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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsNvidia lost $593 billion in market value on January 27, 2025, as its shares fell 16.9% amid investor concern that DeepSeek’s lower-cost AI models could weaken expectations for ever-growing spending on chips and data centers. The often-used “$600 billion” figure is rounded. The selloff reflected a sharp change in market expectations—not proof that DeepSeek had made Nvidia’s chips obsolete or would permanently reduce demand for them.
What happened to Nvidia’s stock?
On Monday, January 27, 2025, Nvidia’s shares fell just under 17%. Reuters reported that the drop erased $593 billion in market value, then a record one-day loss for a company on Wall Street. The headline figure of $600 billion rounds that reported amount.
The decline was part of a broader technology selloff: Reuters reported the Nasdaq fell 3.1% and the Philadelphia semiconductor index fell 9.2% that day. The Associated Press separately put Nvidia’s fall at 16.9% and described losses concentrated in AI-related stocks.
Why did DeepSeek worry investors?
DeepSeek-R1 had been released the week before the selloff. Its rise prompted investors to question whether useful AI models would require the scale of spending on expensive chips, data centers, and supporting infrastructure that many had expected. If models could be trained or run effectively at lower cost, investors might reassess future demand across that supply chain.
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That was the market concern, not an established conclusion about Nvidia’s future sales. The drop coincided with DeepSeek’s growing prominence, and contemporary coverage identified it as a catalyst for investor concern; it does not show that DeepSeek alone caused every market move or that the effect would last. Reuters also noted broader context, including an upcoming Federal Reserve decision and other developments. Reuters’ January 27 report described the concerns as spanning chipmakers and data-center companies.
What did DeepSeek claim about its costs?
Reuters reported that DeepSeek-V3 researchers said the model used Nvidia H800 chips and less than $6 million in training compute. That figure is the researchers’ reported compute cost, not an independently audited total cost of developing or operating the model. Reuters also reported that a DeepSeek official WeChat post claimed R1 was 20 to 50 times cheaper to use than OpenAI’s o1, depending on the task. That comparison was a company claim relayed by Reuters, not an independently audited measurement. Reuters’ account of DeepSeek’s models and claims places V3’s launch on January 10, 2025, and R1’s release in the week before the selloff.
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These figures describe different things. V3’s reported figure concerns training compute; the R1 comparison concerns the cost of use, or inference, relative to another model. Neither figure by itself establishes the full cost of deploying an AI service at scale, the amount of hardware required in every setting, or a direct comparison of model capability.
Did DeepSeek make Nvidia chips obsolete?
The January 27 selloff did not establish that. Nvidia’s spokesperson told TechCrunch that DeepSeek was “an excellent AI advancement and a perfect example of Test Time Scaling,” and said, “Inference requires significant numbers of Nvidia GPUs and high-performance networking.” Those comments were Nvidia’s response, reported by TechCrunch—not independent confirmation of DeepSeek’s exact hardware needs or proof that its models require a particular number of GPUs. TechCrunch reported the spokesperson’s statements.
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There was also uncertainty about the technical details. The Associated Press quoted Wedbush analyst Dan Ives saying questions remained about which chips DeepSeek ultimately used and whether its development worked around chip restrictions. Those were contemporaneous questions, not settled findings. A model’s reported training cost cannot by itself answer how much hardware its users need for inference or how much infrastructure a commercial service will require.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Was the market reaction an overreaction?
The one-day price move shows that investors rapidly repriced expectations; it cannot, on its own, determine whether that repricing was justified over the longer term. The consequences for Nvidia depended on questions the day’s market data could not settle, including how widely lower-cost models would be adopted and what their total infrastructure requirements would be.
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Reuters quoted Bokeh Capital Partners chief investment officer Kim Forrest: “Today is a drubbing for these stocks, but I don’t necessarily think whatever’s going to happen in the short while here – the next couple of days – is where they are ultimately valued.” That was one investor’s contemporaneous view, not a forecast or a definitive verdict on Nvidia’s valuation. Reuters’ coverage of the selloff captured the uncertainty around what the market reaction meant.
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