Is Nvidia Still a Buy in 2026? Can NVDA Reach a $10 Trillion Valuation by 2030? 

Nvidia is at the center of the AI value chain as nearly all AI software will run on chips, and Nvidia designs the most important chips. According to William Blair analysts, Nvidia has an estimated 85–90% share of the AI chip market.

Nvidia's data center revenue in the last quarter of $51.2 billion dwarfs the total of $9.5 billion in AI revenue combined for AMD (AMD) and Broadcom (AVGO). Nvidia has guided its revenue expectations for the current quarter to $65 billion, which represents a 65% increase year-over-year, continuing the momentum from its prior guidance of a 62% increase for the prior quarter. In contrast, AMD's data center revenue growth was only 22% in the prior quarter, while Broadcom's AI revenues increased 63% year-over-year to $5.2 billion; however, Nvidia's overall revenue growth and absolute size were still greater.

While Amazon (AMZN), Google (GOOG) (GOOGL), and Microsoft (MSFT) are all investing in custom chips for their own operations, Nvidia's GPUs continue to be the best all-around general-purpose computing units available; as Jensen Huang recently pointed out, the company is currently "sold out" of cloud GPUs, indicating that even with increasing levels of competition, Nvidia continues to hold onto its position as the industry standard.

Nvidia has notified its Chinese clients that it intends to begin delivery of its H200 processors prior to mid-February Lunar New Year, according to a report from Reuters. Initially, Nvidia plans to deliver 40,000 - 80,000 H200 processors from its current supply of H200 inventory. Since each H200 processor has an approximate selling price of $32,000, Nvidia could potentially earn anywhere from $1.28B - 2.56B in revenue from H200 sales in the China market during FY2027, which starts in January 2026.

Nvidia's agreement with the Trump administration requires it to pay 25 percent of its Chinese revenue to the U.S. government, but it represents a beginning for Nvidia, which had its access to this particular segment of the marketplace completely taken away in April 2025 due to restrictions on Chinese companies regarding sales of their advanced AI chips.

Most importantly, the third source mentioned in the Reuters article provides evidence that Nvidia plans to increase its production capacity to meet customer demand from China. The company anticipates beginning to accept orders for the newly added capacity in Q2 of 2026, demonstrating Nvidia's confidence in the market for its H200 processors in China. This should be no surprise given the fact that the H200 offers approximately six times the performance of the current H20 processor that has been sold to China. Consequently, Chinese technology companies such as Alibaba, ByteDance, and Tencent continue to express great interest in purchasing these chips.

It is also possible that Chinese government officials could require companies to buy homegrown chips in addition to the H200, in order to stimulate the development of local technology. As a result, the overall reduction of barriers/increased ease for Nvidia to sell its advanced chips into China may be accelerated as a result of this requirement, given that Nvidia was expected to sell approximately $30 billion of AI chips there prior to the introduction of the restrictions set by the government of China.

According to IDC, AI's contribution to the global economic output will grow from almost zero to 19.9 trillion by 2030 or approximately 3.5% of total global output if AI continues to be adopted at a similar rate as in the past. For every dollar spent on AI in the business sector today, an indirect and induced effect will produce $4.60 of added value to the world economy. The greatest example of this effect can be found in Palantir Technologies' AIP, which has become an invaluable asset for companies trying to implement generative AI within their operational data and processes.

The implementation of Palantir's (PLTR) AIP provides an immediate return on investment for its customers. Every Palantir AIP customer that has implemented AIP throughout its organization has experienced increased productivity through increased efficiency and eliminated redundancies. Companies like Meta Platforms and Amazon also benefited from AI. Meta successfully implemented AI technology to improve the returns on their advertisers and Amazon reduced costs to consumers by reducing delivery times through their AIs.

The recent lame-duck recession has given a huge boost to thousands of small business owners, who are now enjoying the benefits of AI. According to a survey conducted by Goldman Sachs, nearly 100% of small business owners surveyed have reported positive outcomes from their use of AI, with 85% of respondents claiming their productivity has improved, and 81% stating that AI is augmenting their employee base.

The next stage of expansion is in the product pipeline and the order book. Investor attention has focused on the Hopper and Blackwell architectures, but we should also keep an eye on Rubin's guidance as demand signals are developing. Jensen Huang stated recently that the company has $500 billion of orders, which includes Blackwell, Rubin, and related networking products, with $300 billion expected to be recognized in 2026. Anthropic just signed a $30 billion compute capacity agreement with Microsoft that will be fulfilled using clusters of Blackwell and Rubin chips. On a broader scale, Goldman Sachs predicts that the largest cloud computing companies—Microsoft, Alphabet, Amazon, and Meta Platforms—will invest approximately $500 billion in AI capital expenditures in 2026, and McKinsey estimates that the infrastructure for AI will generate a $7 trillion opportunity over the next five years. This long-term trend will not only enhance Nvidia's existing data center business but also enable the company to participate in adjacent markets such as next-generation CPUs and accelerated computing operating systems through strategic alliances with companies like Intel and Palantir Technologies.

Nvidia continues to post incredible growth even though they had a very strong base of financials. Fiscal 2026 (ending January 31, 2026) will see Nvidia reach $213 billion in revenue at an increase of 63% over the prior year. Consensus estimates project that the company will experience 57% growth in earnings this fiscal year equating to $4.69 per share.

Analysts anticipate Nvidia will maintain this momentum into fiscal 2027 with expectations to see a 48% increase in revenues to $316 billion compared to fiscal 2026 as well as an increase of slightly more than 59% in earnings per share ($7.46). Recently raised estimates for Nvidia's 2026 earnings support the analysts' projections.

Nvidia provided guidance for the current quarter that suggests a 65% increase in year-over-year sales, demonstrating continued momentum moving into the new year, combined with a substantial backlog.

The company has a large order book of $500 billion for AI chips in 2025 and 2026. This is good for Nvidia as it indicates a better outlook than what analysts had prior estimated. With $167 billion generated from data center revenue last year and likely $58 billion this quarter (approximately 90% of total sales attributed to data centers), Nvidia has a potential data center backlog of $275 billion for the upcoming year based on an estimated $225 billion in shipments over the previous five quarters.

Management emphasizes that there is no definitive cap on the backlog. As stated by CFO Colette Kress, “it is an expandable backlog over time” and “there is an opportunity for us to exceed our $500 billion announced backlog.” Another way for growth beyond 2026 comes through the Trump administration’s approval of H200 data center GPUs being sold to China.

Everyone has to strike a balance between potential gain and probability of loss when deciding how to value Nvidia stock. The market based on one view is apprehensive about the company's ability to maintain the current margins on its artificial intelligence products and assigns Nvidia a P/E ratio of 23 times its projected earnings over the next 12 months. However, the market is optimistic enough to give Nvidia a P/E ratio of 36 times based on another view that reflects the robust competitive advantages Nvidia has built up over many years.

The risks associated with Nvidia are significant, including both large language model customers losing money and the continued use of custom silicon by hyperscalers, potential backlash from shareholders regarding future capex increases, and the continued high concentration of Nvidia's business within data centers.

However, the upside is equally significant, including marketplace leadership in graphics processing units (GPUs) and the software stack required to develop AI applications, high demand levels for cloud computing graphics processing unit services even at fairly high quarterly run-rates, the recently announced reopening of the Chinese market to Nvidia through shipment of their new H200 cards, anticipated future revenues in the billions from H200 shipments due to demand in the Chinese market, substantial backlogs of unshipped products (275 billion) based on 2026 demand estimates that are likely to increase, earnings forecasts of $7.52 per share from analysts for 2026 based on expected revenue increases from China, as well as several emerging technologies that could fundamentally re-invent the way we view cars, robots, computers, etc.

Through the projections of increasing AI capex from $600 billion in 2025 to between $3 trillion and $4 trillion by 2030, one can see the position of Nvidia as a toll collector for the expansion of AI, which is why the stock price has the potential to compound into a $10 trillion market cap by 2030.

For investors looking at NVDA and AI stocks, here is the thesis: continue to maintain dominance in areas where it is currently entrenched, scale the ability to satisfy the ever-increasing demand for capacity, and incrementally diversify into adjacent computing markets while continuing to have options open for future reinventions, which is how Nvidia has operated for the last 30 years and is how it could achieve a $10 trillion valuation.