone.”<\/p>\n
Zheng said that the company would target long-horizon tasks and self-evolving autonomous agent \u200bsystems in future models.<\/p>\n
Its next GLM-5.5 model is expected to be released in August and could become the next key milestone in \u200bChinese frontier AI.<\/p>\n
($1=7.8397 Hong Kong dollars)<\/p>\n
(Reporting by Laurie Chen; Editing by Clarence Fernandez)<\/p>\n","protected":false},"excerpt":{"rendered":"By Laurie Chen BEIJING, June 25 (Reuters) – Chinese AI startup Z.ai said on Thursday it plans to…\n","protected":false},"author":2,"featured_media":85545,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[6744,53,3013,20205,32727,45942],"class_list":["post-85544","post","type-post","status-publish","format-standard","has-post-thumbnail","category-agi","tag-agi","tag-anthropic","tag-artificial-general-intelligence","tag-frontier-models","tag-open-source-model","tag-qinkai-zheng"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/85544","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=85544"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/85544\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/85545"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=85544"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=85544"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=85544"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}