As the demand for AI computing power continues to explode, NVIDIA CEO Jensen Huang has provided a judgment that far exceeds market expectations, believing that the company's advanced chip revenue exceeding $1 trillion is very likely to be achieved, and hinted that as the company enters new markets, overall revenue will surpass this level.
On Tuesday, the 17th, Eastern Time, during NVIDIA's annual developer conference GTC, Huang stated that the revenue expectation of over $1 trillion announced on Monday has strong &#34;visibility.&#34; NVIDIA expects to achieve, record, and deliver business worth over $1 trillion, and holds &#34;firm confidence&#34; in reaching the &#34;over $1 trillion&#34; goal.
Huang pointed out that this expectation only includes revenue from the two core architecture product lines, Blackwell and Rubin, and does not include upcoming new products or new regions and markets. This means that NVIDIA's potential overall AI business scale may further exceed the current estimates.
Huang stated that the $1 trillion goal will continue to expand. Quarterly expectations can exceed market expectations. Customers want to ensure they have sufficient supply.
On Monday, the opening day of GTC, Huang revealed that by the end of 2027, NVIDIA's next-generation AI acceleration chip architecture Blackwell and the next-generation Rubin products are expected to cumulatively create at least $1 trillion in revenue. This figure is double the $500 billion forecast Huang mentioned four months ago.
At the GTC conference at the end of October last year, Huang said that NVIDIA has &#34;visibility&#34; to achieve a cumulative $500 billion in data center business revenue from 2025 to 2026, which includes Blackwell and Rubin architecture products.
Huang's recent statements regarding the $1 trillion revenue expectation not only reinforce market confidence in the long-term prosperity of AI infrastructure but also further highlight NVIDIA's core position in the global computing power competition. The doubling of NVIDIA's chip revenue expectation from $500 billion to $1 trillion is driven by the steep upward demand curve for AI.
On Monday, after revealing the expectation of at least $1 trillion in revenue, Huang said: &#34;In fact, we will even be in short supply. I am sure that the actual computing demand will be much higher.&#34; He pointed out that today's NVIDIA systems have proven to be the &#34;lowest cost infrastructure&#34; globally. Because NVIDIA can run AI models across almost all fields, this versatility allows the $1 trillion invested by customers to be fully utilized and maintained over a long lifecycle.
<h2>Three Major Supports for the &#34;Trillion Dollar Revenue&#34; Expectation</h2>
Analysts believe that there are three major supports behind Huang's &#34;trillion dollar revenue&#34; expectation.
<ul>
<li>High Order Visibility, Supply Shortage Remains the Main Line</li>
</ul>
Huang emphasized that the core demand of customers at present is to &#34;ensure sufficient supply,&#34; rather than price. This reflects that the AI computing power market is still in a typical supply bottleneck stage
He further pointed out that large-scale purchases from cloud vendors and AI companies have created a high level of certainty in the company's orders, bookings, and shipments, which is also a key reason for its confidence in providing a &#34;strong visibility&#34; judgment.
From an industry perspective, tech giants including OpenAI, Meta, and Microsoft are continuously ramping up AI data center construction, driving exponential growth in computing power demand.
<ul>
<li>AI enters the &#34;Inference Era,&#34; demand curve rises again</li>
</ul>
Unlike the past two years, which focused on &#34;model training,&#34; Jensen Huang repeatedly emphasized at the conference that the AI industry has entered an &#34;inference inflection point.&#34;
Inference refers to the real-time computing demands of AI models in practical applications, corresponding to user scale expansion and commercialization, with computing power demand far exceeding that of the training phase.
NVIDIA expects this trend to become the core driving force behind a trillion-dollar market, leading to comprehensive growth in chips, CPUs, and the entire AI system.
<ul>
<li>Product iteration + platformization, extending the growth cycle</li>
</ul>
The anticipated scale of $1 trillion only covers the Blackwell and next-generation Rubin architecture chips, with Rubin expected to begin large-scale deployment in 2026.
At the same time, NVIDIA is also advancing the more long-term Feynman architecture and strengthening its CPU, networking, and software ecosystem, attempting to shift from &#34;selling chips&#34; to &#34;selling AI factories.&#34;
Analysts point out that this platformization strategy means NVIDIA's future revenue will no longer be limited to a single GPU but will expand to a complete data center system, significantly amplifying the revenue ceiling.
<h2>Market Reaction: Expectations are high, but the logic is stronger</h2>
Although the &#34;$1 trillion&#34; revenue target is highly impactful, the capital market's reaction has been relatively restrained.
On Monday, after Jensen Huang announced at least $1 trillion in revenue, NVIDIA's stock price initially hit a daily high, with an intraday increase of about 4.8%, but quickly retraced more than half of the gains, ultimately closing up 1.65%. On Tuesday, the stock opened high but fell, initially rising nearly 1.2% before turning to a decline, closing down about 0.7%.
Some analysts believe that NVIDIA had already risen significantly before, and the market had adequately priced in high growth.
However, most institutions still believe that this forecast reinforces a core logic: the construction of AI infrastructure is still in its early stages, and demand has not peaked; rather, it is accelerating from training to broader application deployment.
As analysts have stated, what Jensen Huang describes is not just growth in chip sales but the emergence of an &#34;AI industrial era.&#34;
Commentators believe that Huang's latest statements send a clear signal: the AI computing power race is far from over and has just entered a larger-scale commercialization phase.
For NVIDIA, this not only means a renewed opening of performance growth space but also signifies its gradual evolution from a chip company to an infrastructure provider in the AI era

GTC 大会引爆 AI 叙事，算力、推理、智能体成焦点，产业链预期升温，资金聚焦硬件与应用落地主线。

GTC 大会引爆 AI 叙事，算力、推理、智能体成焦点，产业链预期升温，资金聚焦硬件与应用落地主线。

Did the GTC conference fuel the rise of AI narratives

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Jensen Huang stated that the expectation of over $1 trillion only includes the revenue from the two core architecture product lines, Blackwell and Rubin, and does not account for upcoming new products or additional regions and markets

- Nvidia CEO Jensen Huang predicts that the company's advanced chip revenue could exceed $1 trillion, driven by high demand for AI infrastructure.  
- This expectation, supported by significant orders and the shift from model training to real-time AI applications, highlights Nvidia's central role in the AI market.  
- Analysts suggest this places Nvidia on the path from a chip manufacturer to a comprehensive AI infrastructure provider, signaling ongoing growth and expansion in AI capabilities.

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NVIDIA's bold bet on the AI "trillion-dollar era": Jensen Huang claims chip revenue expectations have "strong visibility," and the target will continue to expand