With NVIDIA, the world's highest-valued company often dubbed the "most important stock on Earth" and "AI chip king," reporting another exceptionally strong quarterly performance and future outlook, all members of the "Magnificent Seven" have now disclosed their results. This group, accounting for roughly 40% of the U.S. stock market's value, has been the core driver of the AI-fueled super bull market since 2023. Despite unprecedented supply disruptions in the oil market due to the effective closure of the Strait of Hormuz, casting a significant shadow over global growth prospects, their latest quarterly results and forward guidance provide a powerful rationale for the market to remain invested in the AI computing theme, thereby bolstering bullish sentiment across global equities.
NVIDIA's latest earnings, which surpassed expectations, concluded the highly anticipated Q1 reporting season for the "Magnificent Seven." Their reports have become a crucial barometer for investors to assess the fundamental strength of the "AI computing trade" sweeping global markets and to gauge whether an "AI bubble," reminiscent of the dot-com era, is inflating toward a burst. The "Magnificent Seven," widely recognized by Wall Street analysts as comprising Apple, Microsoft, Alphabet, Tesla, NVIDIA, Amazon, and Meta Platforms, are the core force behind the S&P 500's record highs. Top Wall Street investment firms view them as the portfolio most capable of delivering outsized returns amid what is considered the most significant technological shift since the internet era.
The S&P 500's cumulative gain of over $30 trillion during the past three years of a "super bull market" has been largely driven by these global tech behemoths. It has also been strongly propelled by chip companies (like Micron, TSMC, and Broadcom), memory product leaders (like SanDisk, Western Digital, and Seagate), and power system suppliers (like Constellation Energy) that have significantly benefited from massive global investments in AI computing infrastructure. Guided by "AI faith," massive global capital flows related to artificial intelligence are concentrated on two primary investment themes: AI computing infrastructure construction and AI application revenue generation.
For the U.S. stock market, which has repeatedly hit new highs and entered a new long-term bull cycle, and for the MSCI World Index, the increasingly fervent "AI faith" centered on the "artificial intelligence investment theme" has been the core and most powerful bullish driver in recent years. As long as this wave of "AI faith" remains hot and continues to sweep global equity markets, the bull run in U.S. and global stocks is poised to continue its exceptionally strong upward trajectory.
**AI Computing Chain Super Bull Market Gets More Fuel! Tech Giants' Spending Expectations Reach New Highs**
Earnings reports from four tech giants (Microsoft, Amazon, Meta Platforms, and Alphabet), released almost simultaneously, sent the same crucial signal for the AI computing chain super bull market: the arms race in AI computing infrastructure/resources is far from over. Their combined capital expenditures are projected to reach at least approximately $725 billion by 2026—significantly above 2025 spending levels and the latest Wall Street analyst forecasts. These tech giants are willing to bear pressure on cash flow and profit margins rather than take "one step less" in the computing arms race.
It is understood that Wall Street's mainstream price target for NVIDIA already values it as a $7 trillion company; the most aggressive consolidated target pushes it toward the $12 trillion level. The core logic behind these high targets is NVIDIA's evolution from a GPU leader to a "full-stack AI factory infrastructure platform"—with GPUs, CPUs, networking, rack-scale systems, software ecosystems, and capital returns collectively supporting valuation expansion. AI-accelerated computing infrastructure spending is expected to potentially reach $3-4 trillion by 2030.
As AI agents gain global popularity, the AI computing investment focus is shifting from "single-point computing competition around AI GPUs" to "AI agent-driven full-stack computing systems." The next wave of excess alpha returns will no longer belong solely to the strongest leaders in AI GPU/AI ASIC fields but will systematically diffuse across the full-stack AI computing infrastructure layer, including data center CPUs, DRAM/NAND/HBM memory, AI PCBs, liquid cooling systems, data center optical interconnect systems, ABF substrates/glass substrates, and a wide range of foundry services.
On April 30th, the three cloud computing super giants—Microsoft, Google (Alphabet), and Amazon—delivered impressive results on the same night, highlighting how the unexpectedly explosive growth of their cloud businesses, benefiting from the AI wave, is leading Wall Street to reprice AI's commercial returns.
A recent report from Morgan Stanley's analyst team indicates that the combined capital expenditures of the five hyperscale tech giants (Amazon, Google, Meta, Microsoft, Oracle) are projected to reach about $800 billion in 2026 and are expected to exceed $1.1 trillion in 2027, up from a previous forecast of $950 billion. Morgan Stanley analysts emphasize the core logic behind these massive investments: heavy upfront investment and capacity building, followed by recouping costs through scaled commercial revenue and ROIC based on AI computing resources. The surge in cloud computing backlogs and AI application tokens is the most direct evidence that this logic is working. The unexpectedly rapid growth of these giants' cloud businesses is causing Wall Street to reassess AI's commercial payback.
Regarding AI revenue prospects, Anthropic, which in February launched a series of heavyweight AI agents that rattled global software stocks, recently revealed a significant profitability trajectory. This strong revenue data and the better-than-expected profit path are likely to further accelerate tech giants' efforts to build their "AI computing super empires." Anthropic's forecast of Q2 revenue doubling and achieving operating profit for the first time highlights the AI industry chain shifting from a "cash-burning narrative" to a "cash flow cycle narrative."
Most significantly, Anthropic's monthly Annual Recurring Revenue (ARR) surged by $110 billion, equivalent to the combined scale of three SaaS giants—Palantir, Snowflake, and DataBricks—over a decade. This is an unprecedented miracle in the history of capitalism. Anthropic also expects Q2 revenue to jump from $48 billion in Q1 to $109 billion, with operating profit of about $559 million. This indicates that cutting-edge AI applications are not merely consuming computing power but are beginning to convert enterprise programming, agent workflows, cybersecurity, and data analysis into high-value token revenue.
The explosive demand for Claude and AI tools is pushing Anthropic toward its first profitable quarter. Furthermore, its computing cost per dollar of revenue decreased from about 71 cents in Q1 to approximately 56 cents in Q2, showing that scale effects and inference efficiency are improving the AI application economic model.
Additionally, a research report suggests that for every $100 increase in U.S. imports of AI-related hardware, the GDP of major Asian suppliers may increase by $35, accelerating the formation of an "AI-driven super surplus" in Asian economies. This implies that the AI boom is no longer just a story of application-layer valuation expansion for OpenAI/Anthropic but a global capital cycle of "U.S. AI application profit expansion -> large cloud providers' Capex -> Asian AI computing infrastructure hardware exports -> U.S. dollar asset repatriation."
From both industry chain and equity market perspectives, Anthropic's profitability inflection point and the "super surplus" in the Asian AI computing chain form a closed loop: U.S. AI application companies generate massive revenue, profits, and boost listed valuations; Hyperscalers (U.S. tech giants) expand AI capital expenditures; Asian chip manufacturing chains, HBM, server, and advanced packaging suppliers gain export benefits; and these benefits flow back through dollar assets, foreign exchange deposits, and overseas investments to support the U.S. financial environment, particularly the "low-interest rates" desired by figures like Trump. Simultaneously, the Asian AI computing chain is gradually becoming a key force for a long-term and healthy bull market in U.S. and global stock markets.
For instance, equity or cash gains from the AI boom for Asian chipmakers like SK Hynix, Samsung, and TSMC are circulating in the global economy, forming a capital chain akin to a "circular AI boom." The profit spillover from the Asian AI industry chain, if converted into allocations to dollar assets, U.S. corporate bonds, U.S. tech bonds, and long-term bonds, could indeed help absorb the U.S. AI financing wave, thereby compressing credit spreads, improving financing conditions for tech giants, and supporting a long-term bull market in U.S. equities.
The Asian AI computing industry chain is already the undisputed hardware foundation for U.S. Hyperscalers' expansion of AI data centers. Subsequently, the external surplus generated by the benefits from Asian AI chips/AI server manufacturing/AI PCBs/optical interconnects/liquid cooling/data center power, and other AI computing infrastructure, will partially flow back into dollar assets, thereby strongly supporting the U.S. low-interest-rate financing environment and U.S. stock valuations.
**The following charts clearly illustrate the current market's intense focus on the "Magnificent Seven" AI investment frenzy and the significant divergence within the group.**
**NVIDIA, with its flawless performance, continues to define the AI bull market! Its growth rate far outpaces other tech giants.**
Revenue growth within the Magnificent Seven remains highly uneven, with NVIDIA's scorching growth rate helping it maintain a dominant lead in performance expansion. Driven powerfully by accelerating demand for AI computing infrastructure, the chip giant's revenue continues to soar, solidifying its position as the world's highest-valued company.
NVIDIA's results for Q1 of fiscal year 2027 (ending April 26, 2026) show revenue surged 85% year-over-year to $81.62 billion, nearly 3.1% above the average analyst estimate. Its core business—Data Center revenue of approximately $75.2 billion, contributing over 90% of total revenue—and total revenue both set new quarterly records, indicating AI computing demand remains the absolute main driver of NVIDIA's growth.
NVIDIA's Q2 revenue guidance midpoint of about $91 billion sets another quarterly record, significantly above the average analyst expectation. More importantly, this time NVIDIA presented Wall Street not just a single AI GPU or graphics card growth story but a rapidly expanding blueprint for AI factory economics. Citi noted that NVIDIA's breakdown of data center sales into Hyperscale and ACIE improves visibility; the chip giant also expects its Vera CPU sales to reach $20 billion this year and projects a $200 billion Total Addressable Market (TAM) for CPUs by 2030. This signifies NVIDIA is evolving from an "AI GPU leader" into an AI infrastructure platform company encompassing "GPU + CPU + networking infrastructure + rack-scale systems + CUDA developer software ecosystem," even aggressively entering the data center server CPU value pool long dominated by Intel and AMD.
In contrast, other companies in the Magnificent Seven portfolio are expanding at relatively steady paces, although they are all expected to invest hundreds of billions or even trillions of dollars into their respective global AI computing infrastructure projects, hoping to reap strong profit curves closely tied to AI applications in the coming years.
The chart above shows that the earnings growth momentum of large tech companies is far from uniform.
**AI Data Center Construction Race Fuels Unprecedented Borrowing Spree**
To fund their increasingly grand AI ambitions, the Magnificent Seven are turning to the bond market on an ever-larger scale. According to Dealogic data, bond issuance from this portfolio has surged significantly. Their bond sales year-to-date have reached $134 billion, compared to a total issuance of $87.5 billion for the full year 2025. This year's debt surge is led by Alphabet, Amazon, and Meta—tech giants at the very heart of the super arms race to build AI computing infrastructure.
The chart shows the Magnificent 7 have comprehensively increased bond issuance to fund their AI ambitions.
Wall Street bankers generally state that U.S. tech giants may follow Alphabet's lead one by one in tapping overseas markets for funding, as they cannot rely solely on U.S. Wall Street financial markets to support AI ambitions of this unprecedented scale—otherwise, they would overwhelm demand and cause "AI bubble" sentiment and financing costs to spike sharply. Some signs of strain are already emerging. While global tech stocks continue to soar, pushing benchmark stock indices higher, the bond returns of these tech companies are lagging behind the overall investment-grade bond market.
Alphabet has almost overnight become a dominant player in multiple overseas debt markets. The company successfully issued nearly $60 billion in the Japanese bond market. Its euro-denominated debt currently stands at about €22 billion ($26 billion), ranking eighth among non-financial issuers, surpassing regular large issuers including BMW Group and Mercedes-Benz Group. By the end of this week, it could become Japan's second-largest corporate bond issuer. Earlier this week, U.S. cloud computing and e-commerce super giant Amazon raised over $3 billion in its inaugural Swiss franc bond offering, making it the sixth-largest issuer in that market.
**The Magnificent 7 Prove AI Trade is More Than Faith; It's the Fundamental Driver for Tech Stock Long-Term Bull Run! AI Investment Frenzy Fuels Global Stock Market Rebound**
After a shaky start to the year and stock market volatility following Middle East geopolitical conflicts, tech giant stock prices have regained momentum for market cap expansion. Investors are aggressively betting on the long-term prospects of this technology, even as they worry about the actual pace of return on these companies' investments.
The chart shows that as large-cap tech stocks regain strong momentum, NVIDIA and Alphabet are leading the gains. However, the hierarchy sometimes appears to have seen notable shifts. Alphabet shocked Wall Street with cloud business growth rates surpassing larger cloud rivals Microsoft and Amazon at times, even nearing the growth rate of NVIDIA's profit-generating data center business. Its market capitalization nearly overtook NVIDIA's to become the world's most valuable listed company before pulling back.
According to statistics from Tajinder Dhillon, Director of Earnings Research at LSEG, the earnings growth of the Magnificent Seven will continue to be a significant force driving the expansion of the S&P 500's overall EPS. It is projected they may stabilize into a growth trajectory by the time we enter 2027, although the portfolio is still expected to significantly outperform the broader S&P 500 index.
The following chart shows quarterly earnings growth forecasts by portfolio, highlighting the significant importance of the Magnificent Seven's strong profit growth for U.S. stock earnings fundamentals.
This latest trend further reinforces the core view of bullish investors: the market will continue to concentrate on mega-cap tech giants, supported by fundamentals rather than being on the brink of an "AI bubble" burst driven by euphoria.
The most typical example undoubtedly lies in NVIDIA's latest performance, which clearly highlights that the global frenzy for AI computing infrastructure construction is far from over and is expanding from AI GPUs/AI ASICs to data center CPUs, high-performance networking infrastructure, server cluster-level systems, AI super factories, and enterprise-scale AI cloud computing systems.
On Wall Street, bullish sentiment for the "global AI leader" NVIDIA is heating up further, with the average analyst price target implying a potential market capitalization exceeding $7 trillion for NVIDIA.
Isabelle Freidheim, Founder and Managing Partner of Athena Capital, stated, "Investors have no reason to do anything differently because the current index concentration composition has been working in their favor."
As global enterprises accelerate their deployment in the artificial intelligence field, capital expenditures for the majority of S&P 500 component companies are expected to increase significantly in the coming years. However, this also raises a question: how much cash do tech giants have left for shareholder returns? Goldman Sachs statistics show that overall capital expenditures for S&P 500 component companies are projected to grow by 33% in 2026, compared to a mere 3% growth expectation for share buybacks.
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