Swan.my.id - United States - Pre-Earnings NVDA 2026 is drawing investor attention as NVIDIA prepares to report its fiscal second-quarter results amid a major expansion of artificial intelligence infrastructure. The chip giant has announced up to $105 billion in credit support for a massive OpenAI data center project in Ohio.
The announcement has reignited debate over how money moves through the rapidly growing AI ecosystem. Critics argue that technology companies may be financing one another in a circular flow. Supporters, however, see the arrangements as a new form of infrastructure financing for an industry entering an industrial-scale growth phase.
The earnings report comes at a critical moment for NVIDIA. The company remains one of the biggest beneficiaries of global AI spending, while its Blackwell architecture continues to support data center expansion. At the same time, investors are watching valuation, export restrictions, debt exposure across the AI sector, and increasingly high expectations for future growth.
Pre-Earnings NVDA 2026 Comes With Strong Growth Expectations
NVIDIA was scheduled to release its fiscal second-quarter 2027 results on August 26, 2026. The report followed a strong first quarter in which the company delivered revenue of $81.6 billion.
That figure represented an 85% year-over-year increase. It also exceeded the analyst estimate of approximately $79.1 billion. Non-GAAP earnings per share reached $1.87, compared with expectations of around $1.77.
The Data Center segment remained the main growth engine. Revenue from the segment climbed 92% year over year to $75.25 billion.
Demand for NVIDIA’s Blackwell architecture played a major role. Networking technologies such as InfiniBand and NVLink also supported the expansion of its data center business.
NVIDIA guided for fiscal second-quarter revenue of about $91 billion, plus or minus 2%. The company also expected non-GAAP gross margin to remain around 75%.
However, Wall Street expectations were already higher. Analyst consensus stood near $93.5 billion in revenue, while expected earnings were approximately $2.01 per share.
That difference is important. NVIDIA has beaten analyst expectations for four consecutive quarters. Therefore, investors are no longer watching only whether the company meets its own guidance. They are also watching whether it can exceed an already elevated market consensus.
NVIDIA’s $105 Billion OpenAI Financing Raises Questions
On August 17, NVIDIA announced credit support of up to $105 billion for OpenAI’s planned data center campus in Ohio.
The initial project is expected to provide 4.25 gigawatts of capacity. Another 3.75 gigawatts could be added through an expansion option.
The facilities are expected to be built and operated by SB Energy. OpenAI is expected to lease the infrastructure under a long-term arrangement.
NVIDIA also announced a direct $1.5 billion investment in SB Energy. The move puts NVIDIA closer to the infrastructure spending that ultimately drives demand for its chips.
The development has created renewed discussion about so-called circular financing in the AI industry.
A simplified version of the criticism looks like this:
- Microsoft provides funding and infrastructure support to OpenAI.
- OpenAI purchases computing capacity from cloud providers.
- Cloud providers purchase NVIDIA chips and networking equipment.
- NVIDIA provides financing for infrastructure used by AI companies.
- AI companies then purchase more NVIDIA-powered computing capacity.
Critics argue that money can circulate among a relatively small group of major technology companies.
Nevertheless, the structure does not automatically make the business model fraudulent. Unlike historical accounting scandals, the AI ecosystem is supported by physical infrastructure, semiconductor products, data centers, electricity consumption, and actual computing demand.
The central question is therefore not simply whether money moves in a circle. The more important question is whether end-user demand continues to grow fast enough to support the investment.
AI Infrastructure Spending Remains the Main Growth Driver
The broader spending picture remains significant.
Meta has projected capital expenditure of roughly $125 billion to $145 billion for 2026. Microsoft has indicated spending of about $190 billion, while Amazon has outlined approximately $200 billion.
Together, those figures approach $535 billion.
Meanwhile, NVIDIA has moved beyond simply supplying chips. Its involvement in financing infrastructure shows how strategically important the company believes AI computing demand will remain.
Another major development came from NVIDIA’s partnership with six global asset managers. Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR were brought together to help mobilize more than $500 billion in third-party capital for AI infrastructure.
The strategy reflects a broader shift. AI infrastructure is increasingly being treated as a long-term industrial investment rather than a short-term technology trend.
However, rapid spending does not guarantee equally rapid returns.
Investors must still determine whether data center operators can generate enough revenue to justify the enormous cost of GPUs, power systems, cooling facilities, networking equipment, and real estate.
Why the AI Financing Debate Is Different From Enron
One of the strongest bearish arguments surrounding NVIDIA involves the possibility of excessive circular financing.
Investor Michael Burry has compared aspects of the current AI investment cycle with accounting problems seen during the Enron era. Such comparisons have attracted attention because the AI industry involves large transactions between companies that are often strategic partners.
There are, however, important differences.
Enron’s scandal involved fraudulent accounting and fictional or misleading representations of assets and profits. In the AI industry, the underlying infrastructure is tangible.
NVIDIA produces physical GPUs. Data centers consume enormous amounts of electricity. Cloud providers operate real facilities. Companies also generate revenue from customers using AI services.
That distinction does not eliminate investment risk. It simply changes the nature of the risk.
The key concern is whether the infrastructure can eventually generate sufficient economic returns.
OpenAI’s enterprise business provides one indication of broader adoption. Its enterprise revenue reportedly reached $40 billion in annual recurring revenue and moved ahead of consumer revenue.
This suggests that AI spending is not limited to technology companies. Banks, retailers, manufacturers, and other businesses are also paying for AI services from operating budgets.
At the same time, AI usage continues to increase even as the cost of generating individual tokens falls.
Google, for example, has reported processing around 3.2 quadrillion tokens per month. That represents roughly seven times the volume from a year earlier.
For NVIDIA, falling token prices are not necessarily a direct threat. NVIDIA sells the computing infrastructure required to process AI workloads rather than the AI tokens themselves.
Key Risks for NVDA Investors
Despite the strong growth outlook, NVIDIA faces several risks that could influence its stock price.
China Export Restrictions
Restrictions on advanced AI chip exports to China remain one of the most direct risks.
China is a major technology market, and tighter restrictions could reduce NVIDIA’s addressable market. The company has also indicated that national security considerations could take priority over commercial interests.
Because of that, investors should continue monitoring management comments about China during earnings calls.
High Market Expectations
Another risk is the unusually high expectations surrounding NVIDIA.
A company can report strong growth and still see its stock fall if investors expected even better results.
With analyst revenue expectations already above NVIDIA’s own guidance, the earnings bar is extremely high.
Therefore, the market reaction may depend heavily on forward guidance rather than the headline quarterly numbers alone.
Neocloud Debt
The financial condition of AI cloud providers is another concern.
CoreWeave, one of the most closely watched AI-focused cloud companies, has accumulated significant debt while reporting negative free cash flow.
The company has also secured large contracted revenue commitments. However, contracts are not the same as cash already received.
If a highly leveraged AI infrastructure company experiences financial stress, investor sentiment could spread across the broader AI sector.
Depreciation Risk
Another issue involves the useful life of AI infrastructure.
Michael Burry has argued that the industry could underestimate depreciation costs by as much as $176 billion through 2028.
If GPUs and data center equipment become obsolete faster than expected, companies could face larger future depreciation expenses.
This does not mean current financial statements are necessarily incorrect. Instead, it highlights an important assumption investors should monitor.
NVDA Technical Outlook Before Earnings
NVIDIA’s technical structure remained broadly bullish heading into the earnings period.
The stock was trading around $217.56 in the latest technical snapshot provided for the analysis. It remained above its 20-day moving average of $212.38 and its 50-day moving average of $207.12.
More importantly, the stock remained well above its 200-day moving average near $195.18.
The key resistance level was around $227.32. A sustained move above that level could potentially open the way toward the $236.40 area.
On the downside, the $212.38 area represented the first important support zone. The next level was around $207.12, followed by the longer-term $195.18 area.
Momentum indicators suggested that short-term conditions were cooling.
The Stochastic RSI showed %K around 64.75 and %D around 81.20. The divergence suggested that momentum was weakening after the stock’s strong recovery from its late-July decline.
Therefore, NVIDIA’s long-term trend remained positive, but the short-term setup was less certain.
What Investors Should Watch Next
The NVIDIA earnings report was expected to provide more than a snapshot of past performance. Investors were also looking for clues about the next phase of the AI investment cycle.
Several indicators deserve particular attention:
- Data Center revenue growth and future guidance.
- Demand for Blackwell GPUs and networking products.
- Gross margin trends.
- Free cash flow generation.
- Cash conversion relative to net income.
- The impact of China export restrictions.
- Customer concentration among major AI companies.
- Capital spending plans from hyperscale cloud providers.
- Financial conditions among AI-focused cloud operators.
One metric that deserves special attention is NVIDIA’s cash conversion.
The ratio of operating cash flow to net income had declined from approximately 0.94 times to 0.79 times over the periods highlighted in the analysis.
That does not represent an immediate warning sign. However, a continued decline could raise questions about the quality and sustainability of earnings growth.
Is NVIDIA’s AI Financing Strategy Sustainable?
The debate around NVIDIA and OpenAI ultimately comes down to the economics of AI infrastructure.
There are clear reasons for optimism. Data Center revenue is growing rapidly, hyperscalers continue to invest heavily, and AI adoption is expanding beyond technology companies.
However, the scale of spending also creates risks.
The industry must eventually demonstrate that massive investments in GPUs, data centers, electricity, and networking infrastructure can produce sustainable returns.
For NVIDIA, the current position remains unusually strong. It sits at the center of the AI computing supply chain while benefiting from demand across cloud providers, enterprises, and AI laboratories.
Still, the stock market does not reward growth alone. It also evaluates expectations, valuation, cash flow, competition, and future profitability.
That is why the Pre-Earnings NVDA 2026 story is bigger than one quarterly report.
The $105 billion OpenAI financing commitment highlights NVIDIA’s confidence in the next phase of AI infrastructure. At the same time, it raises legitimate questions about how capital flows through the ecosystem.
For investors, the most important signal will be whether real AI usage and customer revenue continue to grow fast enough to justify the enormous infrastructure spending.
If that trend continues, NVIDIA could remain one of the central beneficiaries of the AI expansion. If growth slows while financing and depreciation costs rise, the market could become far less forgiving.