"NVIDIA Corporation (NVDA.US) struggles to maintain a solid performance after consistently exceeding expectations, as investors grow tired of constant surprises: Q1 results exceed expectations, dividends increase by 25 times, but Q2 revenue guidance falls short of buyers' hidden expectations."

After the close on Wednesday, NVIDIA Corporation (NVDA.US), the world's largest semiconductor company by market value, released a "crushing" first quarter financial report for the fiscal year 2027: revenue surged by 85% year-on-year to $81.6 billion, with data center revenue reaching $75.2 billion, both significantly exceeding Wall Street consensus. However, the stock price plummeted by more than 3% after hours, and although it barely rebounded later, the market's lukewarm response to this "strongest quarterly report in history" has exposed investors' core anxiety as the AI narrative enters deep waters. Record-breaking financial data For the first quarter of the fiscal year 2027 ending on April 26, NVIDIA Corporation achieved revenue of $81.62 billion, an 85% year-on-year increase, significantly exceeding analysts' consensus range of $78.75 billion to $79.2 billion. Adjusted earnings per share were $1.87, also surpassing the market estimate of $1.75 to $1.77. Net profit for the quarter reached $58.3 billion, an increase of 211% year-on-year, almost triple that of the same period last year. The data center business remains the core growth engine. Data center revenue for the quarter reached $75.2 billion, a 21% increase from the previous quarter, nearly doubling from $39.1 billion in the same period last year, far exceeding analysts' expectations of $72.8 billion. The company reformed its financial reporting in this quarter, splitting the data center business into two major submarkets, "Hyperscale" and "ACIE" (AI Cloud, Industrial, and Enterprise), to better reflect current and future growth drivers. Edge computing revenue was $6.4 billion, a 10% year-on-year increase. "Hyperscale" will include revenue from public clouds and the world's largest consumer internet companies, while ACIE will focus on illustrating NVIDIA Corporation's growth opportunities in various dedicated AI data centers and AI factories across industries and countries/regions. Edge computing will focus on data processing devices for intelligent agents and physical AI, including PCs, game consoles, workstations, AI-RAN base stations, Siasun Robot&Automation, and cars. The adjusted gross margin was 75%, in line with expectations. Free cash flow was as high as $48.55 billion, providing a solid foundation for the company's large-scale shareholder return plan. Forward guidance: $91 billion "ceiling" and anticipated early overshooting Looking ahead to the second quarter, NVIDIA Corporation expects revenue to reach $91.0 billion, with a fluctuation of 2%. This figure is higher than the analyst consensus mean of $86.88 billion compiled by LSEG, and also exceeds the median guidance of $87.0 billion reported in some media outlets. Non-GAAP gross margin is expected to remain around 75% plus or minus 50 basis points. NVIDIA Corporation CFO Colette Kress stated that by the end of this decade, infrastructure spending on artificial intelligence is expected to reach $3 trillion to $4 trillion annually. "AI is no longer icing on the cake, but a necessity to enhance productivity in all industries and positions," she said, adding that NVIDIA Corporation's Blackwell architecture is "ubiquitous." Kress stated that the architecture has been adopted and deployed by "all major hyperscale data center operators, all cloud service providers, and all major model manufacturers." However, the problem lies in the anticipated "ceiling." Despite the analyst average forecast being $87.0 billion, private expectations among buying institutions have quietly risen to $96.0 billion. While the $91.0 billion guidance technically constitutes a "beat" statistically, it falls far short of convincing the market, which had already set expectations extremely high. eMarketer analyst Jacob Bourne pointed out directly: "NVIDIA Corporation has once again exceeded expectations, but after crushing it for multiple consecutive quarters, this has essentially been priced in by the market." In other words, the marginal surprise effect is diminishing. When a company consistently outperforms revenue expectations for 12 consecutive quarters, merely "meeting" the most optimistic forecasts is clearly not enough to convince the market to push higher. The drastic fluctuations in the stock price after hours are a microcosm of this game: the stock price plummeted by over 3% after the announcement, then rebounded to near flat, and as of the time of writing, it was down by about 0.9%. Year-to-date, NVIDIA Corporation's stock price has risen by around 20%, outperforming the S&P 500 but lagging behind most large chip industry peers - investors have long been digesting the known fact that "performance will exceed expectations." Shareholder returns: $80 billion buyback and signals of increased dividends Faced with an increasingly sensitive secondary market, NVIDIA Corporation's management has rarely significantly increased shareholder return efforts. The company announced a new $80 billion stock buyback authorization, and raised its quarterly cash dividend from $0.01 per share to $0.25 per share, a 25-fold increase. In the first quarter of the fiscal year 2027, the company had already returned $20 billion to shareholders through buybacks and dividends. The background of this move is worth noting. Bank of America Corp. previously noted that NVIDIA Corporation was only using 47% of its free cash flow for dividends and buybacks during the 2022-2025 period, far below the level of about 80% for large tech peers. A significant increase in the dividend ratio can be seen as a proactive strategy choice by management to broaden the shareholder base and fill perceived "valuation gaps" at high levels. With a current market value of about $5.46 trillion, the $80 billion buyback size is only equivalent to 1.5% of the market value, but combined with a 2400% dividend increase, the signal significance is already at maximum capacity. Competitive landscape: The era of inference is no longer a "one-man show" If the expectation game is the surface cause of the stock price volatility after hours, the collective "land grab" by competitors in the inference chip market poses a bigger variable hanging over NVIDIA Corporation's long-term valuation. The AI chip market is undergoing a shift in demand from "training" to "inference." The global AI chip market is expected to exceed $280 billion in 2026, with inference chips accounting for 52%, or around $145 billion. While NVIDIA Corporation still leads in the training segment, its market share has decreased from around 80% to about 70%. In the inference segment, the competitive landscape is more fragmented. On one hand, large scale cloud providers are accelerating self-creation. Alphabet Inc. Class C's TPU, Amazon.com, Inc.'s Trainium and Inferentia series chips are steadily taking bites out of NVIDIA Corporation's customer budgets. Broadcom Inc. is collaborating with software developers like OpenAI to enter the custom chip field. On the other hand, traditional rivals like AMD are actively positioning themselves in the inference market, while Intel Corporation is also building up its strength. More disruptively, AI chip newcomer Cerebras Systems just completed its annual largest IPO last week, surging by 68% on its first day. Its wafer-scale engine WSE-3's inference speed is 15 to 1000 times faster than GPU solutions in specific scenarios, showcasing the viability of a "non-NVIDIA Corporation route" to the market. Facing this competition, NVIDIA Corporation is not standing idly by. The company released a new CPU and AI system based on Groq technology in March, focusing on the inference scene. CFO Colette Kress revealed during the call that NVIDIA Corporation's CPU's total addressable market is about $200 billion, with nearly $20 billion in CPU revenue visibility locked in for this fiscal year. Additionally, the company disclosed a $30 billion cloud computing service agreement for the quarter, interpreted by analysts as a key strategy to bind cloud providers through "bottom-line commitment." Chinese market: Structural risk of zero market share In NVIDIA Corporation's growth narrative, the "absence" of the Chinese market has evolved from short-term disturbance to a structural reality. The financial report and conference call disclosed that the second quarter guidance for NVIDIA Corporation "does not include any data center revenue from China." According to Bernstein Research and other institutions' latest forecasts, NVIDIA Corporation's market share in China's AI chip market has plummeted from 95% three years ago to 8%. In stark contrast, domestic manufacturers like Huawei HiSilicon, Cambricon, and Hygon Information Technology have leveraged their self-developed architectures to rise strongly, with domestic AI accelerator card market share surpassing 60%. Among them, Huawei HiSilicon's Ascend 950PR's inference performance is three times that of NVIDIA Corporation's H20, and is expected to occupy 50% of the Chinese market share by 2026. While U.S. export control policies have begun to permit some older products to be exported to China on a case-by-case basis, the Chinese government's determination to prioritize supporting domestic supply chains remains firm. NVIDIA Corporation CEO Jensen Huang previously admitted that the company's market share in China has essentially "returned to zero." A market that was considered a $50 billion annual opportunity by management is now forecasted to contribute nothing in baseline predictions - a loss that is not only detrimental but also a growth ceiling that investors cannot ignore for a company with revenue nearing $400 billion. Outlook: Supply chain expansion and expectations for "Vera Rubin," can Agentic AI support a trillion dollar guidance? Despite facing competition and GEO Group Inc pressure, NVIDIA Corporation's short-term demand side remains hot. Data shows that U.S. major hyperscale cloud providers' total spending on AI infrastructure in 2026 is expected to exceed $700 billion, a significant jump from $400 billion in 2025 - this vast amount of budget is the underlying fuel for the continued skyrocketing of data center revenue. To meet this massive demand, NVIDIA Corporation is heavily increasing its supply chain investments. The company's supply scale rose to $119 billion this quarter, a 25% increase from the previous quarter's $95.2 billion. This implies that the company has secured critical production capacity for the next several quarters in advance to hedge against bottleneck risks from global semiconductor supply shortages. The next focus for investors is whether the next-generation AI architecture known as "Vera Rubin" can enter the volume production ramp-up phase as scheduled in the second half of 2026. Goldman Sachs Group, Inc. maintained a "buy" rating and a $250 target price for NVIDIA Corporation in a report before the financial report, implying about 20% upside from the current stock price, but explicitly listing the Vera Rubin production schedule as one of the core catalysts to drive a valuation reassessment. The growth ceiling of the existing Blackwell architecture has been fully priced in by the market, and a true incremental story requires the next generation product to take over. In the financial report statement, Huang used an ambitious expression: "The construction of AI factories - the largest infrastructure expansion in human history - is accelerating at an extraordinary pace. Agentic AI has arrived, enabling productive work, creating real value, and rapidly scaling across companies and industries." Analysts from Goldman Sachs Group, Inc. listed the penetration rate of Agentic AI (Agent AI) in the enterprise sector as their top concern variable, viewing it as a key signal to verify whether NVIDIA Corporation can fulfill the "trillion dollar total addressable data center market" vision put forward at the GTC conference. If agent AI can truly enter core business processes in enterprises, the surge in computational demand will be an exponential amplification of the current demand level concentrated on training - presenting NVIDIA Corporation with its biggest opportunity to reshape competitive barriers in the inference era. NVIDIA Corporation stated in regulatory filings that the Rubin platform is expected to begin shipping in the latter half of fiscal year 2027. Rubin and Blackwell are NVIDIA Corporation's flagship AI chips. They can build large language models that support conversational AI (e.g., OpenAI's ChatGPT). The Blackwell chip is already on the market, while the Rubin chip is the company's next generation processor, now fully in production. Huang previously stated that Blackwell and Rubin chips could generate over $1 trillion in revenue by the end of 2027. When asked about the forecasted chip revenue reaching $1 trillion, Huang noted that Vera CPU's standalone sales were not factored into that forecast. He mentioned that Vera would be the biggest contributor beyond the $1 trillion expected revenue. The H200 chip is based on NVIDIA Corporation's older Hopper technology and is the company's second-most advanced AI chip, primarily targeting the Chinese market. While the H200 chip is slower than the Blackwell chip in many AI tasks, it is still widely used in the industry. Before the tightening of export restrictions in the U.S., NVIDIA Corporation held about 95% market share in China's advanced chip market. The Chinese market once accounted for 13% of NVIDIA Corporation's revenue, and Huang estimated earlier that the AI market alone in China would reach $50 billion this year. Huang: NVIDIA Corporation is making progress in inference computing During the Q&A segment of the conference call, Huang stated that NVIDIA Corporation is "gaining market share" in the inference computing field, which refers to the process of using trained models in real-time applications. Huang said, "We are almost the only company currently serving physical artificial intelligence," referring to the fact that the company has long been researching physical AI, and that business is growing rapidly. Thus, the company's market share growth in inference is accelerating rapidly. Physical artificial intelligence refers to AI that can interact with the real world, such as self-driving cars and factory robots, rather than just software. In the field of artificial intelligence, training refers to the process of training models, while inference refers to the real-time use of models. NVIDIA Corporation has long held almost a monopoly in the chip field used for training artificial intelligence systems, but now faces competition from other tech giants who are developing their own chips to meet evolving market demands. These demands are shifting towards processors that can run artificial intelligence systems, respond to queries in real-time, and execute tasks. The so-called inference market is larger, but also more intensely competitive. In summary NVIDIA Corporation's financial report is flawless in absolute terms: revenue, profit, guidance, and shareholder returns all significantly exceeded market consensus. However, when "beating expectations" itself has become part of market pricing, investors' questions naturally shift from "how much more can be beaten" to the "sustainability of growth" and "evolution of the competitive landscape." The $80 billion buyback and the dividend increase of 25-fold are precise responses to valuation anxieties, rather than solutions to fundamental problems. The multi-pronged competition in the inference chip market, the structural absence in the Chinese market, and the volume production pace of the next-generation Vera Rubin architecture collectively test whether NVIDIA Corporation can transition from a "phased winner" to a "long-term champion." Against a backdrop of accelerating AI infrastructure construction, Huang's trillion-dollar TAM vision may not be a pipe dream - but it requires not only the booming progress of the current data center business, but also the all-dimensional penetration capability from training to inference, from hyperscale to enterprise, and from the U.S. to the world. As the narrative shifts from "GPU shortages" to the "ecological battle," the market's cool eye towards this historically strongest quarterly report may be the beginning of a new turning point that is already underway.