Nvidia’s property plunged Monday, losing$ 600 billion in market value—the largest single-day market cap decline in history—as world interest turned to Chinese AI company DeepSeek.

The tech giant’s stock began the day trading at$ 140 but fell 16 % and closed at$ 118 as news of DeepSeek’s low-cost AI developments and high-performance spread.

The U.S. tech industry lost roughly$ 1 trillion in market capitalization as a result of its decline, which is consistent with broader trends, including issues relating to cryptography, which include the U.S. market.

DeepSeek’s potential to exceed OpenAI’s o1 while operating at a significantly lower cost, apparently under$ 5 million, has rocked the tech sector, which has prioritized computing power over performance.

According to Appfigures ‘ statistics, its victory has propelled DeepSeek to become the best free software in the U.S.

China’s claims that Chinese builders are training their AI designs on Nvidia H100 cards, which the U.S. barred from selling to them, raise questions about the effectiveness of U.S. export controls and China’s entry to cutting-edge technology, which contribute to the sell-off.

” The Taiwanese laboratory, they have more H100s than people think, you know”, Scale AI CEO Alexandr Wang told . ” My knowledge is that DeepSeek has about 50, 000 H100s, which they can’t speak on, certainly, because it is against the export settings that the U. S. has put in place”.

According to Professor Ion Stoica, a computer scientist at UC Berkeley and co-founder of Databricks and Anyscale, the U.S.’s reluctance to acknowledge open-source AI growth may have given Chinese firms an advantage in the field of AI growth, citing regulation issues and national security concerns.

” When I say open source, I mean open data, open training algorithms, open weights, and open evaluations—maximum visibility into how they’re trained and what they’re trained on”, Stoica told . ” Now we’re in a situation where Chinese companies bet on open source, unlike the U. S., and are clearly ahead”.

Stoica emphasized the transformative potential of lower AI model costs, while declining to speculate on the tech stock market.

” If the cost of building or serving these models drops by 10 or 100x, it could hurt these companies”, he said. These businesses could become even more valuable if it encourages innovation and accelerates AI development by doing more with the same hardware.

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