China’s Z.ai raises revenue target 25% after US$5 billion cash injection
Chinese artificial intelligence developer Z.ai has raised its year-end annual recurring revenue (ARR) outlook by 25 per cent to US$3 billion, as the firm indicated its fresh US$5 billion war chest had helped clear its computing capacity bottlenecks for the time being. The updated ARR projection, up from a previous estimate of about US$2.4 billion, was disclosed during an investor call on…
Chinese AI firm Z.ai has increased its fiscal year annual recurring revenue (ARR) target by 25% to US$3 billion, following a US$5 billion cash infusion. This new guidance was revealed during an investor call, up from an estimated US$2.4 billion. Z.ai, also known as Zhipu AI, used the funds to resolve its computing capacity limitations and accommodate rising demand for its AI services.
The company's ARR, reflecting projected monthly subscription income over a year, had reached US$1.8 billion this year. Executives stated that "in the short term, computing power supply is no longer the primary constraint on the company's rapid revenue growth." The firm's shares rose 5.9% to HK$720 in Hong Kong after the call, despite a 14.3% drop in stock value over the previous two days due to a global AI stock slump.
Z.ai has seen a surge in its coding user base, expanding by more than 1 million in two weeks after releasing its GLM-5 model in February. Additionally, the company's planned 30 billion yuan (US$4.5 billion) infrastructure expansion could add up to 100,000 petaflops of computing power, with 40% reserved for model training and research.
These developments could potentially generate 40 billion yuan in annual revenue. Z.ai's co-working tools are also gaining popularity beyond coding products, with industry orders exceeding 1 billion yuan since the GLM-5.3 release in August. The company is also expanding partnerships with cloud service providers, with revenue-sharing agreements expected to start in October.
Written by urgent.news from SCMP Business's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.