人工智能（AI）芯片巨头英伟达（Nvidia）将于当地时间2月25日（周三）盘后公布最新季度财报。近一年 来，该股股价涨涨跌跌，目前处于历史性低估值区间。市场对此次财报保持着高度敏感和期待。 根据FactSet（慧甚）的调查，2026财年第四季度（截至今年1月），预计其每股收益为1.51美元，营收为658.4 亿美元。研究平台Visible Alpha的预测显示，调整后每股收益为1.52美元，同比增长67%，营收达658.7亿美元，将 创下历史纪录。 尽管基本面预期强劲，但期权定价显示，华尔街交易员预计英伟达在本周末前可能出现高达6%的上下波动， 这意味着股价可能被推升至约201美元（去年11月以来未曾触及的水平），也可能被拖累至178美元。Investopedia的 期权读数也预测了约6%的隐含涨幅。MarketWatch的数据则显示，该股过去10次财报发布后的次日中位数涨幅为 3.2%。 值得注意的是，尽管英伟达仍是全球市值最高的公司（超过4万亿美元），其股价却在历史低位徘徊。尽管2月 23日，英伟达股价上涨0.9%，收于191.55美元，逆科技板块整体跌势上扬，但自去年10月底创下收盘低价以来，该 股已 ...

Core Viewpoint - Nvidia's Q3 FY2026 financial report shows record revenue of $57 billion, reinforcing the growth of the AI market amid skepticism about an AI bubble [1][2]. Financial Performance - Nvidia's Q3 revenue of $57 billion increased by 22% quarter-over-quarter and 62% year-over-year; net profit reached $31.91 billion, up 65% [2]. - Data center revenue hit a record $51.2 billion, growing 66% year-over-year, while gaming revenue was $4.3 billion, up 30% [2]. - The company returned $37 billion to shareholders through stock buybacks and dividends in the first three quarters of FY2026 [2]. Profitability Metrics - The GAAP gross margin for Q3 was 73.4%, a decrease of 1.2 percentage points year-over-year, attributed to a shift in business model and a $4.5 billion expense [3]. - Nvidia aims to improve gross margin to around 75% by the end of the fiscal year through cost improvements and business structure optimization [3]. Market Dynamics - Nvidia's revenue from the U.S. nearly doubled to $39.177 billion, while revenue from China fell over 60% to $2.973 billion due to geopolitical issues and market competition [4][7]. - The company has established partnerships with AI leaders like OpenAI and Microsoft, which are expected to enhance its ecosystem and revenue potential [4]. Strategic Outlook - Nvidia anticipates revenue of $65 billion for Q4 FY2026, with GAAP and non-GAAP gross margins projected at 74.8% and 75.0%, respectively [3]. - The company is focused on expanding its CUDA architecture to adapt to diverse workloads in AI, which ASICs struggle to meet [6]. Challenges and Responses - Nvidia faces challenges in building comprehensive computing solutions, requiring multiple components and addressing increased memory demands [5]. - The company is committed to engaging with the Chinese government to navigate market challenges and maintain a competitive edge in AI computing [7].