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What Will NVIDIA‘s Stock Price Reach by 2033?

NVIDIA‘s meteoric stock price rise over the past decade, fueled largely by the company‘s market-leading position in GPUs (graphics processing units) and the emerging growth of AI (artificial intelligence), has been nothing short of remarkable. In just the past five years alone, NVIDIA’s share price has skyrocketed over 1,100% from around $30 in late 2018 to over $400 at the time of this writing.

So what could power NVIDIA‘s next decade of stock price performance? And more specifically, what could shares of this semiconductor juggernaut be trading at by October 2033? While impossible to predict with certainty, by analyzing current positioning, growth drivers, and potential risks, we can make an informed projection.

Nvidia‘s Commanding Market Position Provides Platform for Growth

Nvidia‘s dominance in visual computing platforms and services has only strengthened over the past several years. The company now powers over 250 million GeForce gaming GPUs across PCs and cloud platforms as well as leads in professional visualization, data science/AI, autonomous vehicles, and the metaverse.

Specific to gaming, Nvidia owns over 80% discrete GPU market share based on the latest reports, showcasing the true scale and reach of their graphics leadership. GeForce also rules supreme in the fastest growing segment – laptops – with over 85% share.

On the data center and AI front, the company’s leadership may be even more substantial. The NVIDIA computing platform accelerates 9 of the top 10 supercomputers in addition to powering major cloud infrastructures like Amazon Web Services, Microsoft Azure, and Google Cloud.

With dominance across these large and strategic end-markets, Nvidia enjoys pricing power, customer loyalty/stickiness, and a consistent funnel of customer budget dollars to fund further innovations. This virtuous cycle strengthens Nvidia‘s positioning while weakening rivals attempting to keep pace.

Discrete GPU Market Share

Company Market Share
Nvidia 84%
AMD 16%

Source: Jon Peddie Research

Multi-Billion Dollar Market Expansions Will Buoy Growth

Major market expansions lie ahead that play directly into Nvidia’s core competencies around simulated reality and AI-centric data center computing.

As one example, IDC forecasts the market for accelerated computing to reach $100 billion by 2027. Much of this growth will come from scaling AI across the world’s largest industries and boosting climate and drug discovery research. Nvidia’s end-to-end AI platform, which spans everything from cloud-native services to processors and networking, makes them a primary benefactor. Expanding partnerships with leading hyperscalers ensure their technology underpins many next-gen services.

AI Accelerated Computing Market Size

Year Market Size Growth
2022 $28B 16.7%
2027 $100B 30.8% CAGR

Source: IDC

Gaming offers another avenue for top-line growth. There remains substantial room for penetration by tapping into the nearly 3 billion gamers worldwide. Upgrades to support resource-intensive features like ray tracing and AI-powered graphics will drive consistent GPU sales.

Lastly, opportunities in the auto sector show immense promise. Nvidia DRIVE technology already powers over 350 vehicle models and the addressable market here could eventually eclipse gaming itself. As autonomous driving functionality becomes standard, growth will rapidly scale over the coming decade. Goldman Sachs recently estimated the TAM for AI applications in the auto industry to reach $72B by 2030.

Auto Industry AI TAM Growth

Year Market Size Growth
2022 $1.4B
2025 $4B 34% CAGR
2030 $72B 95% CAGR

In summary, Nvidia competes within some of technology’s most attractive and fast-growing ecosystems. Their ability to deliver category-defining products tailored to customer needs ensures they capture a disproportionate amount of industry profits.

Competitor Deep Dive

Make no mistake, Nvidia faces no shortage of competitive threats across its various product categories. Here we‘ll analyze the landscape and competitive positioning of their largest rivals.

AMD – Resurgence Powered by Architectural Innovation

Arguably Nvidia’s most formidable challenger within the GPU domain recently has been AMD. Long an also-ran in graphics, AMD invested heavily in new architectural improvements that significantly boosted performance. Improvements included additional stream processors, faster interconnects between components, and enhanced software optimization. These enhancements combined with leveraging the latest 7nm manufacturing nodes fueled 50-100% performance gains across product generations.

On the AI acceleration front, AMD offers Instinct GPUs that compete directly with Nvidia’s V100 and A100 data center offerings. Though competitive on peak performance, AMD still faces challenges matching Nvidia’s AI software ecosystem and continued optimization from relentless focus in this space. However, with strong roadmap execution and increasing data center processor share, AMD does appear positioned to capture discrete market share gains versus Nvidia looking ahead.

AMD v. Nvidia Discrete GPU Market Share

Year AMD Share Nvidia Share
2019 16% 84%
2022 25% 75%

Source: Jon Peddie Research

Intel – Leveraging IDM Manufacturing Prowess

Intel’s semiconductor prowess, bolstered by leading integrated device manufacturing infrastructure, makes them a formidable competitor across Nvidia’s product portfolio.

In data center, Intel’s Xeon processors still dominate but face accelerating erosion from AMD and other Arm-based offerings. However, through packages combining Xeons with GPUs, FPGAs, and AI accelerators, Intel provides high performance systems-level solutions. Though still early with modest revenues, Intel has proven quite responsive recently in neutralizing competitive threats.

On graphics, Intel’s Arc lineup targets the entry discrete market with very competitive $200-300 offerings. Success here could expand Intel’s presence upmarket over time and into the enterprise. However, much like AMD, they face challenges stacking up to Nvidia’s software ecosystem.

Ultimately Intel competes broadly across high performance compute markets and leverages manufacturing leadership for differentiation. Though share erosion remains likely in specific segments, Intel will remain a top player in this space for the foreseeable future.

Qualcomm – Platformization of Key Auto & 5G Edge Markets

While not directly competing in core GPU/AI acceleration markets, Qualcomm’s Snapdragons power various intelligent edge devices like PCs, vehicles, smartphones etc. And their ability to integrate 5G modems alongside compute/ML acceleration makes Snapdragons a compelling platform choice for customers.

As automakers seek out self-driving capabilities, Qualcomm aims to provide an end-to-end hardware/software platform combining autonomy functionality and cabin experience management. Already Design Wins exceed $10B in lifetime revenue with continued momentum.

Success “platformizing” key edge segments like auto and IoT could allow Qualcomm to capture and own key relationships, even in spaces utilizing Nvidia’s latest GPU offerings. However, their software ecosystem remains nowhere near as expansive. Either way, Qualcomm’s aggressive push towards AI and edge computing keeps them firmly on Nvidia’s radar looking ahead.

Growth Driver Deep Dives

In addition to Nvidia’s core gaming and data center markets, emerging use cases offer significant growth potential over the next decade.


As immersive digital worlds become mainstream over the coming years, Nvidia‘s Omniverse platform aims provide the underlying graphics, simulation and collaboration infrastructure to fuel the Metaverse. This platform brings together Nvidia‘s expertise in ray tracing, AI modeling, simulation and more to enable next generation applications spanning gaming, robotics and industrial digital twins.

Nvidia believes that over the next 10 years, the cumulative revenue opportunities for simulated worlds will drive well over $1 trillion in sales of specialized hardware, software, and cloud services to power the Metaverse. Their early move to provide an end-to-end technology stack to support customer needs ensures they remain the de facto platform for Metaverse builders.

Autonomous Vehicles

Today Nvidia DRIVE technology already powers 23 of the top 25 electric vehicle platforms, underscoring their momentum towards powering next-gen software defined vehicles. In a fully autonomous future, DRIVE centralizes all computationhorsepower to handle sensor processing, perception, planning and mapping without driver input. Success will require sophisticated, redundant systems leveraging AI and ability to process insane amounts of data – playing directly to Nvidia‘s strengths.

Goldman Sachs recently estimated the TAM for AI applications in the auto industry to reach $72B by 2030. Capturing even 25% share here would contribute over $18B in high margin licensing revenue – equivalent to nearly 20% of Nvidia’s current annual sales.


As mentioned Nvidia‘s Omniverse platform provides the underlying engine to enable global teams to collaborate in simulated 3D worlds. Use cases span conceptual design reviews, interactive training environments, digital twins of factory floors and more. Over 600 companies currently leverage Omniverse to streamline workflows.

Nvidia estimates that over 50 million 3D designers and engineers stand to benefit from gaining easy access to photorealistic, simulated collaboration. If we assume even 15% of design/engineering professionals convert to power users on Omniverse at $50 per month, that represents $1.13B per year in recurring revenue potential for Nvidia.

In summary, multiple emerging technology megatrends offer Nvidia greenfield opportunities to deploy their AI and simulation expertise. Their software platforms seek to cultivate expansive, high value-add ecosystems across these domains. Demonstrated success in gaming provides the blueprint. Capturing just fractions of the full addressable markets across Metaverse, Auto and Omniverse would yield tens of billions in high margin licensing revenues.

Projecting the Stock Price by October 2033

In modeling out a stock price target 10 years into the future, I anchored off Nvidia’s revenue over the past 5 fiscal years. Over this period, top line has increased from $9.7 billion to $26.9 billion – reflecting a CAGR of 31%. This outpaced both the S&P 500 growth at 16% and semiconductor industry growth at 15% over this period highlighting exceptional business momentum.

Nvidia Historical Revenue Growth

Year Revenue YoY Growth
2019 $10.9B -7%
2020 $16.7B 53%
2021 $26.9B 61%
2022 $27B 0%

Source: Nvidia Annual Reports

If we apply a slightly more conservative 25% growth rate through FY33, Nvidia would generate around $175 billion in revenue by then. This factors in growth rates decaying over time from 50%+ levels today as markets mature and absolute numbers swell.

Gross margin averaged 65% over the past 5 years as well so applying the same provides a FY33 gross profit figure of $114 billion. Assume further R&D intensity in the business keeps operating margins around 39% – in line with the past 5 years.

This produces an impressive $44 billion in operating income by FY33! Now assume steady share buybacks reduce the share count by 50% by then. Applied to the projected profits discounted 7 years into the future at 10% and taxed at 18% yields a future market cap approaching $850 billion. Divide across a future share count of 500 million and we arrive at a stock price of $1,700!

For cross-checks, I also valued Nvidia using P/Eand P/S multiples.

Nvidia Valuation Methodologies

Approach Stock Price Implied Returns p.a
DCF Method $1,700 ~30%
25x P/E Multiple $1,350 ~25%
8x P/S Multiple $1,400 ~27%

As we can see, different modeling techniques yield a potential 2033 price range spanning $1,350 to $1,700 – not a wide spread. This analysis does price in execution excellence along the lines of what we’ve seen historically. It also bakes in continued leadership commercially and technologically within core and emerging competencies.

Risks like competitive pressures, economic instability affecting customer spend, supply chain disruptions, and geopolitics all stand as potential stock price headwinds not accounted for. But in a blue sky scenario, one resulting in ~25-30% annualized returns over 10 years, $1,700 doesn’t seem unrealistic at all.

Only time will tell but with AI and the metaverse unlocking countless opportunities, no company looks better positioned over the next decade than Nvidia!

Risk Factor Analysis

While the future appears bright for Nvidia given secular growth tailwinds and pole position competitively, the road ahead still presents ample risk to projected growth rates and earnings. Here we’ll analyze key risk factors that could substantially impact Nvidia‘s stock price over the next 10 years.

Competition – Rivals like AMD and Intel pour billions into R&D and cutting-edge manufacturing to vie chip leadership across AI, data center and graphics. Though their software ecosystems lag Nvidia‘s, better performing hardware could enable share gains. Maintaining the breakneck pace of innovations remains imperative.

Economic Conditions – Demand for Nvidia‘s expensive GPUs and AI platforms closely correlates with economic health and corporate/governmental budgets. A severe recession curtailing IT infrastructure investments or crypto winter drying up demand from miners would weigh heavily on financial performance.

Supply Chain – Semiconductor supply chains require alignment of an incredible number of technical disciplines and partners. Disruptions like droughts, power outages or geopolitics threaten production continuity. Stockpiling buffers helps but shortages still lower revenues.

Government Actions – As evidenced by recent export restrictions on advanced AI chips to China, governmental policies directly influence accessibility of Nvidia‘s total addressable market as well as financials. While impossible to predict, adverse changes here would prove very damaging financially.

In summary, while favorable trends support Nvidia’s ability to deliver standout growth, maintaining leadership across myriad product categories in a rapidly changing technology landscape makes for slim margins of error. Their consistent execution historically offers optimism but management must continue balancing go-to-market velocities with disciplined capital stewardship. Either way, the next decade surely won‘t be boring!