NVIDIA's 70% Revenue Growth Outlook May Surpass Apple and Alphabet

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NVIDIA's ecosystem growth is accelerating, with CFO Colette Kress revealing during the Q2 2027 earnings call a projected 70% revenue increase for fiscal 2028, pushing revenue to $67.3 billion and surpassing Apple and Alphabet. CEO Jensen Huang stated that demand is outpacing supply, particularly for storage chips. AI infrastructure is expanding into new on-chain sectors, including regional firms and open model ecosystems.

Dynamic Watch Beating AI News: During the Q2 fiscal year 2027 earnings call, NVIDIA CFO Colette Kress stated that the company expects revenue growth of 70% in fiscal year 2028, significantly exceeding the Wall Street consensus of 44% according to LSEG. Based on market projections of NVIDIA’s fiscal year 2027 revenue of $396 billion, a 70% increase in fiscal year 2028 would result in annual revenue of approximately $673 billion. According to current Wall Street forecasts, this scale would surpass Apple and Alphabet, making NVIDIA the second-highest-revenue U.S. technology company, behind only Amazon, which remains primarily driven by retail operations. NVIDIA CEO Jensen Huang stated that actual demand growth is “far above 70%,” but current supply capacity only allows the company to confidently forecast a 70% increase. Global supply constraints for components such as memory chips limit higher guidance, and NVIDIA will continue working with its supply chain to expand capacity. Huang noted that NVIDIA has rarely provided such long-term financial forecasts in the past, but the company can now observe next year’s compute demand, and data center partners are investing heavily in land, power, and other resources, necessitating consistent communication with partners. He also stated that demand for AI infrastructure has expanded beyond early adoption by a few hyperscale cloud providers and single cutting-edge labs to include a broader range of customers such as regional AI companies, neo-cloud providers, startups, enterprise clients, open model ecosystems, and physical AI applications.

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