Nvidia’s Q3 earnings forecast and supremacy in the AI-chip sector
Nvidia is set to unveil its Q3 earnings on Wednesday, November 20, with analysts predicting a remarkable year-over-year revenue increase of 82%, pushing total revenue close to billion. This remarkable upturn is primarily fueled by steady demand for Nvidia’s traditional Hopper chips, in addition to initial successes from its recently launched Blackwell processors. The company had earlier signaled to investors that Q3 revenue would be around .5 billion, over twice the amount reported during the same timeframe last year.
Despite these optimistic forecasts, Nvidia has encountered some hurdles, especially delays in delivering its Blackwell processors due to design modifications and ongoing supply-chain complications. Nevertheless, the company’s supremacy in the AI-chip sector remains intact, with its technology powering extensive datasets and language models for major tech corporations such as Alphabet, Microsoft, Amazon, and Meta Platforms. This strong position indicates that Nvidia is likely to continue steering investors towards notable revenue expansion in the upcoming year.
UBS analysts have pointed out the increasing investment in AI technologies, predicting that the four largest hyperscalers—crucial players in global AI infrastructure—will allocate 7 billion to capital projects related to AI next year, reflecting a 33.5% rise from the current year’s forecast. This increase in AI funding further reinforces Nvidia’s role as a frontrunner in the AI-chip industry, positioning the company perfectly to seize a substantial segment of this burgeoning market.
Supply issues and analyst target price revisions
Supply issues have emerged as a significant challenge for Nvidia in fully leveraging the escalating demand for AI chips. Although the company enjoys a stronghold in the AI accelerator market, analysts are increasingly highlighting supply chain bottlenecks that could hinder its capacity to satisfy the soaring demand in the short term. Such constraints are particularly apparent in the rollout of Nvidia’s Blackwell processors, which have experienced delays due to design adjustments and supply chain disturbances.
Last week, Nvidia CEO Jensen Huang took proactive measures to tackle these problems by urging South Korea’s SK Hynix to speed up the delivery of high-bandwidth-memory (HBM) chips. These essential components for AI systems facilitate the efficient processing of substantial datasets while utilizing less energy. This strategy emphasizes the pressing demand Nvidia faces in fulfilling the rapidly rising need for its AI chips, especially as companies across various sectors—from tech leaders like Alphabet and Microsoft to automotive giants like Tesla—boost their AI investments.
In spite of these obstacles, analysts remain optimistic about Nvidia’s long-term potential. Piper Sandler analyst Harsh Kumar recently lifted his price target for Nvidia by to 5 per share, highlighting the firm’s robust standing in the AI-chip arena. Kumar conceded that supply challenges might restrict Nvidia’s capability to surpass revenue expectations in the near term, yet he retains confidence that the company will experience substantial growth through 2025. He estimates the total addressable market for AI accelerators will increase by approximately billion by 2025, with Nvidia anticipated to secure the majority of this growth.
In a similar vein, Morgan Stanley analyst Joseph Moore also raised his price target for Nvidia, albeit more cautiously, by to 0 per share. Moore noted that while demand indicators remain strong, supply constraints could moderate Nvidia’s ability to make larger upward revisions to its revenue targets. He expects Nvidia’s Blackwell processors to generate “several billion” in sales during the January quarter, with estimates falling between billion and billion. Although this slightly undercuts earlier expectations, it still signifies a notable contribution to Nvidia’s total revenue.
In the Australian market, where the adoption of AI is accelerating across various sectors, Nvidia’s supply limitations could have significant implications. Australian businesses, particularly in industries like mining, finance, and healthcare, are increasingly leaning towards AI technologies to enhance efficiency and innovation. As the demand for AI accelerators grows, any delays in Nvidia’s capacity to deliver its innovative chips could affect the timelines of AI-driven projects in Australia. However, with Nvidia’s strong market position and ongoing efforts to resolve supply challenges, the company is well-positioned to capitalize on the global and Australian AI surge.
