Core Viewpoint - Nvidia's FY26Q3 financial report indicates a robust demand for AI computing power, with a significant revenue forecast of $500 billion from the Blackwell and Rubin platforms by the end of 2026, amidst a backdrop of global GPU shortages and a backlog of 5 million orders [1][2][30]. Financial Performance - Revenue reached $57.01 billion, exceeding expectations by nearly $2 billion and showing a year-over-year increase of 62% [2][3]. - Adjusted net profit was $31.7 billion, translating to an average daily profit of $350 million, surpassing the annual revenue of many tech companies [2][4]. - Adjusted gross margin was 73.6%, with a target of 75% for FY27, reflecting improved profitability [5][7]. Business Segments - Data center revenue was $51.2 billion, accounting for 90% of total revenue, with a year-over-year growth of 66% [9]. - The computing business grew by 56%, supported by the GB300 product line [10]. - Networking revenue doubled to $8.2 billion, driven by NVLink and Spectrum-X [13]. - Gaming revenue was $4.3 billion, up 30% year-over-year, while professional visualization and automotive segments also showed strong growth [16]. Demand and Orders - Nvidia reported a staggering demand for GPUs, with a backlog of 5 million units and a projected revenue visibility of $500 billion from AI projects through 2026 [18][30]. - Major partnerships include a 1 GW computing power agreement with Anthropic and a three-year supply deal with Saudi Arabia for 400,000 to 600,000 GPUs [18]. Technological Advancements - The Blackwell platform, particularly the GB300, is expected to dominate the market, offering performance improvements over previous models [19]. - The upcoming Rubin platform, set to launch in late 2026, aims for significant performance enhancements [19][31]. Strategic Partnerships and Supply Chain - Nvidia's growth is supported by strategic partnerships across various sectors, including collaborations with OpenAI and traditional industries like Caterpillar and Toyota [22][25]. - The company is focused on building a resilient global supply chain, with key partnerships with TSMC and other suppliers to ensure production capacity [26][27]. Future Outlook - Nvidia's financial results challenge the notion of an AI bubble, demonstrating real demand and profitability in the AI sector [30]. - Key indicators for future growth include meeting revenue targets for FY26Q4, successful launch of the Rubin platform, and maintaining supply chain stability [30][31].

5000亿订单在手！英伟达这波"算力狂欢"，真能一直嗨？ 还在纠结 AI算力需求会不会降温？英伟达FY26Q3财报直接给了答案。 单季营收 570.1亿美元，超预期近20亿，同比暴涨62%；调整后净利润317亿美元，日均净赚3.5亿美金——比不少科技公司全年营收还多。 更狠的是，公司锁定 FY27毛利率75%，还说Blackwell+Rubin平台到2026年底能稳拿5000亿收入。一边是全球GPU卖断货、500万个订单 排队，一边是Rubin平台要登场、地缘有小波动，这台"算力印钞机"能转多久？ 01 业绩拆解： 每组数据都在"碾压预期" 英伟达这季业绩不是运气，核心是 AI算力需求真爆发了。 营收盈利：量利齐飞，钱花不完 营收： 570.1亿美元，超预期551.9亿，环比涨22%，日均进账6.3亿美元。 盈利：调整后 EPS1.3美元，同比涨60%、环比涨24%；自由现金流220.9亿美元，同比增32%。 毛利率：冲刺 75%，赚钱效率再升级 调整后毛利率 73.6%，环比涨0.9个百分点，超预期。 支撑逻辑有二： Blackwell平台量产，GB300成高毛利主力；规模效应对冲成本。 还预告 FY26Q ...

美股AI泡沫恐慌情绪蔓延之际，"AI芯片巨头"英伟达（NVDA.O）交出了超预期的财务"成绩单"。 图源：英伟达公众号 美东时间11月19日周三美股盘后，英伟达公布了2026财年第三季度的财报。财报显示，英伟达第三财季营收为570.1亿美元，超出市场预期的549.2亿美元， 环比增长22%，同比增长62%。净利润为319.1亿美元，同比大涨65%，经调整后的每股收益为1.30 美元，高于市场预期的1.25美元。毛利率73.4%，同比稍 有下跌1.2个百分点。 | | GAAP | | | --- | --- | --- | | ($ in millions, except earnings per share) | Q3 FY26 | 02 I | | Revenue | $57,006 | র্ক | | Gross margin | 73.4% | | | Operating expenses | $5,839 | | | Operating income | $36,010 | র্ক | | Net income | $31,910 | $2 | | Diluted earnings per shar ...

Core Insights - Nvidia reported record revenue of $57.01 billion for Q3 FY2026, a 62% year-over-year increase, significantly exceeding market expectations [3][5] - The company provided a strong revenue guidance of $65 billion for Q4 FY2026, indicating robust growth momentum [3][7] - The Blackwell platform is a major revenue driver, with GB300 accounting for two-thirds of Blackwell's total revenue, and demand for cloud GPUs has outstripped supply [3][6][7] - The next-generation Rubin platform is progressing as planned, with the first chip delivered and mass production expected in FY2026 [3][6] - Software and services, particularly AI Enterprise and DGX Cloud, are experiencing significant growth, enhancing revenue visibility and resilience [3][6] Financial Performance - Revenue reached $57.01 billion, up 62% year-over-year and 22% quarter-over-quarter, surpassing the market expectation of $55.19 billion [5] - Net profit was $31.9 billion, reflecting a 65% year-over-year increase [5] - Gross margin was reported at 73.4% (GAAP) and 73.6% (non-GAAP) [5] - Adjusted earnings per share (EPS) were $1.30 (non-GAAP) [5] Business Segment Performance - Data center revenue was $51.2 billion, a 66% year-over-year increase [6] - Gaming/AI PC business generated $4.3 billion, up 30% year-over-year [6] - Professional visualization revenue reached $760 million, a 56% year-over-year increase [6] - Automotive and robotics revenue was $592 million, reflecting a 32% year-over-year growth [6] Future Guidance - The company expects Q4 revenue to be $65 billion (±2%) [7] - Non-GAAP gross margin guidance is set at 75.0% (±50 basis points), significantly above market expectations [7] Business Highlights and Strategic Direction - Demand for data center products remains strong, with supply being a key focus [7] - CEO Jensen Huang emphasized the emergence of new AI model manufacturers and startups across various industries and countries [7] - Nvidia is positioned as a leader in AI infrastructure, with a comprehensive system offering beyond just chip sales [10][12] Management Commentary - CEO Jensen Huang noted that computational demand in training and inference is accelerating, creating a compounding effect [11] - CFO Colette Kress confirmed that demand for AI infrastructure continues to exceed expectations and projected a gross margin of around 70% by FY2027 [12] - Management addressed investor concerns about sustainability of growth, indicating that demand is accelerating and new applications are emerging [13] - Inventory levels have increased, but management clarified that this is likely a strategic move to prepare for future demand rather than a sign of weakening demand [15]

Core Insights - The article discusses Masayoshi Son's regret over selling SoftBank's stake in NVIDIA, which could have been worth over $150 billion today if held [1][2] - The conversation highlights NVIDIA's transformation into a key player in the AI era, emphasizing the importance of timing in high-growth industries [2] - SoftBank's recent strategic moves, including selling NVIDIA shares to invest in OpenAI, reflect a shift in focus towards AI startups [3][4] Group 1: NVIDIA Investment History - SoftBank invested approximately $3.6 billion in NVIDIA in May 2017, acquiring a 4.9% stake, but sold all shares by January 2019 for about $6.9 billion, realizing a profit of around $3.3 billion [1][3] - In October 2025, SoftBank sold 32.1 million shares of NVIDIA for approximately $9.17 billion as part of its asset monetization strategy [3] - The company has a history of buying and selling NVIDIA shares, indicating a pattern of missing out on significant gains during NVIDIA's growth phases [5] Group 2: Strategic Shift Towards AI - SoftBank's decision to divest from NVIDIA was influenced by its investment in OpenAI, where it plans to invest $22.5 billion, increasing its stake from 4% to 11% [3][4] - The Vision Fund's $19 billion profit in the second quarter was bolstered by investments in the AI ecosystem, including chips and large language models [4] - Despite selling NVIDIA shares, SoftBank remains involved in AI projects that rely on NVIDIA technology, such as the $500 billion Stargate data center project [4] Group 3: Market Dynamics and Short Selling - NVIDIA's stock has become a focal point for both bullish and bearish investors, with significant short positions being taken by notable figures like Michael Burry [6][12] - The article outlines the volatility surrounding NVIDIA's stock, driven by large short positions and the potential for significant price swings [14][20] - Concerns about NVIDIA's valuation and the sustainability of its growth are highlighted, with analysts questioning the timing of cash flow realization in relation to capital expenditures [10][17]

Core Insights - The article discusses the missed investment opportunity by SoftBank's founder Masayoshi Son in NVIDIA, highlighting the regret over selling shares before the company's significant growth driven by AI demand [1][2][4]. Group 1: Investment History - SoftBank invested approximately $3.6 billion in NVIDIA in May 2017, acquiring a 4.9% stake, but sold all shares in January 2019 for about $6.9 billion, realizing a profit of approximately $3.3 billion [1][7]. - If SoftBank had retained its shares, their current value would exceed $150 billion [1][7]. - In October 2025, SoftBank sold 32.1 million shares of NVIDIA for approximately $5.83 billion as part of its asset monetization strategy [5][7]. Group 2: Strategic Shifts - SoftBank's recent stock sales are part of a broader strategy to invest heavily in AI projects, including a $22.5 billion investment in OpenAI, which will increase its stake from 4% to 11% [5][8]. - The company aims to maintain financial stability while providing investment opportunities, as stated by CFO Yoshiaki Goto [5]. Group 3: Market Reactions and Analyst Perspectives - Despite SoftBank's stock sales causing a 2% drop in NVIDIA's share price, the company remains involved in several AI projects reliant on NVIDIA technology, such as the $500 billion Stargate data center project [6]. - Analysts suggest that SoftBank's actions should not be interpreted as a negative stance towards NVIDIA but rather as a necessity for funding its AI investments [6]. Group 4: Short Selling Dynamics - NVIDIA has become a significant target for short sellers, with a nominal short position exceeding $48 billion as of October 2025, making it the largest single short position in the U.S. capital markets [16][21]. - The volatility of NVIDIA's stock is largely influenced by the substantial options positions, leading to exaggerated price movements [23]. - Short sellers express concerns over NVIDIA's pricing power, the AI investment return timeline, and potential accounting adjustments affecting depreciation [17][18][19].

Group 1 - NVIDIA CEO Jensen Huang visited TSMC to request more chips, with the exact quantity being confidential [1] - Huang emphasized the strong and growing business demand for chips, particularly for the Blackwell platform, which includes GPUs, CPUs, network chips, and switches [1] - TSMC's Chairman C.C. Wei confirmed Huang's visit was to encourage and thank TSMC for their hard work in meeting the increasing demand [1] Group 2 - Huang stated that AI is the most important technology of this era, impacting every country and company, and reaffirmed Taiwan's critical role in the global semiconductor manufacturing landscape [2] - Huang mentioned ongoing communication with governments worldwide to help them understand the importance of AI technology and its development [2]

Core Insights - NVIDIA's CEO Jensen Huang presented a vision for a new industrial revolution driven by AI at the GTC conference, introducing the revolutionary Blackwell platform and the concept of the "AI factory" [2][3] - The AI factory is designed to produce intelligent tokens efficiently, marking a shift from traditional data centers to specialized AI production facilities [5][6] Accelerated Computing: Beyond Moore's Law - Huang highlighted the end of Moore's Law, stating that the increase in transistor count no longer leads to proportional performance and power efficiency improvements [3][14] - NVIDIA's solution is the "accelerated computing" paradigm, which leverages a robust CUDA ecosystem to maximize GPU capabilities [3][15][17] AI Factory: The Core Infrastructure of a New Industrial Revolution - The AI factory is focused solely on producing intelligent tokens, which are essential for AI understanding and generating information [5][6][38] - The demand for computational resources is experiencing exponential growth due to the increasing complexity of AI models and their applications [5][39] Blackwell Platform: A Revolutionary Product of Extreme Collaborative Design - The Blackwell platform represents a significant leap in performance, with the Grace Blackwell (GB200) achieving ten times the performance of its predecessor, the H200 [6] - This platform is designed as a complete computing unit, integrating chips, systems, and networks to ensure optimal performance and cost-effectiveness [6][39] Physical AI: Bridging Digital Intelligence with the Real World - Huang introduced the concept of "Physical AI," which requires a new computing architecture to enable AI to interact with the physical world [7] - This architecture involves three types of computers: one for training models, one for simulation, and one for operating robots [7] American Manufacturing and Future Outlook: From Blackwell to Rubin - Huang emphasized the importance of American manufacturing, detailing the production process of Blackwell in the U.S. [8][9] - The next-generation platform, Rubin, is set to be introduced with a commitment to continuous innovation and improvement [9] Expanding New Frontiers: From 6G Communication to Quantum Computing - NVIDIA announced a partnership with Nokia to develop a new product line, NVIDIA ARC, aimed at revolutionizing wireless communication through AI and accelerated computing [21][22] - The company is also focusing on quantum computing, highlighting the integration of quantum processors with NVIDIA's GPU technology for enhanced computational capabilities [25][27] The Essence of AI: New Computing Stack and AI Factory - AI is described as a transformative force that has redefined the computing stack, moving away from traditional software development to data-intensive programming [31][33] - The AI factory is essential for generating the tokens that AI systems require to function effectively, marking a departure from conventional computing paradigms [38][39]

Core Insights - Nvidia's Q2 revenue reached $46.7 billion, a year-over-year increase of 56% and a quarter-over-quarter increase of 6%, surpassing market expectations of $46.06 billion [1][2] - Non-GAAP gross margin was 72.7%, down 3.0 percentage points year-over-year but up 11.7 percentage points quarter-over-quarter; after excluding the impact of H20, the gross margin was 72.3% [1][2] - Net profit for the quarter was $25.78 billion, a 52% increase year-over-year and a 30% increase quarter-over-quarter, exceeding market expectations of $23.46 billion [1][2] - Non-GAAP diluted EPS was $1.05, reflecting a 54% increase year-over-year and a 30% increase quarter-over-quarter [1][2] Performance Guidance - The company expects Q3 revenue to be $54 billion, with a fluctuation of 2% [2] - Projected GAAP and non-GAAP gross margins are 73.3% and 73.5%, respectively, with a fluctuation of 50 basis points [2] - The company anticipates a non-GAAP gross margin of around 70% by the end of the year [2] Revenue Breakdown - Data center revenue for Q2 was $41.1 billion, up 56% year-over-year and 5% quarter-over-quarter [2] - Gaming and AIPC revenue was $4.3 billion, reflecting a 49% increase year-over-year and a 14% increase quarter-over-quarter [2] - Professional visualization revenue was $600 million, up 32% year-over-year and 18% quarter-over-quarter [2] - Automotive and robotics revenue reached $590 million, a 69% increase year-over-year and a 3% increase quarter-over-quarter [2] Blackwell Platform - The Blackwell platform significantly contributed to revenue, with a 17% quarter-over-quarter growth, accounting for nearly 70% of data center computing revenue [2] - The GB200NVL system is widely adopted and deployed among CSPs and consumer internet companies [2] - The company has successfully transitioned factory production to support GB300 capacity enhancement, with current weekly production at approximately 1,000 racks [2] H20 and China Market - Nvidia did not sell H20 chips to the Chinese market in Q2, resulting in a $4 billion reduction in H20 sales [3] - The company released $180 million worth of inventory to customers outside of China during Q2 [3] - Nvidia sees a potential opportunity of $50 billion in the Chinese market if competitive products can be introduced [3] - AI infrastructure capital expenditure is still in its early stages, expected to reach $3-4 trillion by 2030 [3]

Core Viewpoint - Nvidia's Q2 FY2026 earnings report exceeded market expectations, indicating sustained demand for AI infrastructure with sales growth projected to remain above 50% [3][4][6] Financial Performance - Nvidia's revenue and profit surpassed market forecasts, with a notable 35% increase in stock price this year, although there was a slight decline in after-hours trading due to data center revenue not meeting expectations [4][6] - The company anticipates an additional $7 billion in revenue for Q3, primarily driven by data center business [16] Product Development - Key products such as the Blackwell and Rubin platforms are showing significant progress, with Blackwell achieving a record high performance and a 17% quarter-over-quarter growth [5][20] - The GB300 chip has entered mass production, with weekly output expected to reach approximately 1,000 racks, and the Rubin chip is on track for large-scale production next year [5][6] Market Dynamics - The AI infrastructure market is projected to reach $3-4 trillion in the next five years, driven by the increasing demand for computational power from AI applications [7][8] - Nvidia's potential revenue in the Chinese market is estimated to reach $50 billion by 2025, with a compound annual growth rate of 50% expected [7][15] Geopolitical Factors - The U.S. government has begun approving licenses for the sale of H20 chips to China, with Nvidia estimating potential revenue of $2-5 billion from these sales in Q3 [6][15] - The company is actively engaging with the U.S. government to facilitate the sale of Blackwell chips to China, emphasizing the strategic importance of the Chinese market [15][16] Industry Trends - The demand for AI infrastructure is being fueled by the rapid evolution of AI technologies, with companies increasingly adopting AI-driven solutions across various sectors [21] - Nvidia's transition from a GPU company to a full-stack AI infrastructure provider is enhancing its competitive edge in the market [11][13]