Amid xAI’s Colossus and Amazon’s (AMZN, Financial) Project Rainier supercomputers, Nvidia (NVDA, Financial) remains the linchpin of most AI operations, with xAI particularly dependent on it. However, Amazon is taking an independent route with new AI accelerator chips to challenge Nvidia’s monopoly. While CEO Jensen Huang is steering Nvidia toward sustained prosperity by protecting market share through diversification and expanding AI inference capabilities, the market is inevitably becoming saturated with more players. My valuation model indicates Nvidia is moderately undervalued at present, but in the next three to five years, a significant valuation decline is likely due to an impending revenue contraction, according to my analysis.
Operational analysis
Nvidia has long been established as the unrivaled AI accelerator provider, but the market is subtly shifting. New entrants, such as Amazon with its Trainium3 chip announced at re:Invent, and Google’s (GOOGL, Financial) (GOOG) TPUs, are likely to pressure Nvidia’s market position in the long term. However, for now, Nvidia remains the undisputed leader in AI chip design.
Nvidia’s flagship GPUs, such as the H100, have played a critical role in data centers, leading to the company accounting for 98% of global GPU shipments in 2023. Despite developing their own chips, companies like Amazon continue collaborating with Nvidia. For example, Amazon's Project Ceiba involves building an AI supercomputer exclusively on AWS using 20,736 Nvidia GB200 Superchips, with 414 exaflops for Nvidia’s own AI R&D.
Competitors such as Cerebras and Groq are also targeting the AI inference market as training workloads diminish. Nvidia is responding by enhancing its GPUs for inference tasks while exploring unified solutions that bridge the gap between training and inference. This is critical for Nvidia to remain relevant, as one of the core risks of investing in Nvidia is its vulnerability to a revenue contraction, which could inevitably lead to a valuation decline.
Companies like Microsoft (MSFT, Financial), Meta (META, Financial), and Google have invested billions of dollars in infrastructure built around Nvidia’s GPUs and CUDA platform. CUDA has been instrumental in Nvidia’s dominance, offering over 400 CUDA-accelerated libraries tailored to tasks like linear algebra, deep learning, and data processing. These reduce development time and improve performance for AI applications. Given the high switching costs associated with migration, Nvidia’s position is robust. However, competitors such as Advanced Micro Devices (AMD) (with ROCm), Intel (INTC) (with oneAPI), and emerging players like Spectral Compute are developing alternatives to challenge Nvidia’s dominance. Looking 10 years ahead, these dynamics are likely to compound, leading to an unavoidable revenue decline as AI infrastructure demand tapers with the conclusion of the bulk of the AI training phase.
Nevertheless, Nvidia’s proactive approach to market consolidation and share protection underpins a bullish outlook for the near future. While I have cautiously noted the medium- to long-term risk of revenue contraction, the company’s fair valuation at present, without accounting for future revenue declines, positions it for continued growth over the next three years—consistent with the period used in my valuation model.
In the near term, Nvidia will thrive as Big Tech companies compete to build AI supercomputers. As of late 2024, 384 of the world’s TOP500 supercomputers are powered by Nvidia technologies, representing nearly 70% of the list. Nvidia’s Eos supercomputer is one of the fastest AI-focused systems globally and is optimized for training large AI models. Elon Musk’s xAI Colossus supercomputer, powered by Nvidia Hopper GPUs, plans to expand to one million GPUs, potentially becoming one of the largest AI supercomputers worldwide. In contrast, Amazon’s Project Rainier, leveraging Trainium chips, represents a strategic move to challenge Nvidia’s dominance. Amazon has partnered with Anthropic to use Project Rainier for training advanced AI models. This underscores the delicate balance Nvidia must maintain between defending its competitive advantage and collaborating with peers.
Valuation analysis
For my valuation analysis, I have used a period from now until January 2028, accounting for approximately three years of robust growth before I expect heavy volatility due to slowing revenue growth and eventual contraction. My Fiscal 2028 revenue estimate is $260 billion, with an EBITDA margin assumption of 65%, leading to an EBITDA estimate of $169 billion. To be conservative, I have opted for a terminal EV-to-EBITDA ratio of 35, significantly lower than its five-year average of 49 due to slowing growth likely at the time. Consequently, my estimate for Nvidia’s Fiscal 2028 enterprise value is $5.92 trillion. Given the company’s current enterprise value of $3.38 trillion, the implied CAGR from December 2024 to January 2028 is 20.51%.
Nvidia’s weighted average cost of capital is 18.62%, with an equity weight of 99.68% and a debt weight of 0.32%. Equity costs 18.68%, while debt costs 2.33% after tax. Discounting the company’s January 2028 enterprise value back to December 2024 using the WACC results in a present-day intrinsic enterprise value of $3.54 trillion. Compared to the current enterprise value of $3.38 trillion, this implies a margin of safety for investment of 4.85%.
For investors with a lower risk tolerance, we may consider the returns likely if the stock were sold at the beginning of 2027 and bought now, which would more significantly protect against downside cyclical dynamics that become increasingly probable as time passes. A conservative estimate for the company’s January 2027 annual revenue is $235 billion. At an EBITDA margin of 62%, the company will have an annual Fiscal 2027 EBITDA of $145.7 billion. At an EV-to-EBITDA ratio of 40, the company’s enterprise value would be $5.83 trillion, indicating a 31.31% CAGR from December 2024 (EV of $3.38 trillion) to January 2027.
Risk analysis
As mentioned, the greatest risk is that Nvidia fails to reach a $6 trillion valuation before market confidence erodes due to revenue contraction caused by slowing AI infrastructure expenditures. My sentiment and sensitivity models suggest Nvidia may peak between $4.5 trillion and $5 trillion in enterprise value before cyclical dynamics take hold. While investing based on fundamentals is optimal, market movements often deviate from these principles due to distortions against fair value tied to future earnings and revenue expectations. Given Nvidia’s prominence, a valuation decline could precede a revenue contraction by one to two years.
Nvidia is also heavily reliant on a limited number of foundries, particularly TSMC (TSM), for chip manufacturing. In my recent macroeconomic and geopolitical analyses on defense companies, I highlighted the significant risk of a financial crisis—or, in a worst-case scenario, a depression—should China blockade or militarily invade Taiwan. Therefore, I currently consider Nvidia a high-risk investment from a macroeconomic standpoint. Exposure to the stock may be better suited to moderated, risk-mitigated portfolio strategies, heavily oriented toward short-term U.S. Treasuries (which Berkshire Hathaway (BRK.A) (BRK.B) currently holds 30% of its assets in), alongside some gold and lower-risk, well-valued, dividend-oriented equities.
Conclusion
My valuation model suggests Nvidia has approximately a 5% margin of safety and a potential three-year enterprise value CAGR of over 20%, assuming rational market pricing based on present revenues and earnings. However, due to the anticipatory nature of markets, Nvidia may peak at a lower valuation before cyclical factors weigh on investor sentiment. It is crucial to remain mindful of volatility risks while recognizing Nvidia’s substantial near-term growth potential as it continues to defend and expand its leading position in AI chip technology.
