That figure would surpass the company’s financing target as it prepares to go public next year, Bloomberg News reported Tuesday (Oct. 6).
Contemporary Amperex Technology Co. and tech giant Tencent are among the biggest backers in the new round, due to close soon, sources familiar with the matter told Bloomberg.
According to the report, DeepSeek initially hoped to raise around $7.4 billion (or 50 billion yuan), though interest in the round exceeded expectations after the release of the company’s latest AI model. Sources said the term sheets signed indicate the round could approach $15 billion.
Bloomberg describes DeepSeek’s listing as one of the most highly anticipated debuts on the Chinese market in years. Rival Moonshot, meanwhile, is also aiming for an early 2027 initial public offering (IPO) after closing funding at a $50 billion valuation, the report added.
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DeepSeek first came to prominence early last year when it introduced an AI model that rocked Silicon Valley and Wall Street by offering performance comparable to that of U.S. rivals while using significantly fewer Nvidia chips.
Last month saw a report from The Information — citing unnamed sources — which said DeepSeek had more than doubled its annualized revenue run rate in the last few months, putting that rate at $1 billion.
In other artificial intelligence news, PYMNTS spoke recently with Pavan HS, senior director of product, agentic commerce at Visa, about the way merchants are viewing AI agents: approaching them as another path to sale, with all the requirements related to payments, fraud, loyalty, returns and customer service applicable elsewhere.
“At the end of the day, for merchants, agentic commerce is just another sales channel,” he said in an interview published Tuesday. “The two things that they care about is being trustworthy and making it convenient for their consumers.”
The channel is one that forms long before checkout, the report said, using the example of a shopper planning a trip to Norway and asking an AI assistant for help in finding a jacket. The merchant then has to provide enough structured product information for the agent to link “Norway in winter” with the features of the right coat.
Different agents can find that information through different protocols or via web crawling, leaving merchants to determine where/how they want their catalogs exposed, the report added.
“Some merchants might choose to sell on other AI platforms, and some merchants might choose to build their own chatbot,” HS told PYMNTS. “There are pros and cons associated with each of these approaches.”
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