NVIDIA Reports Strong Earnings Boosted by AI Demand, Delivery Forecasts
NVIDIA (NVDA) continues to generate excitement during earnings calls, often providing more insights than anticipated. Key areas of focus this time included GPU demand, AI factories, and challenges in China.
Prior to yesterday’s earnings reveal, I sought clarity on two main items.
Clarity on Lost GPU Sales to China
First, I wanted to know if the company would provide additional guidance on its projected $15 billion in write-downs from lost H20 GPU sales to China. The response was affirmative. CEO Jensen Huang and CFO Colette Kress confirmed last month’s guidance, indicating that Q1 losses totaled $7 billion and Q2 is expected to reach $8 billion.
Huang also addressed the potential $50 billion market in China, emphasizing its significance for NVIDIA.
Significant Delivery Ramps in GB200 NVL72 Systems
Second, I was curious about the production ramp of the new GB200 NVL72 rack systems, which have an average selling price of over $3 million. Reports indicated that NVIDIA delivered 1,500 GB200 units in April, leading to projections of at least 5,000 units for Q2. If the number exceeds 10,000, it would signal strong investor confidence.
Colette’s remarks anchored this optimism. Major hyperscalers are deploying nearly 1,000 NVL72 racks per week—totaling 72,000 Blackwell GPUs. Microsoft has rapidly deployed huge quantities of these systems. This pace could potentially result in over 15,000 units shipped in Q2.
NVIDIA shares surged to $144 in after-hours trading, with projections suggesting a possible rise above $150 soon. The $45 billion quarterly guidance appears conservative given the anticipated production.
Investments in AI Factories
Last week, following Huang’s keynote at Computex, I noted his frequent mention of “AI factories.” Colette confirmed this notion by stating, “Our customers’ commitments are firm,” reflecting a 73% increase in Datacenter revenue driven by AI factory build-outs.
This elevated demand stems from major cloud service providers like Microsoft Azure, Amazon AWS, and Google Cloud, alongside companies like Tesla and OpenAI, all of which are in a multi-year build-out phase for AI capabilities.
Huang highlighted that companies like Tesla require NVIDIA’s solutions for various high-tech applications, reinforcing the growing trend in AI-driven demand.
Upcoming Product Innovations
NVIDIA is also preparing to unveil its next-generation GB300 systems, which began sampling earlier this month. These units are designed for a smooth transition from the GB200, promising high performance while maintaining compatibility.
This seamless integration is central to NVIDIA’s strategy and product roadmap, enhancing customer satisfaction through consistent improvements in their systems.
Global Trends in AI and Robotics
Interestingly, Huang emphasized that nations are also recognizing the necessity of controlling their data for economic value, suggesting a global shift towards developing localized AI capabilities.
In practice, companies focusing on robotics and AI applications are already leveraging simulation and synthetic data training to maximize operational efficiencies.
NVIDIA Leads AI Factory Innovations as Global Demand Grows
BMW was the first automaker to use NVIDIA Omniverse for designing new factory operations through “digital twins.” Now, countries are beginning to leverage similar technologies to improve areas such as urban planning, agriculture, education, and supply chains aimed at reducing poverty.
NVIDIA’s technology is facilitating AI factory projects across various industries. Major companies like AT&T, BYD, Capital One, Foxconn, MediaTek, and Telenor are launching significant initiatives supported by sovereign clouds in locations like Saudi Arabia, Taiwan, and the UAE. Demand for AI infrastructure is projected to reach tens of gigawatts soon.
Colette highlighted the rapid acceleration of AI factory deployments, noting that nearly 100 NVIDIA-powered factories have been initiated this quarter. This marks a two-fold increase from last year, with the number of GPUs in use also doubling during the same timeframe.
Export Controls and AI Development in China
Jensen Huang, CEO of NVIDIA, dedicated a significant portion of his remarks to discussing the impact of export controls on U.S.-China relations regarding AI development. He emphasized that China is a leading AI market, home to many of the world’s AI researchers.
Huang stated that restrictions under current U.S. policy effectively close a $50 billion market to American companies, which may hinder U.S. competitiveness in the long run. He argued that withholding technology may force China to create its AI infrastructure independently, increasing global competition.
According to Huang, China’s innovation will continue with or without U.S. chip technology. He expressed that the primary concern is not whether China will develop AI, but whether it will do so on American platforms. Export restrictions may inadvertently strengthen China’s technological capabilities globally.
Asserting that U.S. policies should focus on enhancing American platforms, Huang mentioned that collaboration with global developers, including those in China, is essential for U.S. leadership in AI. He indicated that AI platforms must remain open source to maintain this competitive edge.
NVIDIA’s stock (NVDA) is anticipated to open above $140, providing a potential buying opportunity for investors following significant demand trends. Analysts predict NVIDIA could reach $500 billion in revenue over the next five years, supported by the AI economy.
The company is projected to become a $1 trillion entity by the 2030s, possibly making it the first company to achieve a $5 trillion market cap.
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The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
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