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China's AI Bubble Bursts: $480 Billion Wiped Out

China's STAR50 index of AI and chip companies fell 40% in under four months, erasing roughly $480 billion in market value.

Azad Khorsheed · Developer And writer
· 1 min read
China's AI Bubble Bursts: $480 Billion Wiped Out
Image: Kurd Developers

When researching artificial intelligence in China, no story stands out more right now than the "AI bubble." Shares of Chinese companies building AI and chips have suffered a sharp sell-off on the stock market.

What happened?

According to Reuters, the STAR50 index — which tracks leading AI and semiconductor companies on the Shanghai stock exchange — has fallen 40% from its July peak in less than four months, wiping out roughly $480 billion in market value. Companies such as Unitree, CXMT and MetaX were among the hardest hit.

What does this mean?

The crash exposes a wide gap between the money that poured into China's AI sector and the profits it can realistically generate. One reason: companies like DeepSeek, Alibaba, Moonshot AI and MiniMax have bet on open models offered for free or at very low prices, which makes it hard to turn them into revenue.

Retail investors absorbed a large share of the losses, and foreign investors have also pulled money out of the sector. Funding hasn't dried up entirely, though: DeepSeek recently raised $15 billion in one of the largest funding rounds in China's history.

What is the global impact?

For comparison, the US Nasdaq is only about 6% below its record high. China's experience is now a live example of the risks of AI valuations running ahead of real profits, and it may push companies and investors worldwide to be more cautious and take the necessary precautions.

Sources

Sources: Reuters, Futurism, Il Post / Financial Times, Digit
Azad Khorsheed

Azad Khorsheed is a software developer and project manager based in the Kurdistan Region of Iraq. He builds web and mobile systems with Laravel and React, with a focus on Arabic and Kurdish (RTL) interfaces. Here he writes about programming and lessons from real-world projects.