You May Have Sold Nvidia for the Wrong Reason. Here Are 3 Reasons Why You Should Be Buying This Artificial Intelligence Stock Once Again.

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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.

Nvidia stock fell thanks to DeepSeek, but investors may have jumped the gun

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.