The “new king of the stock market” Nvidia (NVDA.US) is far from over! Next stop, $5 trillion market capitalization?
The Zhitong Finance App learned that Rosenblatt, a well-known investment agency on Wall Street, recently released a major research report. The core content is: based on Nvidia's CUDA-centered software business potential prosperity expectations, even if the stock price of AI chip leader NVDA.US (NVDA.US) rises by more than 210% within a year, the chip giant's stock price will continue to rise in the next 12 months. It is expected that Nvidia's stock price will be 50% higher than the current level. This is the opinion of Rosenblatt chip industry analyst Hans Mosesmann (Hans Mosesmann). In this research report, he raised the agency's target share price for Nvidia from $140 to an astonishing level of $200 per share within 12 months, ranking as Wall Street's highest target price for Nvidia.
Mosesmann reiterated Nvidia's rating as a “buy” in the research report. The analyst's latest bullish forecast also means that the total market value of Nvidia, the “new king of the global stock market,” which recently won the title of “the world's highest listed company by market capitalization” for the first time, may reach 5 trillion US dollars within 12 months. Currently, without taking into account the overnight rise in US stocks, Nvidia's total market value is as high as 3.34 trillion US dollars, surpassing the two established tech giants Apple and Microsoft, and far ahead of cloud computing giants Google and Amazon.
In late May, Nvidia, the AI chip giant named “Earth's Most Important Stock” by Goldman Sachs, announced unparalleled results that shocked global investors and shocked global investors, dispelling people's concerns about the slowdown in AI-related corporate spending. Nvidia is once again using its own efforts to comprehensively strengthen the “AI faith” of technology stock investors, thus driving US technology stocks to continue to rise recently. At the same time, it has also helped Nvidia's stock price to start a new round of crazy gains, continuously setting new all-time highs that have shocked investors.
Nvidia's total Q1 revenue increased 262% year over year to 26 billion US dollars. Total revenue hit a record high, and the year-on-year growth rate of total revenue was Nvidia's third consecutive quarter with a year-on-year growth rate of more than 200%. Driven by strong demand for H100/H200 GPUs, Nvidia's Q1 data center revenue increased 427% year over year to a record high of US$22.6 billion.
According to Rosenblatt chip industry analyst Mosman, Nvidia's market capitalization is worth the figure of 5 trillion US dollars. “We've seen Nvidia's Hopper, Blackwell, and Rubin series AI GPU architectures drive 'value market' share in one of Silicon Valley's most successful silicon chip and platform product cycles,” Mosman emphasized.
CUDA-centered software business may be Nvidia's new revenue generation engine
Looking ahead, analyst Mosman said that Nvidia's real source of strong profits is not only its AI GPU products, which focus on AI hardware infrastructure, but also Nvidia's software business, which is fully led by Nvidia's popular CUDA software and hardware collaboration platform. That is, “CUDA+AI GPU”, together form Nvidia's extremely powerful moat.
Currently, millions of software developers around the world are inseparable from Nvidia's CUDA platform. They are building and updating iterative large-scale language models and other AI applications on the basis of AI GPUs, which are indispensable for artificial intelligence training/inference systems behind generative AI such as ChatGPT, and the Nvidia CUDA platform. “The real story lies in the software's refinement of all hardware systems. We expect Nvidia's software business to grow significantly over the next 10 years in terms of the overall sales mix, and Nvidia's valuation tends to rise sharply due to the sustainability characteristics of the software business.”
If Nvidia can obtain a considerable recurring revenue scale from the software business layout centered on the CUDA platform, then the chip giant's revenue scale will be more predictable, thereby greatly reducing the risk of the company's revenue decline. Analyst Mosman emphasized in the research report that Nvidia's CUDA-centered software business may help push the company's profit scale to reach $5 per share after split adjustments in 2026.
Nvidia has always relied on sales of hardware products to accelerate revenue growth, and hardware product sales usually have obvious cyclical characteristics. Very unstable “boom and bust” periods are common for hardware products such as chips, and even Nvidia's high-performance GPUs cannot avoid cyclical attributes. Currently, Nvidia's hardware business is unquestionably in an unprecedented “boom period.”
Nvidia has been deeply involved in the field of global high-performance computing for many years. In particular, the CUDA computing platform built by itself is popular all over the world. It can be described as the preferred software and hardware collaboration system in high-performance computing fields such as AI training/inference. The CUDA computing platform is a parallel computing acceleration platform and programming aid software developed exclusively by Nvidia. It allows software developers and software engineers to use Nvidia GPUs to accelerate parallel general computing (only supports Nvidia GPUs and is not compatible with mainstream GPUs such as AMD and Intel).
CUDA can be described as a platform that is extremely dependent on the development of generative AI applications such as ChatGPT. Its importance is on par with the hardware system, and it is essential for the development and deployment of large models of artificial intelligence. With its high technical maturity, absolute performance optimization advantages, and extensive ecosystem support, CUDA has become the most commonly used and widely popular collaborative platform for AI research and commercial deployment.
According to Nvidia's official website, using Nvidia GPUs for general CUDA accelerated computing programming and some basic tools is free, but if it involves large-scale CUDA enterprise-level applications and support (such as NVIDIA AI Enterprise), or if leasing Nvidia computing power on cloud platforms (such as Amazon AWS, Google Cloud, Microsoft Azure) requires a subscription CUDA microservice to develop an AI system, additional fees may be required. In addition to the huge GPU hardware revenue brought by CUDA's firm binding to AI GPUs and the revenue generated by large-scale CUDA enterprise-level applications, the software business derived from CUDA as the core is also the engine for Nvidia CUDA to achieve huge revenue generation.
For example, based on the extremely powerful CUDA platform with extremely high penetration rate and powerful AI GPUs, Nvidia's recent software business layout can be described as continuously increasing. Previously, in March GTC, Nvidia officially launched a microservice called “NVIDIA NIM”, which is charged per GPU usage time. It is a cloud-native microservice focusing on optimization. It aims to shorten the time to market for generative AI applications based on AI models and simplify their deployment workloads in the cloud, data centers, and GPU-accelerated workstations, enabling enterprises to deploy AI applications based on Nvidia's AI GPU cloud inference computing power and acceleration based on the CUDA platform. It seeks to establish an AI application software development ecosystem with an exclusive Nvidia GPU system.
Getting started with NIM is straightforward. In the NVIDIA API catalog, enterprise developers can access a variety of big AI models that can be used to quickly build and deploy their company's AI applications on the NIM platform. Therefore, we can simply understand that “NVIDIA NIM” and Microsoft Azure OpenAI Service provide an AI developer service ecosystem with similar functions and application scenarios. They all aim to simplify application software deployment and inference workloads based on the AI big model. NIM fully utilizes the accelerated computing capabilities provided by the CUDA platform to ensure the best performance of AI models running on Nvidia GPUs. This integration made NIM part of NVIDIA's software and hardware ecosystem, and promoted the construction of an AI application software development ecosystem for Nvidia's exclusive GPU system.
From a long-term holding perspective, the “Earth's Most Important Stock” rally is probably far from over
Last month, Beth Kindig (Beth Kindig), a tech industry analyst from the well-known investment institution I/O Fund, was also very optimistic about Nvidia's software business revenue expectations centered on CUDA.
“The CUDA software platform is a collaborative platform that AI developers must use. So, the real reason that is similar to the iOS ecosystem barriers is that people are locked into iPhones because developers are developing apps for iPhones, and the same thing happened to Nvidia. In other words, the CUDA platform is content for AI engineers to learn to program GPUs, which helps lock them in. Coupled with a combination of high-performance GPUs, I now call it an insurmountable moat.” Kindy said in the report.
Notably, Nvidia's long-term market capitalization outlook given by I/O Fund analyst Jindi is more aggressive. The analyst said that by 2030, Nvidia's stock price is expected to soar more than 200% from the current level, and the market value is expected to reach 10 trillion US dollars by then (currently Nvidia's market value is about 3.34 trillion US dollars). The main logic is that Nvidia's “CUDA+AI GPU” ecosystem is extremely powerful, and that Nvidia's next generation of AI GPUs based on the BlackWell architecture are expected to bring huge revenue contributions.
Analyst Jindi predicts that by the end of Nvidia's 2026 fiscal year, the revenue from Nvidia's Blackwell architecture AI GPUs will greatly exceed its predecessor GPU-H100. At that time, the Blackwell architecture is expected to drive Nvidia to achieve data center revenue of up to 200 billion US dollars.
In the report, Jindi also predicted that by 2027, the total potential market size of the global AI data center market will reach 400 billion US dollars and reach 1 trillion US dollars by 2030, and the data center AI chip market is expected to be mainly occupied by Nvidia rather than its largest rivals AMD or Intel. “Nvidia will take the lion's share,” Kindy said. “This is largely due to the CUDA ecosystem and the powerful performance of Nvidia's AI GPUs.
In Nvidia's new Blackwell architecture AI GPU press release in March, Tesla CEO Musk publicly shouted that Nvidia's AI hardware is “the best AI hardware.” Musk also compared technology companies' artificial intelligence arms race to a high-risk “poker game,” that is, companies need to invest billions of dollars in artificial intelligence hardware every year to maintain competitiveness.
Mosesmann reiterated Nvidia's rating as a “buy” in the research report. The analyst's latest bullish forecast also means that the total market value of Nvidia, the “new king of the global stock market,” which recently won the title of “the world's highest listed company by market capitalization” for the first time, may reach 5 trillion US dollars within 12 months. Currently, without taking into account the overnight rise in US stocks, Nvidia's total market value is as high as 3.34 trillion US dollars, surpassing the two established tech giants Apple and Microsoft, and far ahead of cloud computing giants Google and Amazon.
In late May, Nvidia, the AI chip giant named “Earth's Most Important Stock” by Goldman Sachs, announced unparalleled results that shocked global investors and shocked global investors, dispelling people's concerns about the slowdown in AI-related corporate spending. Nvidia is once again using its own efforts to comprehensively strengthen the “AI faith” of technology stock investors, thus driving US technology stocks to continue to rise recently. At the same time, it has also helped Nvidia's stock price to start a new round of crazy gains, continuously setting new all-time highs that have shocked investors.
Nvidia's total Q1 revenue increased 262% year over year to 26 billion US dollars. Total revenue hit a record high, and the year-on-year growth rate of total revenue was Nvidia's third consecutive quarter with a year-on-year growth rate of more than 200%. Driven by strong demand for H100/H200 GPUs, Nvidia's Q1 data center revenue increased 427% year over year to a record high of US$22.6 billion.
According to Rosenblatt chip industry analyst Mosman, Nvidia's market capitalization is worth the figure of 5 trillion US dollars. “We've seen Nvidia's Hopper, Blackwell, and Rubin series AI GPU architectures drive 'value market' share in one of Silicon Valley's most successful silicon chip and platform product cycles,” Mosman emphasized.
CUDA-centered software business may be Nvidia's new revenue generation engine
Looking ahead, analyst Mosman said that Nvidia's real source of strong profits is not only its AI GPU products, which focus on AI hardware infrastructure, but also Nvidia's software business, which is fully led by Nvidia's popular CUDA software and hardware collaboration platform. That is, “CUDA+AI GPU”, together form Nvidia's extremely powerful moat.
Currently, millions of software developers around the world are inseparable from Nvidia's CUDA platform. They are building and updating iterative large-scale language models and other AI applications on the basis of AI GPUs, which are indispensable for artificial intelligence training/inference systems behind generative AI such as ChatGPT, and the Nvidia CUDA platform. “The real story lies in the software's refinement of all hardware systems. We expect Nvidia's software business to grow significantly over the next 10 years in terms of the overall sales mix, and Nvidia's valuation tends to rise sharply due to the sustainability characteristics of the software business.”
If Nvidia can obtain a considerable recurring revenue scale from the software business layout centered on the CUDA platform, then the chip giant's revenue scale will be more predictable, thereby greatly reducing the risk of the company's revenue decline. Analyst Mosman emphasized in the research report that Nvidia's CUDA-centered software business may help push the company's profit scale to reach $5 per share after split adjustments in 2026.
Nvidia has always relied on sales of hardware products to accelerate revenue growth, and hardware product sales usually have obvious cyclical characteristics. Very unstable “boom and bust” periods are common for hardware products such as chips, and even Nvidia's high-performance GPUs cannot avoid cyclical attributes. Currently, Nvidia's hardware business is unquestionably in an unprecedented “boom period.”
Nvidia has been deeply involved in the field of global high-performance computing for many years. In particular, the CUDA computing platform built by itself is popular all over the world. It can be described as the preferred software and hardware collaboration system in high-performance computing fields such as AI training/inference. The CUDA computing platform is a parallel computing acceleration platform and programming aid software developed exclusively by Nvidia. It allows software developers and software engineers to use Nvidia GPUs to accelerate parallel general computing (only supports Nvidia GPUs and is not compatible with mainstream GPUs such as AMD and Intel).
CUDA can be described as a platform that is extremely dependent on the development of generative AI applications such as ChatGPT. Its importance is on par with the hardware system, and it is essential for the development and deployment of large models of artificial intelligence. With its high technical maturity, absolute performance optimization advantages, and extensive ecosystem support, CUDA has become the most commonly used and widely popular collaborative platform for AI research and commercial deployment.
According to Nvidia's official website, using Nvidia GPUs for general CUDA accelerated computing programming and some basic tools is free, but if it involves large-scale CUDA enterprise-level applications and support (such as NVIDIA AI Enterprise), or if leasing Nvidia computing power on cloud platforms (such as Amazon AWS, Google Cloud, Microsoft Azure) requires a subscription CUDA microservice to develop an AI system, additional fees may be required. In addition to the huge GPU hardware revenue brought by CUDA's firm binding to AI GPUs and the revenue generated by large-scale CUDA enterprise-level applications, the software business derived from CUDA as the core is also the engine for Nvidia CUDA to achieve huge revenue generation.
For example, based on the extremely powerful CUDA platform with extremely high penetration rate and powerful AI GPUs, Nvidia's recent software business layout can be described as continuously increasing. Previously, in March GTC, Nvidia officially launched a microservice called “NVIDIA NIM”, which is charged per GPU usage time. It is a cloud-native microservice focusing on optimization. It aims to shorten the time to market for generative AI applications based on AI models and simplify their deployment workloads in the cloud, data centers, and GPU-accelerated workstations, enabling enterprises to deploy AI applications based on Nvidia's AI GPU cloud inference computing power and acceleration based on the CUDA platform. It seeks to establish an AI application software development ecosystem with an exclusive Nvidia GPU system.
Getting started with NIM is straightforward. In the NVIDIA API catalog, enterprise developers can access a variety of big AI models that can be used to quickly build and deploy their company's AI applications on the NIM platform. Therefore, we can simply understand that “NVIDIA NIM” and Microsoft Azure OpenAI Service provide an AI developer service ecosystem with similar functions and application scenarios. They all aim to simplify application software deployment and inference workloads based on the AI big model. NIM fully utilizes the accelerated computing capabilities provided by the CUDA platform to ensure the best performance of AI models running on Nvidia GPUs. This integration made NIM part of NVIDIA's software and hardware ecosystem, and promoted the construction of an AI application software development ecosystem for Nvidia's exclusive GPU system.
From a long-term holding perspective, the “Earth's Most Important Stock” rally is probably far from over
Last month, Beth Kindig (Beth Kindig), a tech industry analyst from the well-known investment institution I/O Fund, was also very optimistic about Nvidia's software business revenue expectations centered on CUDA.
“The CUDA software platform is a collaborative platform that AI developers must use. So, the real reason that is similar to the iOS ecosystem barriers is that people are locked into iPhones because developers are developing apps for iPhones, and the same thing happened to Nvidia. In other words, the CUDA platform is content for AI engineers to learn to program GPUs, which helps lock them in. Coupled with a combination of high-performance GPUs, I now call it an insurmountable moat.” Kindy said in the report.
Notably, Nvidia's long-term market capitalization outlook given by I/O Fund analyst Jindi is more aggressive. The analyst said that by 2030, Nvidia's stock price is expected to soar more than 200% from the current level, and the market value is expected to reach 10 trillion US dollars by then (currently Nvidia's market value is about 3.34 trillion US dollars). The main logic is that Nvidia's “CUDA+AI GPU” ecosystem is extremely powerful, and that Nvidia's next generation of AI GPUs based on the BlackWell architecture are expected to bring huge revenue contributions.
Analyst Jindi predicts that by the end of Nvidia's 2026 fiscal year, the revenue from Nvidia's Blackwell architecture AI GPUs will greatly exceed its predecessor GPU-H100. At that time, the Blackwell architecture is expected to drive Nvidia to achieve data center revenue of up to 200 billion US dollars.
In the report, Jindi also predicted that by 2027, the total potential market size of the global AI data center market will reach 400 billion US dollars and reach 1 trillion US dollars by 2030, and the data center AI chip market is expected to be mainly occupied by Nvidia rather than its largest rivals AMD or Intel. “Nvidia will take the lion's share,” Kindy said. “This is largely due to the CUDA ecosystem and the powerful performance of Nvidia's AI GPUs.
In Nvidia's new Blackwell architecture AI GPU press release in March, Tesla CEO Musk publicly shouted that Nvidia's AI hardware is “the best AI hardware.” Musk also compared technology companies' artificial intelligence arms race to a high-risk “poker game,” that is, companies need to invest billions of dollars in artificial intelligence hardware every year to maintain competitiveness.
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