【免责声明】本文仅代表作者本人观点，与和讯网无关。和讯网站对文中陈述、观点判断保持中立，不对所包含内容 的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考，并请自行承担全部责任。邮箱： news_center@staff.hexun.com 截至2026年2月26日 10点45分，上证科创板人工智能指数（950180）上涨0.12%，成分股云天励飞 上涨5.71%，思看科技上涨3.88%，天准科技上涨3.56%，海天瑞声上涨3.37%，芯原股份上涨2.02%。科 创人工智能ETF华夏（589010）多空胶着，最新报价1.59元。拉长时间看，截至2026年2月25日，科创 人工智能ETF华夏近2周累计上涨0.76%。 消息面，英伟达首席执行官黄仁勋在接受媒体采访时，对即将到来的GTC2026大会进行预热，明确 表示将在会上揭晓"世界前所未见"的全新芯片，引发业界广泛关注。AI浪潮带动算力需求爆发，服务 器、AI芯片、光芯片、存储、PCB板等环节价值量将大幅提升，建议关注高速PCB龙头沪电股份和深南 电路、全球服务器ODM龙头工业富联、AI芯片设计厂商寒武纪-U、国产处理器龙头海光信息、封装基 板厂 ...

英伟达将于周三公布财报，其股价隐含波动率为 4.4%，所有人的目光都集中在黄仁勋能否交出满意答卷。 我们不会在此花费太多时间，因为坦率地说，我们没有什么独到的见解。 原因何在？ 我能给出的最佳解释是，投资者仍更青睐供应链上游的公司，如存储、半 英伟达将于周三公布财报，其股价隐含波动率为 4.4%，所有人的目光都集中在黄仁勋能否交出满意答卷。 我们不会在此花费太多时间，因为坦率地说，我们没有什么独到的见解。 原因何在？ 我能给出的最佳解释是，投资者仍更青睐供应链上游的公司，如存储、半导体设备、台积电、光模块等，这些公 司终于开始获得定价权，这可能以牺牲 GPU/ASIC 利润率为代价。 除了常见的 "AI 周期 / 资本支出"杂音外，空头的主要顾虑在于：1) TPU 和 ASIC 带来的竞争加剧；2) 存储价格 上涨引发的利润率担忧；3) 数据中心建设受电力限制制约。 从这个角度看，当前格局颇为有趣：股价毫无起色，而管理层有机会借此消除市场源头信息加微WUXL7713对 增长和利润率的担忧。 过去六个月，该股一直在震荡区间内横盘整理，表现明显逊于 SOX 指数，令许多投资者感到沮丧。 过去六个月，该股一直在震荡 ...

Group 1 - The overall Server market is stabilizing, with ODMs focusing on AI Server development, particularly with NVIDIA's new Blackwell platform products [1] - TrendForce estimates that Blackwell GPUs will account for over 80% of NVIDIA's high-end GPU shipments this year [1] Group 2 - North American CSP giant Oracle is expanding its AI data centers, benefiting companies like Foxconn, Supermicro, and Quanta [2] - Supermicro's growth this year is primarily driven by AI Servers, having secured some GB200 Rack projects [2] - Quanta has successfully expanded its GB200/GB300 Rack business due to collaborations with major clients like Meta, AWS, and Google, along with Oracle orders [2] - Wiwynn is deepening its partnerships with Meta and Microsoft, expecting performance growth in the second half of the year, focusing on ASIC AI Servers [2] Group 3 - The expansion of AI data centers will be crucial for the scaling of the liquid cooling industry [2] - Liquid cooling solutions are increasingly being adopted for high-end AI chips, with new data centers incorporating "Liquid Cooling Ready" designs to enhance thermal management efficiency [2] Group 4 - Liquid cooling is becoming a standard configuration for high-performance AI data centers, driving demand for cooling components [4] - Fositek has begun shipping components for the GB300 platform, competing with Danfoss in the supply of quick connectors for AWS ASIC liquid cooling [4] - Auras is actively entering the data center liquid cooling market, with its business becoming a core growth driver, serving major clients like Oracle, Supermicro, and HPE [4] - Auras has started supplying liquid cooling products to Meta, establishing a foundation for future participation in the GB200 platform's liquid cooling supply chain [4]

Core Viewpoint - Nvidia has transformed from a leading chip manufacturer to a full-stack AI infrastructure leader, with a 50% stock price increase in three months, driven by strong product offerings and robust financial performance [1][2][9]. Financial Performance - Nvidia maintains a gross margin of over 75% and expects Q2 revenue to reach $45 billion, exceeding market expectations [1][9]. - The company has a free cash flow margin exceeding 60%, indicating strong operational efficiency [1][14]. Product Roadmap - The upcoming GB300 series (Blackwell Ultra) is expected to enhance inference throughput and memory utilization by 50% [4]. - By Q4 2025, the NVL72 will achieve scale in large data centers, becoming a cornerstone for Nvidia's high-margin data center inference workloads, which currently account for over 70% of its data center business [4][9]. - The Vera Rubin architecture, set to launch in H2 2026, will offer over three times the inference computing capability compared to GB300, while maintaining backward compatibility [4][5]. - The Rubin Ultra design, expected by 2027, aims to deliver up to 15 exaFLOPS of FP4 throughput, significantly enhancing Nvidia's position in AI inference cloud [5][9]. Market Position and Competitive Landscape - Nvidia's structural advantages, including dominant platform economics and a deep ecosystem, position it as a core holding in AI infrastructure [2][10]. - The long-term potential market for AI is projected to reach $1 trillion, with infrastructure needs estimated at $300 billion to $400 billion [10][12]. - Despite competitive pressures from AMD and other custom chip developers, Nvidia's established software stack (CUDA, NeMo) and supply chain integration provide a buffer against market share erosion [12][17]. Valuation Metrics - Nvidia's current P/E ratio stands at 54, with a forward P/E of 40, indicating a premium valuation compared to industry averages [12][14]. - The company's PEG ratio is 0.68 (GAAP) and 1.37 (non-GAAP), suggesting that its valuation is at least partially supported by growth [14]. - Nvidia's expected EV/Sales ratio is 21, and EV/EBIT ratio is 34, reflecting a significant premium over industry standards, which reinforces its growth assumptions [14]. Strategic Outlook - Nvidia's roadmap for the next three years includes the launch of Blackwell GB300 in 2025, Vera Rubin in 2026, and Rubin Ultra in 2027, ensuring continued product leadership and predictable profitability [9][17]. - The company plans to invest over $10 billion in next-generation AI research and development, indicating a commitment to maintaining its competitive edge [12][15].