
Nvidia's fiscal Q1 2026 earnings release on May 28 is highly anticipated, but the article suggests the company may underperform expectations due to increasing competition from AMD and internal AI-GPU development by its major customers, potentially impacting its gross margins, which have already shown a declining trend from 78.4% to a forecasted 70.6%. The article also raises concerns about the sustainability of Nvidia's rapid growth and the possibility of an AI bubble burst, despite the company's innovative prowess and current market dominance.
Nvidia (NVDA) approaches its fiscal 2026 first-quarter earnings release on May 28 amid significant investor anticipation, yet faces potential headwinds that could temper its recent stellar performance. While the company has dominated the AI accelerator market with its H100 and forthcoming Blackwell GPUs, achieving near-monopoly status and substantial pricing power—evidenced by GAAP gross margins peaking at 78.4% in Q1 fiscal 2025—this advantage shows signs of eroding. A critical concern is the increasing competition, not only from external players like AMD but more significantly from Nvidia's major customers within the "Magnificent Seven" developing their own internal AI-GPUs. This internal development is expected to reduce AI-GPU scarcity, thereby diminishing Nvidia's pricing leverage. Indeed, Nvidia's GAAP gross margin has already trended downwards, from 78.4% in Q1 FY25 to 73% in Q4 FY25, with a Q1 FY26 forecast of 70.6% (+/- 50 basis points). This persistent margin decline suggests a loss of its primary competitive advantage. Furthermore, Nvidia's rapid innovation cycle, aiming for annual GPU releases, could inadvertently depreciate existing hardware and create uncertainty for buyers. The company's market capitalization has surged by $3 trillion since late 2022 to $3.3 trillion, leaving no room for error in execution or outlook. Historical precedent also suggests that game-changing technologies often experience bubble-bursting events as initial investor enthusiasm outpaces actual adoption and profitability, a risk for the current AI-driven market.
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