DeepSeek Taps CITIC Securities for Shanghai STAR Market IPO

M&A · Partnership
โดย Reuters·CN·Read original
Summary · why it matters

DeepSeek has engaged CITIC Securities to prepare for an initial public offering on Shanghai's STAR Market, according to Reuters, citing two people with knowledge of the matter. The Hangzhou-based AI startup aims to begin the IPO process this year, though the timing, amount to raise, and target valuation have not been determined. The arrangement with CITIC, previously undisclosed, suggests concrete progress toward a public listing, as Chinese firms typically need a securities company for pre-IPO tutoring. The IPO push comes as DeepSeek seeks capital for computing infrastructure, model development, and talent retention, with founder Liang Wenfeng viewing it as a way to build a compensation structure to retain key engineers and researchers amid competition from rivals like ByteDance and Xiaomi. DeepSeek is currently raising a new funding round at a valuation of 500 billion yuan ($75 billion), following a June round of roughly $7.4 billion at a post-money valuation exceeding $50 billion, with Tencent Holdings and CATL as major external shareholders. This valuation remains far below those sought by U.S. rivals like Anthropic and OpenAI, highlighting revenue differences between Chinese and American AI firms. Other Chinese AI startups are also moving toward public markets, with Moonshot filing confidentially for a Hong Kong IPO at a $50 billion valuation. DeepSeek also raised prices on its V4-Flash and V4-Pro API models in August, with increases ranging from 50% to over 1,100%, reflecting growing cost pressures.

Impact on stocks 5

Artificial Intelligence · 2 stocks
Climate Adaptation & Water · 1 stocks
Others · 2 stocks

Theme Impact 1

Off-coverage companies 4

DeepSeekPrivate▲ Positive
Capitalrelevance

DeepSeek advances toward STAR Market IPO, securing capital for infrastructure and talent retention.

AnthropicPrivate± Mixed
relevance

ByteDancePrivate± Mixed
relevance

OpenAIPrivate± Mixed
relevance

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