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Nvidia vs. Alphabet: Which Is the Best AI Stock to Buy Now?

Summarized by NextFin AI
  • The U.S. Supreme Court's ruling on February 20, 2026, struck down emergency tariffs, easing cost pressures on tech firms, leading to a 3.7% rise in Alphabet shares and a 0.9% gain in the Nasdaq Composite.
  • Nvidia's upcoming fiscal Q4 2026 earnings report on February 25 is highly anticipated, as Nvidia's performance is now a key indicator of the AI sector's health, accounting for 7.1% of the S&P 500.
  • Despite Nvidia's projected 65% revenue growth, its stock trades at a lower forward earnings multiple than Alphabet, reflecting market concerns over Alphabet's legacy search business amidst generative AI disruption.
  • The geopolitical landscape adds complexity, with President Trump's new global levy potentially impacting Nvidia's semiconductor supply chain, while Alphabet's software-centric model offers more insulation from trade barriers.

NextFin News - In a week defined by significant legal shifts and high-stakes anticipation, the artificial intelligence sector has once again become the focal point of global financial markets. On February 20, 2026, the U.S. Supreme Court issued a landmark 6-3 ruling striking down broad emergency tariffs previously enacted by U.S. President Trump, a move that immediately relieved cost pressures on major technology hyperscalers. Following the decision, Alphabet shares jumped 3.7%, while the broader Nasdaq Composite gained 0.9% as investors pivoted back to high-growth tech assets. This rally serves as a volatile prelude to the most anticipated event of the quarter: Nvidia’s fiscal Q4 2026 earnings report, scheduled for February 25. With Nvidia now accounting for approximately 7.1% of the S&P 500, its performance has become the de facto barometer for the health of the global AI trade.

The current competitive landscape between Nvidia and Alphabet has evolved from a simple client-provider relationship into a complex dynamic of "co-opetition." While Alphabet remains one of Nvidia’s largest customers, it has successfully scaled its proprietary Tensor Processing Units (TPUs) to handle specific AI workloads. According to The Globe and Mail, Alphabet’s TPUs have become a viable alternative to Nvidia’s GPUs in niche scenarios, particularly for internal Google Cloud tasks where specialized efficiency outweighs general-purpose flexibility. However, Nvidia’s Blackwell architecture continues to hold the crown for the most popular computing units overall, maintaining a dominant market share in the high-end training segment. The strategic tension lies in how much of the AI budget will remain with hardware providers versus shifting toward integrated cloud platforms.

From a valuation perspective, the market is witnessing a rare phenomenon. Despite Nvidia’s projected revenue growth of 65% for the current fiscal year—dwarfing Alphabet’s 7%—Nvidia’s stock is currently trading at a forward earnings multiple that is, in some metrics, cheaper than Alphabet’s. This inversion is historically uncommon and reflects the market's intense scrutiny of Alphabet’s legacy search business, which faces potential disruption from generative AI. Conversely, Nvidia’s valuation is supported by a massive jump in data center sales, which rose 66% year-on-year to $57 billion in its most recent quarter. Analysts note that while Nvidia offers higher upside potential, Alphabet provides a "steady grower" profile, anchored by YouTube, Google Search, and a cloud business that thrives on recurring subscription revenue regardless of which hardware powers the backend.

The macro-political environment under U.S. President Trump adds another layer of complexity. Although the Supreme Court clipped the executive branch's emergency tariff powers, U.S. President Trump immediately signaled a new 10% global levy under Section 122 of the Trade Act of 1974. For Nvidia, which relies on a complex global semiconductor supply chain involving Taiwan and other Asian hubs, these trade frictions remain a persistent risk factor. Alphabet, while also exposed to hardware costs, possesses a more software-centric revenue stream that is partially insulated from physical trade barriers. Furthermore, the U.S. President’s focus on "sovereign AI" and domestic infrastructure could favor Nvidia’s role as the primary supplier of the "new oil"—compute power—required for national security and economic competitiveness.

Looking ahead, the "best buy" depends on an investor's risk tolerance for the maturing AI cycle. Nvidia represents a high-conviction play on the continued expansion of physical AI infrastructure. However, as major clients like Amazon and Meta begin to diversify their chip suppliers to avoid vendor lock-in, Nvidia may face market share moderation. Alphabet, meanwhile, is positioned to capture value from the application layer of AI. As businesses move from training models to deploying them, Alphabet’s integrated ecosystem—combining proprietary chips, a leading cloud platform, and massive consumer touchpoints—offers a more resilient, albeit slower-growing, investment thesis. In the immediate term, the February 25 earnings will likely determine if Nvidia can maintain its valuation lead or if the market will begin rewarding Alphabet’s diversified stability.

Explore more exclusive insights at nextfin.ai.

Insights

What are the key technical principles behind Nvidia's Blackwell architecture?

How has the competitive relationship between Nvidia and Alphabet evolved over time?

What recent legal changes have impacted the AI market, specifically regarding tariffs?

What is the current market share of Nvidia and how does it compare to Alphabet's TPUs?

What factors are influencing Nvidia’s projected revenue growth for fiscal 2026?

How do trade frictions affect Nvidia and Alphabet differently in the semiconductor supply chain?

What are the implications of the Supreme Court ruling for technology companies like Nvidia?

What challenges does Nvidia face with clients diversifying their chip suppliers?

How does Alphabet's business model provide stability compared to Nvidia's growth potential?

What recent updates have been made to Alphabet's Tensor Processing Units?

What are the long-term impacts of the U.S. government's focus on 'sovereign AI'?

What does the term 'co-opetition' mean in the context of Nvidia and Alphabet?

How might Nvidia's valuation evolve following its fiscal Q4 2026 earnings report?

What are the potential risks for Nvidia stemming from its reliance on a global semiconductor supply chain?

How do the growth trajectories of Nvidia and Alphabet differ in the AI landscape?

What historical cases illustrate the volatility of the AI stock market?

How does the integration of proprietary chips and cloud platforms benefit Alphabet?

What are the market reactions to Nvidia's earnings compared to Alphabet's performance?

What strategic advantages does Nvidia have over Alphabet in the high-end training segment?

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