NVIDIA–Oracle–OpenAI: AI Growth Engine or Warning Signs of a Bubble?

TradingKey - Earlier this week, NVIDIA announced a preliminary partnership with OpenAI to jointly deploy 10 gigawatts of compute capacity. According to CEO Jensen Huang, this would translate to roughly 4–5 million GPUs. The first phase of the deployment—1 gigawatt—is expected to launch in the second half of 2026 and will be based on NVIDIA's new Rubin architecture. Under the deal framework, NVIDIA may invest up to $100 billion in OpenAI, with capital disbursed in proportion to the GW rollout schedule.

Following the announcement, NVIDIA shares rose more than 4% intraday, injecting new momentum into a stock that has been under pressure in recent weeks.

The timing of this partnership is notable: AI infrastructure investments have been expanding rapidly. Not long ago, OpenAI publicly announced a collaboration with Oracle to build “Stargate,” a 4.5GW hyperscale data center project in the U.S. Media reports also pointed to a five-year compute procurement agreement between the two parties totaling as much as $300 billion, set to begin ramping in 2027.

In other words, right after locking in a major commitment with one of the leading cloud providers, OpenAI is now entering into another massive agreement with a core compute supplier—raising fresh questions across the market: is this another powerful market catalyst for AI, or are we seeing early signs of a capital bubble?

OpenAI at the Center of It All

The central bottleneck for OpenAI has always been compute. Ongoing shortages have slowed product release timelines and delayed progress on training the next generation of large models. And this isn’t just an OpenAI problem—it’s a broader, industry-wide constraint.

For years, OpenAI relied on Microsoft as its exclusive compute provider. But lately, frustrated by tight supply, the company has started exploring more scalable infrastructure options—with Microsoft’s blessing.

So why is OpenAI making deals both with Oracle for cloud infrastructure and NVIDIA for GPUs?

Officially, this new partnership with NVIDIA is described as "complementary" to OpenAI’s existing relationships with Microsoft, Oracle, SoftBank, and the Stargate initiative. Put another way: Microsoft, Oracle, and Stargate primarily handle data centers, network access, power supply, rack space, and operations—what you might call “heavy infrastructure.” NVIDIA contributes at a different layer, supplying the crucial hardware compute capacity and forward-looking product roadmap.

This layered approach reflects a division of labor across the AI infrastructure supply chain, where different players provide different pieces of the stack. The result is a modular, coordinated ecosystem with staggered roles.

There's also a rather closed-loop dynamic here: NVIDIA injects capital into OpenAI, OpenAI uses that money to pay for Oracle’s cloud services, and Oracle turns around and spends a portion of that on purchasing more GPUs from NVIDIA. The capital essentially cycles back to its origin.

Of course, all parties get something out of the loop: OpenAI secures stable, diversified access to compute; Oracle expands its cloud business; and NVIDIA tightens its grip on the core of global AI infrastructure.

Another Key Player: Broadcom

Aside from the three giants—NVIDIA, Oracle, OpenAI—Broadcom has also begun drawing attention.

Not long ago, Broadcom announced a major custom chip agreement with a large, unnamed customer. Industry consensus strongly suggests that the customer is OpenAI. This move was widely seen as part of OpenAI’s effort to reduce dependence on NVIDIA and pursue a more diversified, heterogeneous compute strategy.

However, just a few weeks later, OpenAI turned around and announced a potential multi-billion-dollar deal with NVIDIA—casting some doubt over what its real intentions are.

That said, there’s no real contradiction. Broadcom’s chips are expected to begin shipping in 2026, but will still need to go through tape-out, validation, and production scaling. They’re well-suited to long-term development timelines. Meanwhile, NVIDIA’s Rubin platform is expected to start shipping at scale in the second half of 2026, and already has major advantages in interconnect (NVLink) and software ecosystem (CUDA).

In practice, OpenAI’s partnership with NVIDIA focuses on high-performance GPU systems and system-level hardware. Its engagement with Broadcom is in a different lane—custom chips, networking solutions, and interconnect design.

These partnerships address different parts of the stack, and aren’t in conflict. Rather, they reflect complementary approaches to building a flexible, scalable infrastructure base.

Shiny Surface, Real Risks

The story may sound synergistic, but the underlying capital structure comes with substantial risk—and markets are alert.

First among those risks is OpenAI's financial position. Despite being valued at over $100 billion, the company is not yet profitable. Analysts expect it could lose more than $5 billion in 2025, while revenue is projected at only around $10 billion—meaningfully below the ~$60 billion per year required to support its cloud infrastructure commitments. Meanwhile, OpenAI faces strong, well-funded competition from Google, Anthropic, Mistral, Meta, and others.

Oracle also faces mounting pressure. In an effort to capture AI momentum, the company has been scaling CAPEX aggressively—well beyond its operating cash flow. Its debt burden is significantly higher than peers. Current estimates place Oracle’s debt-to-equity ratio at a staggering 427%, compared to Microsoft’s 32.7%.

To fund its AI pivot, Oracle has taken on multiple rounds of high-leverage financing and long-dated investment contracts. Its balance sheet is rapidly transforming into that of a capital-heavy infrastructure platform that leans heavily into AI.

This “capital loop” model—where upstream investments, compute purchasing, and downstream hardware orders circulate internally—is starting to raise flags. It bears some resemblance to what happened during the 2000 tech bubble. Back then, Cisco, Lucent, and others offered credit or equity financing to help clients buy their equipment—only to realize, too late, that they had created an artificial cycle.

Some market analysts are already drawing the connection.

Jay Goldberg, an analyst at Seaport Global Securities, compared it to “parents co-signing your first home mortgage.” In good times, this mutual support allows everyone to grow faster and show stronger numbers. But once the cycle reverses (and it always does), the shared risk doesn't disappear. It explodes.

When the market is booming, investments from companies like NVIDIA into OpenAI help generate demand for GPUs, boosting top-line revenue and, in turn, stock performance. That stock performance then funds more investment and secures more contracts. The effect is rapidly compounding.

But when the cycle turns—if capital tightens, demand slows, or confidence erodes—this loop can reverse just as fast. That opens the door to valuation resets, impairments, unmet obligations, and broader systemic pressure all at once.

What Else Might Get Pulled Along?

While the majors are now richly priced—NVIDIA at 50.62x TTM P/E, Oracle at 67.44x, and Broadcom at 86.18x—investors are asking: where’s the opportunity further down the stack?

Some key categories to watch:

▍Compute Layer 

• TSMC – Exclusive foundry partner for NVIDIA’s Blackwell / B100 chips. As AI demand climbs, its advanced-node output could keep scaling. 

• SK Hynix (000660.KQ) – Supplies HBM3e high-bandwidth memory for high-end NVIDIA GPUs—a critical component for multi-GPU cluster efficiency. 

• Supermicro (SMCI) – Official NVIDIA-certified server vendor. Supplies fully integrated systems for Oracle Cloud’s AI environments and OpenAI workflows.

▍Cloud Service Layer 

• CoreWeave (CRWV) – A GPU-specialized cloud provider backed by NVIDIA. Works alongside Oracle in supporting OpenAI—with flexible, scale-up infrastructure. 

• Hugging Face (Private) – Hosts open-source foundation models compatible with OpenAI’s APIs. Supports fine-tuning and deployment on Oracle Cloud (OCI), adding developer flexibility.

▍Data Layer 

• Snowflake (SNOW) – Now integrated with Oracle Cloud’s data backend. Enables high-quality data ingestion and management for OpenAI model training in finance and healthcare verticals. 

• Palantir (PLTR) – Provides enterprise-grade data integration and AI tooling atop Oracle Cloud. Actively used in defense, manufacturing, and industrial applications.

▍Application Layer 

• Salesforce (CRM) – Among the earliest companies to integrate OpenAI’s tech into its Einstein GPT product suite. Runs on Oracle Cloud and targets use in sales, support, and enterprise CX. 

• Epic Systems (Private) – A major U.S. EHR provider. It now connects to Oracle’s data lake and uses GPT-4 for clinical summarization and workflow automation. 

• CrowdStrike (CRWD) – Provides security and compliance solutions across the NVIDIA–OpenAI–Oracle stack, including GDPR, HIPAA, and other regulatory certs.