Table of Contents
The rapid development of generative AI applications such as language models and image generators is leading to an exponential increase in demand for specialized chips and computing power. It is precisely in this segment that none other than NVIDIA (ISIN: US67066G1040) is the leader. The California-based hardware company has even become a key driver of the global AI revolution in recent years. Strong quarterly figures and promising future prospects reflect significant growth potential – and there seems to be no end in sight. The stock price has risen accordingly. Over ten years, it has gained 35,836 percent. Over 20 years, it has more than doubled.
Source: NVIDIA stock price
However, geopolitical developments and intense competition pose challenges that need to be monitored. In the context of a high valuation, this could create a toxic mix. The following NVIDIA stock analysis will examine whether the stock offers opportunities or could be too risky.
Although NVIDIA has been around since 1993, it is only in the last ten years that its momentum has really taken off. Originally, the business model was based on the development and marketing of high-performance graphics processing units (GPUs) for the gaming industry – a niche in which the company was able to grow well and build deep moats to keep the competition at bay. However, as technology has advanced, the areas of application for NVIDIA chips have expanded significantly. Today, NVIDIA is no longer just a manufacturer of graphics cards, but a key player in the fields of artificial intelligence (AI), high-performance computing (HPC), and autonomous driving. The Californian company is also relevant for Bitcoin mining, although this topic has recently taken a back seat. The company divides its business into four core segments:
The data center segment is currently the most important growth driver for NVIDIA. The focus is on graphics processors and system solutions for data center applications. In the last quarter, this segment grew by 73 percent year-over-year to $39.1 billion, accounting for nearly 89 percent of total revenue. NVIDIA's data center technologies are particularly in demand in the field of artificial intelligence, especially for training and executing large language models and generative AI. NVIDIA not only supplies individual GPUs such as the H100 or A100, but also complete platforms such as the DGX systems, which can be used as AI supercomputers. In addition, the integration of high-speed networks such as InfiniBand, acquired through the takeover of Mellanox, plays an important role. By developing its own CPUs such as Grace and hybrid chips such as the Grace Hopper superchip, NVIDIA is increasingly positioning itself as a provider of complete data center infrastructures.
For many years, the gaming segment was the foundation of NVIDIA's success. Today, it is significantly less important, accounting for 8.6 percent of revenue. In the last quarter, however, the division continued to grow at a high level, up 42 percent compared to the same quarter last year. The focus here is on powerful graphics processors for desktop and laptop PCs, which are particularly popular with PC gamers. The GeForce RTX series with ray tracing and AI-based features (such as DLSS – Deep Learning Super Sampling) sets the standard in real-time graphics. At the same time, business with so-called “AI PCs,” i.e., computers equipped with dedicated AI accelerators, is growing. These enable users to run AI applications locally on the device – a trend that will enable NVIDIA to serve the mass market for AI end devices.
Growth in the third-largest segment, “Automotive and Robotics,” was also strong. Compared to the previous year, revenue here rose by 72 percent. However, its share of revenue is only 1.3 percent. The segment focuses on technologies for autonomous driving, advanced driver assistance systems (ADAS), and robotics solutions. With the NVIDIA DRIVE platform, the chip manufacturer even offers a modular solution for vehicle manufacturers that includes both hardware (such as DRIVE AGX boards) and software for data processing and AI models. The platform is also used in the simulation and validation of autonomous driving systems. In robotics, NVIDIA also provides AI-enabled edge computing solutions with Jetson modules for use in industry, logistics, and medicine. In the long term, NVIDIA aims to become a central operating system for autonomous machines.
The Professional Visualization segment accounts for 1.2 percent of revenue. This division serves companies and creative professionals who rely on high-precision graphics and simulation applications. That may sound boring, but the recent growth of 19 percent is solid. Applications include 3D rendering (image synthesis), visual effects, virtual reality, architectural visualization, and digital twins. RTX workstation GPUs and the NVIDIA Omniverse platform enable collaborative work in virtual 3D worlds. They also provide a powerful environment for developing and simulating industrial applications. The goal is to digitally replicate physical processes in order to make design, development, and production more efficient.
What makes NVIDIA special is that the company is much more than a traditional chip manufacturer: over the years, it has developed into a key technology provider for the AI era – arguably the most important era of the last twenty years. NVIDIA is a global leader in the development of graphics processors, which are now used not only for gaming, but primarily for artificial intelligence, research, and high-performance computing. With GPUs such as the H100 and software solutions such as CUDA, NVIDIA has created an infrastructure on which a large proportion of modern AI models, including large language models, are trained. Unlike many of its competitors, NVIDIA not only offers powerful hardware, but also combines it with an extensive software ecosystem, which can represent a huge hurdle for the competition. A good example of this is the company's proprietary CUDA platform, which is now the industry standard for GPU-accelerated computing. In addition, there are special frameworks for deep learning (e.g., TensorRT, Triton), simulation (Omniverse), and robotics (Isaac), which strongly bind developers and companies to NVIDIA. It is also interesting to note that the broad and integrated product portfolio creates strong network effects. Developers who specialize in CUDA tend to remain in the NVIDIA ecosystem. Companies that have implemented NVIDIA systems benefit from seamless scaling. This creates a technological and economic lock-in effect.
These developments show that NVIDIA is not just a supplier of AI infrastructure, but also a catalyst for the AI revolution. Today, the most powerful data centers for generative AI are essentially based on NVIDIA hardware. Companies such as OpenAI, Meta Platforms, Alphabet and Microsoft prefer NVIDIA technology when designing their AI infrastructures, as no other manufacturer offers similar performance. This allows NVIDIA to benefit directly from growth in the areas of cloud computing, generative AI, autonomous vehicles and digital twins. NVIDIA is also active in vertical markets, for example with the DRIVE platform in the automotive sector and with Omniverse in industry. NVIDIA is therefore not only a supplier of chips, but also a provider of complete solutions – from hardware to software integration. It is precisely this platform approach that creates barriers to entry for competitors and ensures high prices and long-term customer loyalty. Another special feature is that NVIDIA is increasingly able to establish its own pricing models thanks to its market position.
NVIDIA's competitive advantage is considered exceptionally high – between three and five years, and in some areas even up to ten years – depending on the market segment and perspective. It could be particularly high in the software ecosystem (CUDA, frameworks), as this is deeply integrated into countless AI and HPC applications. The data center GPU segment, where NVIDIA has a market share of 80 to 90 percent, is also considered unassailable. The lead here is estimated at four to five years, thanks to the combination of powerful hardware (e.g., H100, Grace Hopper), software (CUDA, TensorRT), and complete system solutions.
The larger competitors vary depending on the market segment, but currently no company covers all areas as comprehensively as NVIDIA does. However, AMD could be the closest, especially in the gaming GPU segment. With its Radeon graphics card series, AMD is competing directly with NVIDIA's GeForce products. In the data center sector, AMD is also developing powerful GPUs for AI training and high-performance computing with its Instinct series (e.g., MI300X). AMD is also growing in the server market thanks to its powerful CPUs (EPYC) and is increasingly combining CPUs and GPUs in its own system solutions. Although AMD lags significantly behind NVIDIA in software integration, the company is catching up technologically.
The big tech companies are also increasingly upgrading their hardware. They see too much dependence on NVIDIA. One example is Alphabet. Although Google's parent company is not a traditional hardware vendor, its Tensor Processing Units (TPUs) are in direct competition with NVIDIA in the field of AI acceleration. The TPUs are mainly used in Google's own data centers and cloud services (Google Cloud AI). Google is developing both specialized hardware and its own software frameworks (such as TensorFlow) to accelerate the training and execution of AI models. Even though Google uses its TPUs primarily internally, the company's innovative strength puts considerable pressure on NVIDIA, especially in the cloud business. It should also be noted that the company recently achieved a breakthrough in quantum computing technology with Willow.
Amazon is also experimenting with its own chips. Inferentia for inference and Trainium for AI training are indirect but strategically relevant competitors to NVIDIA. They are specifically designed for use in Amazon Web Services. Although Amazon does not yet sell the chips separately, building its own hardware infrastructure is a clear attempt to break away from its dependence on NVIDIA.
However, other major platform providers such as Microsoft and Meta Platforms are now developing their own AI chips to run their cloud and AI applications more efficiently. Both companies are also major buyers of NVIDIA GPUs, but are working to become more independent in the long term with their own processors (e.g., Microsoft's Maia and Cobalt chips). These in-house developments have not yet reached the performance levels of NVIDIA hardware, but they show that even the largest customers are also potential competitors.
Intel, the current market leader in the CPU sector, appears to be lagging behind in the race. However, with its Arc graphics cards for consumers and data center GPUs such as “Ponte Vecchio,” Intel is attempting to establish itself as an alternative to NVIDIA. Of particular relevance is the development of the Gaudi accelerators, which are being developed by its subsidiary Habana Labs. They are designed for AI training and inference. Although Intel is still a few years behind NVIDIA, its vast financial resources and market position could enable it to make a comeback in the future.
Source: Market Cap Comparison
The trend clearly shows that Nvidia is emerging as the clear winner. With a value of US$4 trillion, the company is even the most valuable in the world. Only AMD can keep pace as a hardware manufacturer. However, its market capitalization of a quarter of a trillion US dollars is miles away from where NVIDIA already stands today.
NVIDIA achieved a new record in the first quarter of fiscal year 2026 with revenue of US$44.1 billion, exceeding analysts' and investors' expectations. Revenue rose by 12 percent compared to the previous quarter and by as much as 69 percent compared to the same period last year.
Source: Financial Data NVIDIA
This once again underscores the high demand for NVIDIA's AI infrastructure and data center solutions, although geopolitical developments had a noticeable impact on earnings. On April 9, 2025, the US government informed NVIDIA that a special license would be required for the export of the new H20 chips to China in the future. As a result of these new requirements, the company had to record a one-time charge of US$4.5 billion, which was caused by excess inventory and contractual obligations.
Even before the export restrictions came into effect, NVIDIA was able to generate revenue of US$4.6 billion with H20 products. However, an additional US$2.5 billion could not be delivered during the quarter. Despite these one-time effects, profitability remained at a high level. The GAAP gross margin was 61 percent. Without the impact from the China business, the adjusted gross margin would have reached 71.3 percent, the company said.
Net income at the end of the first quarter was US$18.8 billion, up about a quarter from a year earlier. CEO Jensen Huang remained optimistic despite the challenges. He pointed to the new Blackwell NVL72 AI supercomputer, which is now being produced on a large scale by system manufacturers and cloud providers.
The system is specially designed for complex AI applications and reasoning. But there is some positive news: Since July 2025, NVIDIA has been allowed to export its H20 AI chips, which were developed specifically for the Chinese market, to China again, which should bring some relief to the company.
For the second quarter of fiscal year 2026, NVIDIA expects revenue of around US$45 billion, with a margin of plus or minus 2 percent. The forecast already takes into account an expected revenue loss of approximately US$8 billion related to export restrictions on H20 chips to China. Due to the lifting of these restrictions in mid-July, this figure could therefore be several billion higher. Despite these growth difficulties, NVIDIA's management tends to expect good business. The forecast alone shows that global demand for NVIDIA technology remains high in other regions. By way of comparison, without the export restrictions, revenue would have increased by over 20 percent compared to the previous quarter. Compared to the same quarter last year, we are talking about growth of 78 percent, which is a lot on this revenue basis.
The gross margin also looks good. It is expected to be 71.8 percent under GAAP and 72 percent under non-GAAP, each with a possible deviation of 50 basis points. NVIDIA plans to further increase this margin during the fiscal year to the mid-70 percent range. This would confirm the company's position as one of the most profitable semiconductor manufacturers in the world.
For the full year, however, NVIDIA expects operating costs to increase in the mid-30 percent range. In my opinion, this is an indication of increasing investment in research, development, and infrastructure, particularly in the context of new products such as the Blackwell platform. This is NVIDIA's latest and most powerful AI architecture and was developed as the successor to the Hopper generation specifically for training and inferencing extremely large AI models. The Blackwell platform features new chips such as the B100 GPU and the Grace Blackwell superchip (GB200), as well as highly integrated systems such as the NVL72 supercomputer. Together, these form a fully scalable infrastructure for next-generation data centers and AI applications.
Source: Sales and Margin forecast
Analysts are also optimistic. In terms of sales growth, double-digit growth rates could still be achieved in the coming years, although the pace is likely to slow down due to the sheer size of the market. However, sales of almost US$450 billion could be achieved by 2033. The result could then be around US$250 billion. However, the margin would no longer increase significantly and would level off below the 60 percent mark. For 2026, analysts initially expect sales growth of 56 percent to US$204 billion with a net profit of US$129 billion.
The HGI score for NVIDIA shows that the company is currently very well positioned in terms of several key growth and quality criteria, although the rating remains ambitious.
Source: HGI Score
With revenue growth of 86 percent based on the last twelve months and even over 100 percent in fiscal years 2024 and 2025, NVIDIA is well above what is typical for traditional tech stocks. The chip manufacturer is also growing extremely profitably.
The Rule of 40 score, which combines revenue growth and profitability, is extremely high at 135 percent. Another positive highlight is the very low debt ratio of 0.1. The PEG ratio is also at an attractive level of 0.7.
This suggests that expected earnings growth could support the stock price despite the high valuation. However, more on this later in the valuation section. All four points received the full three points. Due to the strategy criteria, only two points were awarded for the gross margin of over 70 percent.
The full score would only have been awarded from 75 percent. However, it underlines the efficiency of the business model and stands for high operational leverage, especially since we are talking about a hardware manufacturer and not a software company. However, significantly higher percentages are unlikely to be possible in the near future, as the business will continue to be heavily hardware-oriented.
The biggest weakness in the HGI analysis is the current valuation based on sales: With an EV/sales multiple of 28, NVIDIA is highly valued even for a highly profitable growth company. The HGI model therefore awards 0 out of 3 points here.
With a P/E ratio of 55, NVIDIA stock do not appear cheap at first glance. However, this valuation is justified by the company's strong growth. This can be seen from the dynamic PEG ratio alone. At 0.7, it is well below one. But this can also be seen in the long-term development of the P/E ratio. The expected P/E ratio is currently only 38. If the growth momentum continues, it could even fall to 16 by 2033.
Source: EPS & P/E ratio
A look at free cash flow shows that it tends to keep pace with earnings. Based on the last twelve months, it most recently stood at over US$72 billion. However, measured by the average multiplier, EV/FCF is currently higher than the historical average of 39.5.
Source: Development of free cash flow, net income, and EV/FCF
Nvidia stock is therefore trading with a large dose of future fantasy. It will take years for the company to grow into its current valuation. However, the likelihood that growth will remain high is high, as demand for AI infrastructure, computing power, and specialized chips is growing rapidly and is not a short-term trend, but part of a profound technological revolution. Nvidia is benefiting not only as a hardware supplier, but also as a platform provider that intelligently connects hardware, software, and ecosystems. As long as this structural tailwind continues and Nvidia maintains its technological leadership, an ambitious valuation appears fundamentally justified – albeit with corresponding risk.
On the one hand, geopolitical tensions such as the recent export restrictions on China could restrict access to important markets and customers, thereby slowing sales, profits, and growth. On the other hand, competition in the semiconductor and AI industries is intense. Large corporations such as AMD and Intel, as well as cloud providers such as Google, have been developing their own solutions for some time, which could cost NVIDIA market share. In addition, a large part of the valuation is based on the assumption that NVIDIA will be able to maintain its technological leadership in the long term. However, this assumption could be jeopardized by technological breakthroughs from competitors.
NVIDIA symbolizes the technological change that artificial intelligence is triggering in almost all areas of life and the economy. With its leading role in AI infrastructure, its strong product portfolio, and its deeply integrated ecosystem, the company has established a strategic position that few other competitors can match in terms of breadth and depth. The current financial results impressively demonstrate the strong demand for NVIDIA's solutions. Despite geopolitical hurdles, the company is growing at an exceptional pace for the tech industry.
However, the stock's valuation is ambitious, and much of its current market value is based on high expectations for the future. To meet these expectations, NVIDIA must not only maintain its technological leadership, but also remain innovative while keeping an eye on global risks such as political tensions and increasing competition. However, NVIDIA cannot necessarily control the political environment itself. However, it can develop a diversification strategy that protects it from becoming too dependent on individual customers and regions. For investors, this means above all that investing in NVIDIA is a bet on the long-term momentum of artificial intelligence – with all the opportunities, but also the typical risks of a company leading a disruptive development.
Source: NVIDIA target price
A final look at analysts' opinions on the stock shows that an overwhelming majority of 89 percent recommend buying the chip manufacturer's stock. There are hardly any sell recommendations. The average price target is US$183.60, around six percent above the current price. This means that the stock may have almost exhausted its potential for the time being.
The author and/or persons or companies associated with StocksGuide own or may own shares of NVIDIA. This article represents an expression of opinion and does not constitute investment advice. Please note the legal information.