Investors in Nvidia's stock receive positive updates from President Trump and the financial sector
Last week, Chinese startup DeepSeek caused a stir in the tech world with their publication of a research paper. Claiming their large language model matches leading U.S. models, all while spending significantly less, DeepSeek sent shares of Nvidia (NVDA -0.58%) tumbling due to its dominance in AI accelerator chips.
However, Wall Street sees a silver lining. Analysts believe the efficient training techniques DeepSeek employed could benefit Nvidia by reducing costs and accelerating AI adoption. This could increase demand for Nvidia GPUs, as companies integrate AI features into applications without breaking the bank.
Several analysts have updated their forecasts for Nvidia stock since the DeepSeek research publication, and all see potential upside. Gil Luria at D.A. Davidson set his target price at $135 per share, implying a 5% increase. Morgan Stanley's Joseph Moore set his target at $152, implying a 18% upside. Atif Malik at Citigroup and Stacy Rasgon at Bernstein both set their targets at $175, a 36% upside. C.J. Muse at Cantor Fitzgerald even sees a 56% upside, setting his target at $200 per share.
Even Dan Ives at Wedbush Securities sees an opportunity in Nvidia's post-DeepSeek sell-off. With President Trump wanting to cut corporate taxes and boost AI investments, Ives thinks Nvidia's earnings will grow faster than expected.
Trump's Corporate Tax Rate Reduction and Nvidia's Stock Buybacks
President Trump's corporate tax rate reduction has led to record-breaking stock buybacks, most notably in 2018. Companies like Apple and Alphabet spent billions on repurchasing shares, including Nvidia, which spent nearly $13 billion in the third quarter of 2024. With Trump's proposed further reduction for domestic manufacturers, Nvidia could see even more aggressive buybacks, potentially driving up earnings per share.
The Stargate Project and Nvidia's Staggering Potential
Last week, President Trump announced the Stargate Project, aiming to keep the U.S. at the forefront of AI with investments from private companies. Stargate, a joint venture between OpenAI and SoftBank, plans to build 20 U.S. data centers optimized for AI, with Nvidia's GPUs likely playing a significant role.
Details are still lacking, but Melius Research estimates Nvidia could potentially benefit from over $100 billion in Stargate spending, which has not been factored into Wall Street's estimates.
In short, DeepSeek's innovations in training techniques and their impact on Nvidia GPUs and stock performance present a complex scenario for the tech giant. However, continued innovation, global market positioning, reduced costs, and potential Stargate Project benefits leave room for optimism.
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DeepSeek's efficient training techniques have implications for Nvidia's market position, revenue, and stock performance:
- Reduced Computational Power Requirements: DeepSeek-R1, the large language model developed by DeepSeek, was trained using multi-stage methods which required significantly less computational power compared to traditional large language models.
- Cost Efficiency: DeepSeek's API pricing is significantly lower than that of OpenAI's GPT-4, potentially leading to a decrease in demand for high-end GPUs like Nvidia's H100s.
- Impact on Nvidia's Revenue and Stock Performance: Reduced demand for high-end GPUs could impact Nvidia's revenue and stock performance, as it has been heavily reliant on the AI boom and massive investments in computing power.
- Innovation and Market Positioning: To maintain their market lead, Nvidia may need to innovate more in both hardware design and software optimization, potentially exploring alternative technologies like Application-Specific Integrated Circuits (ASICs) for real-world AI applications.
- Geopolitical and Commercial Implications: DeepSeek's success could democratize AI development, but export controls and national chip bans could limit its penetration in Western markets, affecting its commercial ambitions.
In light of DeepSeek's efficient training techniques, there might be a need for Nvidia to strategize financially. This could involve investing in research and development to stay competitive, as the reduced computational power requirements for training large language models could potentially impact Nvidia's revenue from high-end GPU sales. (money, finance, investing)
Furthermore, with the potential reduction in demand for high-end GPUs like Nvidia's H100s due to DeepSeek's cost-efficient API pricing, financial analysts might need to reevaluate their investment strategies related to Nvidia stock. (money, finance, investing)