AI Concept Stocks 2026 Overview: Growth Logic and Financial Report Analysis of NVIDIA, Broadcom, Marvell, Dell, and HPE

The wave of AI computing power is undergoing a fundamental structural transformation. Investors' focus has shifted from "who is building infrastructure" to "who is deploying AI." Based on financial data from Q2 2026, five representative AI concept stocks—NVIDIA, Broadcom, Marvell Technology, Dell Technologies, and Hewlett Packard Enterprise—are participating in this historic process with different roles and growth trajectories. Their performance data reflect not only their own operational results but also mirror the flow of overall AI infrastructure spending.

Comparison of financial data for five core AI concept stocks in 2026

NVIDIA: Growth has an upper limit, but the market has set a higher threshold

As the absolute leader in AI computing power, NVIDIA's performance in Q1 2026 remains solid: revenue of $44.1 billion, up 69% year-over-year, surpassing analyst expectations of $43.29 billion. Data centers remain the largest pillar, contributing $39.1 billion, up 73%. Notably, the penetration of Blackwell architecture chips exceeded expectations, accounting for 70% of data center revenue, with the market's transition from H-series to B-series shocking industry insiders.

However, strong performance did not lead to a proportionate rise in stock price—after earnings were released, the stock price fell about 1% in after-hours trading. The issue is not NVIDIA's growth itself but that the slight gap between growth and Wall Street's "perfect expectations" was amplified by the market. Revenue growth slowed from 78% last quarter to 69%, a slowdown that drew high attention. Additionally, due to export restrictions, demand for H20 chips in China declined, leading the company to record $5.5 billion in asset impairments, a variable with ongoing uncertainty.

NVIDIA is expanding its narrative boundaries. The Blackwell MVL72 AI supercomputing computer has been deployed, and the Vera CPU has opened new service markets. However, when growth stocks are re-priced by the market, NVIDIA needs to prove not only that next quarter's revenue exceeds expectations but also that its growth path over the next two to three years remains clear. From a valuation perspective, with a current market cap of about $2.7 trillion, NVIDIA must continuously demonstrate its ability to capture market share across all levels of AI infrastructure spending—from GPUs to networking to CPUs—to maintain this scale.

Broadcom: Deepening moat in custom chip route, but market demands "perfection"

If NVIDIA represents the general-purpose GPU route, Broadcom embodies a different differentiated path—custom ASICs (Application-Specific Integrated Circuits). Its Q2 2026 data fully demonstrate the explosive power of this route: total revenue of $22.19 billion, up 48% year-over-year, hitting a record high; AI semiconductor revenue reached $10.8 billion, up 143%.

More importantly, the visibility of its customer base is clear. CEO Chen Fuyang confirmed that Broadcom has six core custom chip customers, including Google, Meta, Anthropic, and OpenAI, which are among the most aggressive global AI infrastructure investors. These six customers are not short-term partners but are deeply integrated with exclusive custom development relationships, with each XPU development cycle typically lasting 18 to 24 months, making switching costs extremely high.

However, after the earnings release, the stock price fell over 13%. The market's skepticism stems from two minor gaps: total revenue of $22.19 billion slightly below Wall Street's expectation of $22.27 billion; infrastructure software revenue of $7.18 billion also below the expected $7.32 billion. Additionally, Chen Fuyang did not raise the full-year AI semiconductor revenue target from $100 billion, which buy-side institutions had already incorporated into their expectations. The market is evaluating the custom chip track with the same strict standards as NVIDIA—slight underperformance could trigger rapid revaluation.

Marvell Technology: Valuation pressure after low-base explosion and visibility of long-term orders

Marvell is the smallest among the five but has the most elastic growth story. Full-year revenue for 2026 reached $27k, up 42%, with data center business accounting for 75%. The company has raised its 2027 revenue guidance to nearly $11.5 billion, an increase of $500 million from previous expectations, roughly a 40% annual growth.

At Computex Taipei, Jensen Huang publicly called Marvell the "next trillion-dollar market cap company," which directly triggered a single-day stock increase of over 32% in early June 2026, with a year-to-date increase approaching 239%. However, the stock subsequently experienced a 15% daily correction amid wide fluctuations. Valuation battles are particularly fierce at this stage, with the current P/E ratio exceeding 70, prompting a reassessment of industry-average valuations.

Marvell's business overlaps significantly with Broadcom's, both focusing on ASIC design services and optical interconnect solutions for hyperscale cloud providers. The difference is that Broadcom is larger and has more stable cash flow, while Marvell has stronger growth elasticity and more room to grow its AI business. For Marvell, whether its valuation in the ASIC track can continue to be reassessed depends on whether AWS and Google will continue to upgrade their capital expenditure guidance in subsequent quarterly reports—this is a key signal to verify if AI inference demand remains high.

Dell Technologies: The biggest cyclical beneficiary of AI server infrastructure

Dell is the fastest-growing among the five, with recent financial data particularly impressive. As of May 1, the quarterly revenue reached $43.84 billion, a significant 88% increase year-over-year, marking the largest single-quarter growth since the company's return to the public market; adjusted EPS was $4.86, far exceeding the market expectation of $2.94.

AI server business is the core growth engine: quarterly revenue surged to $16.1 billion, up 757%. The full-year outlook for AI-optimized server revenue was raised from $50 billion to $60 billion. After the earnings release, the stock soared nearly 33%, driving server vendors like HPE and Supermicro higher.

Dell's growth is driven by the transition of global enterprise AI deployments from "pilot phase" to "large-scale deployment." Dell Vice Chairman and COO Jeff Clarke stated in the earnings call that traditional server shipments also saw significant growth, as semiconductor companies and tech giants utilize servers for internal inference and proxy workloads. Dell's order backlog has risen to $51.3 billion, demonstrating the sustainability of infrastructure spending rather than a one-time surge.

Constraints to watch include gross margin structure. The increasing proportion of low-margin AI servers has lowered gross margin to 17.7%. In the context of continued expansion in AI infrastructure investment, Dell's main strategy is to increase market share and revenue scale, but cost structure pressures remain an unavoidable constraint in its valuation logic.

HPE: Pioneer in enterprise AI infrastructure procurement cycle

HPE's latest financial report provides the clearest signal that enterprise AI procurement has entered a large-scale deployment phase. In Q2 2026, revenue grew 40% year-over-year to $10.7 billion, surpassing the expected $9.79 billion; adjusted EPS was $0.79, nearly 50% higher than both its own guidance and market consensus.

The most significant new information is the AI order backlog: HPE secured $1.8 billion in new AI system orders, bringing total AI system orders to $16.4 billion, with total backlog reaching a record $5.9 billion. The company also sharply raised its full-year revenue growth guidance from 17-22% to 29-33%. CEO Antonio Neri stated that the company's performance has exceeded the long-term financial plan by two years.

Juniper's acquisition integration is a key variable for HPE. The $14 billion acquisition transformed HPE from a primarily server-focused hardware manufacturer into an integrated infrastructure provider with a profit engine in networking. Network business revenue reached about $2.7 billion, up 152% year-over-year, with an operating profit margin of 23.7%—almost twice the company's overall operating margin. In addressing network bottlenecks in expanding AI clusters, Juniper's integration enables HPE to compete with Cisco in AI-native networking.

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Conclusion

Current AI concept stock trading is characterized by the interplay of two forces: one is the fundamental growth driven by each company's product and technological route; the other is the collective pricing of the long-term visibility of AI infrastructure spending. AI infrastructure investment remains in an early stage, with trillions of dollars expected to flow into this field over the coming years—even though this spending cycle has lasted about two and a half years, consumer and enterprise AI adoption continues to accelerate, especially inference demand, which is rapidly increasing due to larger and more complex models.

Server spending is projected to grow 36.9% in 2026, continuously expanding the growth boundary for AI concept stocks. Market valuation logic is also evolving: investors are shifting from broad themes of AI concepts to fine-grained selection of winners and laggards. It is important to note that investing in AI concept stocks involves high industry concentration, rapid technological iteration, policy, and export control risks; past performance does not guarantee future returns. The content of this article is solely an objective analysis of industry and data and does not constitute any buy or sell trading advice. Investors should make independent judgments based on their own risk tolerance.

Both crypto assets and stock trading involve market volatility risks. Gate's stock trading service, through partner brokers, is protected by relevant regulatory frameworks. Please refer to official announcements for specific trading rules and fee rates.