Chinese AI’s Reality Check: Why Zhipu’s Modest IPO Plans Tell the Real Story
Zhipu AI’s reported $300 million IPO target, according to Bloomberg, offers a sobering reality check on Chinese artificial intelligence valuations. For a company that OpenAI explicitly warns is on the “front line” of China’s AI ambitions and has received over $1.4 billion in state backing, this modest fundraising goal reveals more about the economics of Chinese AI than any marketing narrative about innovation prowess.
Zhipu’s current $2.7 billion valuation makes its IPO target look particularly conservative—just 11% of its paper worth. Compare this to the frothy valuations commanded by US AI darlings, where companies routinely raise hundreds of millions at multi-billion dollar premiums. The bigger question is whether this restraint reflects genuine market discipline or an admission that Chinese AI companies cannot command Silicon Valley-style valuations.
Zhipu’s apparent shift from a mainland China listing to Hong Kong adds another layer of complexity. Hong Kong has indeed seen a spectacular IPO revival, with $40 billion raised so far in 2025 compared to just $5.7 billion last year. But venue shopping often signals uncertainty about investor appetite. The mainland market’s increasingly stringent approval process for tech IPOs suggests Beijing itself remains skeptical about AI sector valuations.
The real challenge facing Zhipu and its fellow AI四小龙 (Four AI Dragons) is the race to the bottom on pricing. DeepSeek’s demonstration that comparable AI performance can be achieved for just $5.58 million in training costs has fundamentally shifted investor expectations. When your competitor can build GPT-4 equivalent models at a fraction of the cost, premium pricing becomes impossible to justify. Zhipu’s modest 25 million users and “exceeding 10 million yuan” in annual revenue hardly screams hypergrowth to global investors accustomed to billion-dollar subscription models.
The venue switch reveals deeper tensions in China’s AI ambitions. Despite courting governments across Asia and Africa with promises of “responsible, transparent and audit-ready” Chinese AI alternatives, Zhipu cannot escape the fundamental economics: AI models are becoming commoditized, margins are compressing, and state subsidies are no substitute for sustainable unit economics. This is less about technological rivalry and more about industrial policy colliding with market reality.