The final exam of the AI feast: software crash and NVIDIA Corporation's financial report.

At the beginning of 2026, the chill on Wall Street is more piercing than in previous years. The global software sector has experienced a rare sharp decline, with the S&P 500 software and services index plummeting by over 18% in just a few weeks, causing nearly a trillion dollars in market value to evaporate. This is not a typical cyclical downturn, nor is it a short-term panic brought about by macroeconomic fluctuations, but rather a deeper, more structural anxiety - the market is beginning to question whether AI agents are fundamentally rewriting the value distribution logic of the software industry. At the same time, seismic shifts are quietly taking place at the hardware level. OpenAI has officially released the GPT-5.3-Codex-Spark model based on the Cerebras wafer-level chip, marking the first substantial weakening of dependence on NVIDIA Corporation's GPU ecosystem by major model companies. Signals of hardware diversification are becoming exceptionally clear, with cracks appearing in the once formidable monopoly of computing power. Against this backdrop of internal and external challenges, the "heart" of the global AI industry chain - NVIDIA Corporation (NVDA.US) - is about to reveal its financial report. This is not just a routine performance disclosure, but a stress test on whether "AI spending can continue to run wild." As the profit story at the application layer is being questioned and the dependence on hardware is weakening, can NVIDIA Corporation, at the top of the industry chain, continue to maintain faith in its high valuation? The market is waiting for an answer. The turmoil in the software industry is shaking the foundation of AI spending. The core anxiety behind the sharp decline in the software sector is not just the fluctuations in short-term profits, but rather a fundamental concern about whether business models are being overturned. Over the past decade, the Software-as-a-Service (SaaS) model has been the most certain growth engine in the tech industry. Enterprises lock in customers through subscriptions, leading to stable recurring income. However, the emergence of AI agents is disrupting this logic. Traditional software requires human user interaction to complete tasks such as input, clicks, and confirmations; whereas AI agents can bypass traditional interfaces, understand intent directly, and autonomously call multiple software system APIs to complete workflows that would typically require human collaboration. Imagine a scenario: in the past, enterprises needed to purchase a CRM system to manage customers, an email system for communication, and data analysis tools for generating reports. In the future, an enterprise-level AI agent may only need one subscription to autonomously handle customer follow-ups, email writing, and data analysis. When the agent becomes a true gateway, previously independent software becomes "fundamental capability modules," and pricing power may be reallocated. Software companies are transitioning from "selling tools" to "selling data interfaces," resulting in significantly decreased bargaining power. This implies that the long-term growth expectations of software companies are being reassessed. If the revenue ceiling for SaaS companies decreases, valuation systems are bound to collapse. The investment logic in AI infrastructure is fundamentally based on an assumption: that the application layer will continue to expand, thereby driving the demand for computing power. Cloud computing giants (such as Microsoft Corporation's Azure, Amazon.com, Inc.'s AWS, Alphabet Inc. Class C's Cloud) have significantly increased AI capital expenditures in recent years, with some companies experiencing CapEx growth rates of over 50%. Their logic is that AI applications will explode, developers will rent more computing power, and they need to stockpile GPUs in advance. However, in the backdrop of collapsing software valuations, the market is beginning to ask a sharp question - when will these investments pay off? If the application layer is unable to generate enough profit to cover the high Token costs, and if enterprise customers find that the efficiency gains from AI are not enough to offset the increased software subscription costs, then the demand for computing power from cloud providers may slow down. Once profit expectations at the application layer are downgraded, the investment pace in infrastructure will undoubtedly be affected. This is a typical "bullwhip effect": a small fluctuation in end demand, when transmitted to upstream chip manufacturers, can be magnified into massive order fluctuations. This is the potential chain reaction that NVIDIA Corporation must face. If the software industry enters a cold winter, will cloud providers cut back on orders? If the answer is yes, then NVIDIA Corporation's high-growth narrative will lose its most important support. OpenAI's "de-NVIDIA Corporationization," symbolic significance outweighs practical impact? At the hardware level, OpenAI's launch of the GPT-5.3-Codex-Spark based on the Cerebras chip is seen as a significant signal of hardware ecosystem differentiation. While NVIDIA Corporation still holds absolute market share in the short term, the symbolic significance of the trend cannot be overlooked. In recent years, NVIDIA Corporation has almost become synonymous with AI computing power. Its CUDA ecosystem has built a strong technological moat, making it difficult for developers to migrate to other platforms, thus enabling NVIDIA Corporation to dominate the data center GPU market and maintain high pricing power. However, this monopoly position also brings risks: single supply chain risks, high prices, and production capacity bottlenecks. As leading model companies start exploring diversified chip solutions, the market is clearly signaling that no company wants to be locked into a single supplier. OpenAI, as one of NVIDIA Corporation's largest customers, turning to Cerebras is not only based on cost or performance considerations, but is also a strategic balancing act. Cerebras' wafer-level engine has shown extremely high efficiency in specific large model training scenarios, demonstrating the feasibility of non-GPU architectures in the AI field. This does not mean that NVIDIA Corporation's orders will immediately flow to other providers. The inertia of the CUDA ecosystem is immense, with high migration costs. However, the market premium on its "irreplaceability" may be loosened. In the past, investors were willing to give NVIDIA Corporation a higher price-to-earnings ratio because they believed it was the only choice; now, if there is a second choice, NVIDIA Corporation's pricing power will be constrained. More importantly, if profit pressures are felt at the application layer, customer demands for returns on computing power investments will become more stringent. At that point, issues of pricing, efficiency, and substitutability will be magnified. Cloud providers may increasingly adopt in-house chips (such as Alphabet Inc. Class C's TPU, Amazon.com, Inc.'s Trainium) or third-party alternative solutions to reduce procurement costs. The risk for NVIDIA Corporation is not immediate, but in marginal changes. As long as demand growth outpaces supply, NVIDIA Corporation can maintain high gross margins. However, once demand growth slows down, or the cost-effectiveness of alternative solutions becomes evident, NVIDIA Corporation's gross margins will face downward pressure. OpenAI's move is a harbinger of these marginal changes. It tells the market that AI computing power is no longer a one-man show for NVIDIA Corporation, and a diversified hardware ecosystem is taking shape. This is a long-term bearish signal for NVIDIA Corporation, which relies on maintaining a high valuation through monopoly premiums. The true key to the financial report is not the numbers, but confidence. Investment banks generally expect NVIDIA Corporation to deliver better-than-expected results. After all, the existing backlog of orders is enough to support revenue for several quarters. But, as strategists have pointed out, when the market is accustomed to surprises, the marginal effects of surprises are diminishing. The real key lies in Huang Renxun's statements during the conference call, and the guidance given by the management for the future. The market needs to hear not only about order growth, but also about the sustainability of customer capital expenditures. Are cloud providers still committed to expanding data centers? Are AI applications starting to scale and generate revenue? Are enterprise customers still expanding training and inference budgets? These questions are more important than mere revenue figures. The explosive rise of NVIDIA Corporation over the past two years was based on a belief - that AI is a long-term arms race, and giants will spare no expense in investing in computing power regardless of short-term gains or losses. But if the profit logic in the software industry is being reconfigured, will the arms race slow down? Once capital expenditures reach a rational stage, NVIDIA Corporation's growth curve may regress from exponential to linear. For high valuation companies, changes in pace are often more fatal than changes in direction. If NVIDIA Corporation hints at a slowdown in growth, even if it is still growing, the stock price may face significant adjustments. Because the market pricing is based on the expectation of "infinite growth," once that expectation is adjusted to "finite growth," the valuation multiples will contract. In addition, the market will also closely monitor changes in revenue structure. Has the demand for training peaked? Is the demand for inference taking over? If training demand slows down while inference demand has not yet taken off, NVIDIA Corporation will face a situation of stagnation. Huang Renxun needs to prove to the market that AI is not just about training large models, but also about ubiquitous inference applications, which will sustain a longer-lasting market. The real key to the financial report is confidence. It is about making customers believe that investing in AI can bring returns, and convincing investors that NVIDIA Corporation can continue to grow. If this confidence is shaken, a chain reaction will rapidly spread across the entire industry chain. In conclusion, The sharp decline in the software industry is a signal that the AI revolution is entering uncharted territory. The pains at the application layer may be just the cost of technological advancement, or it may be the beginning of a restructuring of business models. NVIDIA Corporation, standing at the top of this industry chain, appears to be the safest, but also the most sensitive. It is the foundation of the entire AI building, but if there are tremors in the upper levels, the foundation cannot stand alone. If the application layer resumes growth and AI agents create new business value, the demand for computing power will continue to expand, with NVIDIA Corporation remaining the biggest beneficiary; but if profit anxiety spreads to the decision-making level of capital expenditures, the flames may spread upward along the industry chain, eventually reaching chip suppliers. The financial report will reveal not just quarterly profits. It will address a more fundamental question - Is AI spending driven by faith or cash flow? In recent years, AI spending has largely been driven by faith. Giants are afraid of missing out on the future, so they are investing at a loss. But now, the market is starting to demand returns. Shareholders are beginning to question: with billions of dollars invested, where are the profits? If AI fails to bring tangible cash flow, this arms race will likely become unsustainable. As the market moves from "narrative" back to "returns," NVIDIA Corporation needs to prove that it is not just the last one to join the AI feast. It needs to demonstrate that it is selling not just chips, but productivity tools that can continuously generate value. In the spring of 2026, for NVIDIA Corporation, this is not just a financial reporting season, but the ultimate judgment on the survival logic of the AI era. Those who can weather the cycles will become true empires; while prosperity built solely on faith will eventually return to the ground under the gravity of cash flow. The market is holding its breath, waiting for Huang Renxun to provide the answer that can stabilize the entire situation. This article was originally published on the WeChat official account "US Stock Research Society"; Translated by GMTEight, edited by Yan Wencai.