---
title: "NVIDIA's performance is coming in strong. Can the \"AI computing power bull market narrative\" break the \"AI bubble\"?"
type: "News"
locale: "zh-HK"
url: "https://longbridge.com/zh-HK/news/276862432.md"
description: "NVIDIA will announce its quarterly results after the market closes on Wednesday Eastern Time, with global investors focusing on whether its profits can grow in line with the AI capital expenditure budget of $650 billion to $700 billion. Although NVIDIA dominates the AI chip sector, increasing competition from other tech giants may pose risks to its market position. NVIDIA's stock price has only risen about 2% in 2026, affected by fluctuations in the AI market and intensified competition"
datetime: "2026-02-25T09:18:04.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/276862432.md)
  - [en](https://longbridge.com/en/news/276862432.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/276862432.md)
---

> 支持的語言: [简体中文](https://longbridge.com/zh-CN/news/276862432.md) | [English](https://longbridge.com/en/news/276862432.md)


# NVIDIA's performance is coming in strong. Can the "AI computing power bull market narrative" break the "AI bubble"?

According to Zhitong Finance APP, as the "AI chip giant" NVIDIA (NVDA.US), known as the "most important stock on Earth," is set to announce its quarterly earnings after the U.S. market closes on Wednesday Eastern Time (Thursday morning Beijing time), a "stress test" regarding AI computing power investment themes is also on the horizon. Global investors focusing on AI computing infrastructure and the broader AI infrastructure boom are seeking evidence that the profits of this world's highest market capitalization chip giant are closely tied to the significant AI capital expenditure budget trend of the four major U.S. tech giants (hyperscalers), which amounts to between $650 billion and $700 billion, and are expected to achieve strong growth in tandem.

At the same time, the recent announcements from hyperscalers about launching more cost-effective AI ASIC chips based on self-developed models also show signs of posing risks to NVIDIA's long-term absolute dominance in the core area of global AI infrastructure—AI chips.

After driving the U.S. stock market towards a super bull market trajectory over the past three years, NVIDIA's stock price, which holds a high weight in the Nasdaq 100 Index and the S&P 500 Index, has only risen about 2% since 2026. This is mainly due to the "AI apocalypse narrative" triggered by a series of AI agent products from Anthropic, which severely impacted software stocks and high-valuation tech giants, coupled with large-scale cloud vendors accelerating the development of more cost-effective alternative AI ASIC chips (such as TPU) and promoting a multi-vendor strategy, along with intensified competition from companies like AMD. The chart below compares NVIDIA's stock performance in 2026 with the MAGS ETF (focusing on the seven major tech giants in the U.S. stock market) and the S&P 500 Index.

![1772010036(1).png](https://imageproxy.pbkrs.com/https://img.zhitongcaijing.com/image/20260225/1772010048344974.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg)

Alongside strong competitor AMD (AMD.US), which plans to release a new version of its flagship AI server cluster later this year, Google's parent company Alphabet has emerged as a strong competitor to NVIDIA in the AI computing infrastructure field through an agreement to provide its massive self-developed TPU AI computing cluster (part of the AI ASIC technology route) to Anthropic, the developer of the Claude chatbot. According to media reports, Google is also in talks with Meta (META.US), the parent company of Facebook, to supply TPU-based AI computing infrastructure to one of NVIDIA's largest customers.

Furthermore, NVIDIA's performance can be described as "event-driven" performance data, with the options market implying a price volatility expectation of about ±5% after NVIDIA's earnings report. Based on its market capitalization of approximately $4.7 trillion, this corresponds to about $226 billion in single pricing swings; considering its approximately 7.8% weight in the S&P 500 Index, the mechanical effect of this weight alone is enough to trigger significant volatility in the U.S. stock market After experiencing a significant upward trend in the super bull market of U.S. stocks since 2023, the stock prices of the seven largest U.S. tech giants, including Google, Microsoft, Amazon, and NVIDIA, have continued to fluctuate this year. This is mainly because investors have begun to question whether the ongoing large-scale investments in AI computing infrastructure (with the four major U.S. tech giants' AI capital expenditures expected to exceed $700 billion this year, indicating a potential increase of 60%) can generate sufficiently strong returns to support their high valuations.

The so-called "Magnificent Seven" (Mag 7), which occupy a significant weight in the S&P 500 and Nasdaq 100 indices (approximately 35%-40%), includes Apple, Microsoft, Google, Tesla, NVIDIA, Amazon, and Facebook's parent company Meta Platforms. They are the core driving force behind the S&P 500 index's record highs and are viewed by top investment institutions on Wall Street as the most capable combination to bring substantial returns to investors amid the largest technological transformation since the internet era.

## NVIDIA Aims to Capitalize on the AI Inference Wave

To defend its near-monopoly position in AI computing infrastructure and seize the AI inference wave, AI chip superpower NVIDIA reached a reportedly $20 billion deal at the end of last year to obtain chip technology licensing from AI chip startup Groq. Analysts generally believe this move will enhance its leadership position in the rapidly growing AI inference market; inference refers to the process where a trained AI model answers questions in real-time and efficiently completes complex AI workflows. Last week, NVIDIA also agreed to sell millions of AI chips to Meta but did not disclose the transaction amount.

However, as the biggest winner of the AI boom, NVIDIA itself has raised concerns about the sustainability of related AI computing infrastructure spending and the so-called "AI internal loop investment" by extending the potential $100 billion investment process with OpenAI, one of its largest clients. Recently, a media report indicated that the chip giant plans to replace its previous $100 billion commitment with a smaller-scale $30 billion investment.

The AI training side, which is almost monopolized by NVIDIA's AI GPUs, requires more powerful general-purpose AI computing clusters and rapid iteration capabilities across the entire computing system. In contrast, the AI inference side places greater emphasis on unit token costs, latency, and energy efficiency after the large-scale implementation of cutting-edge AI technologies. For example, Google has clearly positioned Ironwood as a TPU generation "born for the AI inference era," emphasizing performance/energy efficiency/cost-effectiveness of computing clusters and scalability.

The essence of NVIDIA's deal with AI chip startup Groq is a non-exclusive licensing of inference-type AI chip technology + the absorption of Groq's founder/CEO Jonathan Ross and some core engineering teams. Some semiconductor industry analysts have also emphasized that Groq's exclusive chip technology focuses on inference and reduces data transport bottlenecks using on-chip SRAM, directly addressing the cost/latency pain points in the inference phase Recently, the non-exclusive licensing agreement worth $20 billion reached with AI chip startup Groq, which licenses its AI inference technology to NVIDIA, and after the completion of the transaction, Groq's founder and core R&D team will join NVIDIA, highlights the increasing competitive pressure brought by the "global AI inference wave" and the growing competition from Google's TPU AI computing clusters. NVIDIA strives to maintain its absolute dominance in the AI chip field with an 80% market share through "multi-architecture AI computing + consolidating the CUDA ecosystem + attracting more AI chip design talent," and aims to secure the full-stack discourse power in AI.

## "Stress Test" of AI Computing Power Investment Theme

The market urgently needs to see whether NVIDIA's profit and revenue growth can continue to deliver and maintain "exceeding expectations" against the backdrop of approximately $650 billion to $700 billion in AI-related capital expenditures from tech giants, and is looking forward to NVIDIA's performance guidance exceeding Wall Street's general expectations.

"This fourth-quarter earnings report from NVIDIA is particularly important because there are significant concerns about the outlook for AI computing infrastructure spending—concerns about whether we are in an AI bubble," said Ivana Delevska, Chief Investment Officer of Spear Invest. The firm holds NVIDIA shares through an exchange-traded fund. "It will be very important to prove that profit growth has not truly slowed."

According to data compiled by LSEG from Wall Street analysts' expectations, Wall Street expects NVIDIA to report a quarterly profit for the period ending in January that surges over 62% year-on-year, which means a slowdown compared to the previous quarter's growth rate of 65.3%, as it will face a more stringent year-on-year comparison base.

NVIDIA's total revenue for the fourth quarter of fiscal year 2026 is expected to soar over 68% to $66.16 billion. Wall Street analysts expect NVIDIA's management to forecast a further revenue growth of 64.4% to $72.46 billion for the first quarter of fiscal year 2027. Notably, the chip giant has exceeded analysts' revenue expectations in the past 13 quarters, but the extent of the outperformance has narrowed, mainly due to analysts becoming increasingly stringent in their growth expectations as NVIDIA's market value reached an unprecedented $5 trillion and experienced more than three years of significant increases.

![1772010062(1).png](https://imageproxy.pbkrs.com/https://img.zhitongcaijing.com/image/20260225/1772010064386690.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg)

RBC's stock analyst team expects the chip giant to provide revenue guidance for the quarter ending in April that is at least 3% higher than the market consensus. Delevska from Spear Invest, a long-term bull on NVIDIA, believes that the chip giant may provide total revenue guidance that exceeds expectations by as much as $10 billion, expecting it to surpass the market consensus by over 13%.

A recent research report from Bank of America indicates that the global AI arms race is still in the "early to mid-stage"; one of the world's largest asset management giants, Vanguard, recently pointed out in a research report that the AI investment cycle may have only completed 30%-40% of its final peak. However, this asset management giant stated that the risk of a pullback in large tech stocks is indeed increasing According to Wall Street giants Morgan Stanley, Citigroup, Loop Capital, and Wedbush, the global investment wave in artificial intelligence infrastructure centered around AI computing hardware is far from over and is only at the beginning. Driven by an unprecedented "storm of demand for AI inference computing power," this round of global AI infrastructure investment is expected to reach a scale of $3 trillion to $4 trillion, continuing until 2030.

The demand for DRAM/NAND storage chips remains strong, and the prices of these storage product lines (such as DDR4/DDR5/data center enterprise-grade SSD series) are experiencing a wild expansion. This is mainly due to the AI computing surge pushing the demand for storage chips and their importance for AI training/inference systems to unprecedented heights. Currently, the global demand for AI computing power is showing an exponential growth trend, with supply far behind the intensity of demand. This can be clearly seen from the exceptionally strong performance data recently released by TSMC, the "king of chips," and ASML, the "king of lithography machines."

For the recent sideways-moving but internally volatile U.S. stock market, the significance of NVIDIA's earnings report is that it not only answers the question of "Is NVIDIA's growth trend strong?" but also addresses whether the logic chain of "strong AI capital expenditure—profit realization—valuation discount" still holds and whether it can dispel doubts related to the "AI bubble." Since 2026, the S&P 500 index has only seen a slight increase (about 0.2%), but there is significant differentiation "under the surface," with sectors like software and services being notably pressured due to concerns over AI disruption. At the same time, on a more macro level, Wall Street surveys also show that the market's path for 2026 is still mixed with uncertainties related to trade and AI computing infrastructure spending, and valuations (forward P/E ratio of about 21.6 times) remain sensitive—therefore, the statements from NVIDIA's management during the conference call regarding customer order visibility, AI investment return cycles (capex ROI), and industry competition dynamics will be regarded as a "risk preference anchor" for the entire high-beta AI infrastructure ecosystem (including cloud computing vendors, AI computing infrastructure supply chains, data center power chains, etc.) and AI software sectors.

## NVIDIA's earnings report, STILL NO. 1, may trigger significant market volatility

Statistical data shows that NVIDIA, the highest market capitalization company in the U.S. stock market and even globally, may trigger significant turbulence in the stock market with its earnings report. The options market implies that NVIDIA's stock price is expected to fluctuate by about ±5% after the earnings report, which corresponds to approximately $226 billion in single pricing movement based on its market capitalization of about $4.7 trillion. Considering its weight of about 7.8% in the S&P 500 index, this mechanical effect alone is enough to cause significant volatility in the U.S. stock market.

If NVIDIA's earnings report and guidance show a "Q4 performance just slightly above expectations or guidance that is not strong enough," it often triggers a synchronized risk-off from leaders in the semiconductor supply chain to cloud computing vendors and software stocks, making short-term volatility (VIX) more likely to be significantly elevated (the VIX has been fluctuating around 20 in recent weeks, usually indicating a notable demand for options protection). Conversely, if revenue and guidance significantly exceed expectations and stabilize the "AI computing bull market narrative," which is crucial for the trajectory of the global stock market bull run, it is more likely to lead to a rapid repair of risk preferences and a decline in volatility Analysts still expect that the demand for NVIDIA's expensive AI chips will remain strong. These chips serve as the "brains" of servers processing massive AI workloads and will account for a significant portion of the huge expenditures tech giants will make this year to expand or build new AI data center capacities on a large scale.

NVIDIA executives hinted in January that they are discussing next year's data center orders with major clients, prompting several Wall Street analysts to predict that the chip giant will update its backlog of AI computing infrastructure orders, which could reach up to $500 billion for 2025 to 2026, first disclosed in October 2025.

However, the biggest constraint on NVIDIA's growth may be the capacity bottlenecks at the chip supply chain level—this bottleneck limits the shipping speed of AI chips, as NVIDIA and its competitors are fiercely competing for capacity space on TSMC's (TSM.US) 3-nanometer chip production lines, the largest chip manufacturer in the world.

Jay Goldberg from Seaport Research Partners wrote in a report: "We believe NVIDIA's performance will easily meet expectations, but given TSMC's capacity constraints, it is hard to see them bringing about larger upside potential."

However, NVIDIA's sales of AI chips to China may make a significant comeback—previously restricted by export limitations imposed by the U.S. government—which could help boost NVIDIA's revenue and profit expectations.

NVIDIA CEO Jensen Huang stated last month that he hopes the Chinese authorities will allow the company to sell its high-performance H200 AI chips locally, and that the relevant sales permits are in the final stages of being finalized.

Competitor AMD (AMD.US), after obtaining permits and being able to ship modified data center server-level CPUs and GPUs to China, has reintegrated high-performance AI chip sales in the Chinese market into its performance forecast for the current quarter.

NVIDIA is expected to record a 75% adjusted gross margin in the fourth fiscal quarter, an increase of more than 1 percentage point compared to the same period last year. Analysts generally expect that the company will not be harmed by the sharp shortage of global memory chip supplies. They stated that NVIDIA's pricing power and its likely locked-in high bandwidth memory (HBM) quotas for the entire year and even through 2027 will shield it from the negative impacts of skyrocketing memory prices

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