NVIDIA’s Earnings Report in the Spotlight: The Rubin Cycle, Revolving Financing, and Long-Term Market Share

NVIDIA is scheduled to release its quarterly earnings report for the period ending in July next week. Given the pattern of recent quarters, the market has become accustomed to "beat-and-raise" outcomes (earnings exceeding expectations and guidance being raised). What will truly determine stock price elasticity are three longer-term issues: whether Rubin can successfully succeed Blackwell, whether AI demand continues to significantly outstrip supply, and the magnitude of financing and balance sheet commitments NVIDIA must undertake to secure future demand.

Based on broker forecasts, fundamentals remain robust. According to the Zephyr Trading Desk, Jefferies released a preview report this week, projecting NVIDIA's revenue for the July quarter to reach $95 billion, higher than the consensus estimate of approximately $91.9 billion. The revenue guidance for the October quarter is expected to reach $108 billion, also exceeding the market expectation of around $103.7 billion.

Morgan Stanley's report is relatively conservative, forecasting revenue of approximately $91.2 billion for the July quarter and about $102.3 billion for the October quarter. However, it similarly believes that recent trends will continue, with quarterly revenue potentially continuing to increase by approximately $10 billion quarter-over-quarter.

In other words, the core of the current market debate is whether the growth trajectory for 2027 and 2028 can continue to be revised upward after the company delivers strong results.

Blackwell remains strong, but Rubin is the key narrative for the next round of valuation.

In the short term, demand for Blackwell remains robust. Microsoft and Amazon's cloud businesses showed more significant improvement during the quarter, while long-term commitments to computing power from companies such as OpenAI and SpaceX continue to support market confidence in NVIDIA's data center revenue.

Morgan Stanley pointed out that although Rubin has not yet made a substantial contribution, NVIDIA's current growth is already quite strong; furthermore, greater acceleration may occur after the January quarter next year.

Rubin is one of the most important keywords in this earnings conference call.

Jefferies believes that the ramp-up speed for Rubin could be significantly faster than that of Blackwell in its early stages. This is because Rubin continues the 72-GPU Oberon NVL72 rack form factor, allowing it to leverage the liquid-cooling data center deployment and manufacturing infrastructure accumulated from GB200 and GB300.

Meanwhile, the new generation design eliminates a significant amount of manual cabling and pipeline installation. Management previously mentioned that the assembly time for compute trays is expected to be reduced from approximately two hours to five minutes.

The underlying implication is that NVIDIA is upgrading its AI chips into replicable, scalable "AI factory systems."

Jefferies projects that VR/R200 will account for approximately 12% of NVIDIA's GPU revenue in the third quarter of fiscal 2027, rise to over 40% by the fourth quarter, and become the dominant revenue source in the first quarter of fiscal 2028.

If this trajectory materializes, the market's valuation logic for NVIDIA will shift from "how long can the Blackwell cycle last" to "whether Rubin can unlock the next round of growth on a higher base."

Vera CPU: Not the main course, but it complements "full-stack control."

Beyond GPUs, Vera CPU represents an incremental growth area worthy of attention in the financial report.

Jefferies estimates that NVIDIA's CPU revenue in fiscal 2027 could reach $20 billion, including Grace and Vera; its calculations show that CPU revenue associated with GPU sales would be approximately $8.65 billion, while standalone Vera CPU revenue would be around $11.35 billion, with the annualized run-rate revenue approaching $32 billion by the fourth quarter.

In absolute terms, CPU revenue still cannot compare with NVIDIA's AI GPU business, serving more as a complementary enhancement. However, its strategic significance is substantial: Vera CPU strengthens NVIDIA's control in AI server and AI factory architectures through low-power LPDDR5X memory and NVLink coherent connectivity with the Rubin domain.

This will also exert new pressure on AMD and Intel. Particularly as large customers increasingly prefer purchasing entire racks or complete systems, NVIDIA is selling a comprehensive computing platform spanning GPUs, CPUs, networking, and software.

OpenAI's Major Deal: Securing Demand, Yet Raising Questions About "Circular Financing"

Of greater concern to the market is NVIDIA's long-term computing capacity arrangements related to OpenAI.

According to Jefferies, NVIDIA has reached an arrangement with SB Energy, under which SB Energy will build, own, and operate the PORTS-Pike Technology Campus in Ohio and lease it to OpenAI for 20 years, with NVIDIA serving as the exclusive compute provider.

NVIDIA will provide credit support for the initial 4.25 GW of IT capacity and holds options for the remaining 3.75 GW, bringing the total potential capacity to 8 GW, while also investing $1.5 billion in SB Energy.

NVIDIA stated that each generation of system deployment at the facility could correspond to approximately 1.5 million GPUs, generating $150 billion to $200 billion in revenue. OpenAI’s existing and planned commitments total approximately 12 GW, expandable to 16 GW, corresponding to roughly $600 billion in NVIDIA compute procurement by 2030.

This undoubtedly provides a clearer anchor for NVIDIA’s long-term order book. However, the market will also question: how much of this demand represents customers’ voluntary capital expenditure, and how much requires NVIDIA to drive through credit support, investment, or revenue-sharing arrangements?

Morgan Stanley believes that financing, market share, and gross margin are the three major points of contention currently concerning investors. NVIDIA’s management is likely to emphasize that these structures help accelerate AI infrastructure development, but investors need to see clearer accounting disclosures, including details on contingent obligations, lease and power payment support, and residual value guarantees.

This determines whether the market views it as 'locking in future revenue' or worries that it constitutes 'trading balance sheet strength for growth.'

Gross Margin and Cost Pressures: Stable in the Short Term, Long-Term Validation Still Required

NVIDIA’s high gross margin has always been a key basis for its valuation premium. Morgan Stanley expects the company may continue to maintain its guidance of mid-70% gross margin for fiscal year 2027.

However, pressures do exist. Costs for HBM, DRAM, advanced packaging, substrates, and front-end wafers remain on the rise, and the ramp-up phase for new products is typically accompanied by challenges in yield, testing, and supply chain integration.

Morgan Stanley also cautioned that the consensus expectation of a significant recovery in gross margin in the second half of fiscal year 2028 may be slightly optimistic.

This implies that if NVIDIA offers a more cautious outlook on medium- to long-term gross margins during its conference call, it could trigger short-term volatility. However, if management can clarify cost lock-ins, pricing power, and system-level sales structures, the event could instead serve as a "clearing of expectations."

The primary bottleneck may lie not in chips, but in electricity.

As AI capital expenditure progresses further, electricity is increasingly likely to become the most immediate constraint.

Jefferies points out that the gap between expected chip demand and grid supply capacity is widening.

Major cloud providers are increasingly partnering with utility companies to build dedicated gas-fired power plants and transmission facilities, while frontier AI labs and emerging cloud providers are adopting more "behind-the-meter" power solutions to bridge the timing mismatch between grid connection availability and compute deployment.

This does not mean that the expansion of AI infrastructure will halt, but it will make the conversion of orders into revenue less linear.

Solutions such as gas turbines, backup power systems, and fuel cells are being advanced, but equipment delivery lead times, grid interconnection approvals, local regulations, and community acceptance will all affect the pace of data center construction. Nuclear power and small modular reactors are more likely to become variables post-2030.

Therefore, NVIDIA's core challenge in the coming years will be whether its customers' data centers, power supply, and financing can keep pace in sync.

Clarity is the true catalyst for stock price movements.

Morgan Stanley maintains its "Overweight" rating and top pick status for NVIDIA, with a target price of $288. It notes that NVIDIA's current forward P/E ratio of approximately 17x for FY28 is not expensive relative to its own historical valuations, semiconductor peers, or the broader market.

However, low valuation alone does not necessarily lead to an immediate rebound. Over the past four quarters, NVIDIA has reported strong results, yet its stock price has consistently declined the following day, indicating that the market now treats “beating expectations” as the baseline scenario. The true drivers of valuation repair will depend on management’s ability to clearly address four key questions:

1. Beyond the guidance for the October quarter, will the January quarter see a significant acceleration due to Rubin;

2. Whether the ramp-up of Rubin is smooth enough to maintain product leadership;

3. The extent of financing obligations behind long-term agreements with partners such as OpenAI;

4. Whether pressures from power supply, regulation, and costs will affect the delivery pace beyond 2027.

Overall, NVIDIA’s latest earnings report is likely to remain strong. However, the market has entered a new phase: it is no longer satisfied with merely seeing demand, but rather seeks to understand how that demand is being fulfilled through the interplay of supply, power availability, financing, and profit margins.

NVIDIA’s narrative remains grand, and short-term performance is well-supported. Yet, as AI infrastructure investment reaches the trillion-dollar scale, investors must assess whether the entire AI industrialization system can sustain its operations.

Editor/lambor