Nvidia(NASDAQ: NVDA) has had a forgettable start to 2025 as shares of the semiconductor giant are down more than 3% as of this writing, and multiple factors out of the company’s control have played a part in its decline.
For instance, the previous Biden administration proposed wide-ranging restrictions on sales of Nvidia’s chips to foreign customers, but the impact of those restrictions was mitigated to some extent by the recent announcement of the Stargate project that could see $500 billion being poured into artificial intelligence (AI) infrastructure in the U.S. This development gave Nvidia stock a shot in the arm, but the chip designer would witness another sell-off very soon.
Chinese AI start-up DeepSeek released its R1 reasoning model and claimed that it was trained for a paltry $5.6 million. DeepSeek’s model was good enough to compete with the o1 reasoning model from OpenAI, a company that has been spending billions to build its AI infrastructure using chips from Nvidia. So, the low-cost nature and efficiency of the Chinese company’s model sent Nvidia stock packing.
Investors were worried about a potential drop in demand for its graphics cards that are being used for AI training and inference by major cloud computing companies and governments. The semiconductor giant shed almost $600 billion of its market cap in a single day on Jan. 27 following DeepSeek’s purported breakthrough. However, a report from semiconductor industry analysis company SemiAnalysis (via Tom’s Hardware) suggests that DeepSeek may not have revealed the actual cost of training its AI model.
SemiAnalysis points out that DeepSeek reportedly incurred $1.6 billion in hardware expenses. It also adds that the Chinese start-up has access to 50,000 of Nvidia’s previous-generation Hopper graphics processing units (GPUs), including 10,000 units of the flagship H100 processor. SemiAnalysis further points out that the $6 million figure highlighted by DeepSeek only refers to the potential money spent on training the model.
It doesn’t consider other costs associated with research, data processing, fine-tuning the model, and infrastructure expenses. Given that DeepSeek has reportedly spent over $500 million on AI funding since its inception in 2023 and has its own data centers, there is a good chance that the cost of training the R1 model that sent Nvidia stock plunging was actually higher than what’s being touted by the Chinese company.
If that’s indeed the case, then investors may have hit the panic button for the wrong reason. However, the good part is that Nvidia’s poor start to the year means that investors have a window to buy this fast-growing company on the dip. Here are three reasons why doing that could turn out to be a smart move.
The first reason to buy Nvidia is its valuation. The stock’s expensive valuation following its tremendous rally over the past couple of years has been a cause for concern for investors and analysts. However, it is now trading at quite attractive levels. Though Nvidia’s trailing price-to-earnings (P/E) ratio of 51 is higher than the tech-laden Nasdaq-100 index’s 33.4, the forward earnings multiple of 30 is lower than that.
The second reason why investors should consider buying Nvidia is related to DeepSeek. Assuming that DeepSeek’s claims are indeed true and it has managed to develop a low-cost model, it could lead to an increase in the demand for AI applications.
British economist William Stanley Jevons observed in 1865 that the increased efficiency in coal consumption wouldn’t reduce the demand for coal. It would instead spur the usage of coal in more industries. This concept, known as the Jevons Paradox, can be seen in many other applications. For instance, the increasing fuel efficiency of vehicles has reportedly led to an increase in distance traveled while the arrival of low-cost LED bulbs hasn’t necessarily brought down electricity bills as people have tended to install more lights because of reduced costs.
So, efficient AI models could lead to an increase in their demand, and that’s why the need for Nvidia’s chips is likely to remain solid. As such, DeepSeek’s purported breakthrough isn’t necessarily a bad thing for Nvidia.
The final reason to buy Nvidia stock following its recent pullback is that cloud computing giants are set to keep spending more money on AI infrastructure. President Donald Trump’s $500 billion AI infrastructure push that’s being driven by the likes of Oracle, OpenAI, SoftBank, and Abu Dhabi-based AI investment vehicle MGX to build AI data centers will require more chips. Meanwhile, recent announcements from the CEOs of Meta Platforms and Microsoft supporting higher spending on AI also point toward healthy AI chip demand.
Finally, a spike in bookings for the advanced machines sold by Dutch semiconductor equipment giant ASML provides further evidence that the appetite for advanced chips to support AI workloads isn’t going away. So, it won’t be surprising to see Nvidia’s fortunes turn around, which is why investors should consider using the recent pullback in this AI stock given the healthy growth that it is capable of delivering in the long run.
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Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool’s board of directors. Harsh Chauhan has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends ASML, Meta Platforms, Microsoft, Nvidia, and Oracle. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.
You May Have Sold Nvidia for the Wrong Reason. Here Are 3 Reasons Why You Should Be Buying This Artificial Intelligence Stock Once Again. was originally published by The Motley Fool
