NVIDIA Announces Financial Results for Third Quarter Fiscal 2026

On November 19, 2025, NVIDIA Corporation (NASDAQ: NVDA) released its financial results for its third quarter of fiscal 2026, reporting a blockbuster quarter fueled largely by surging demand for artificial intelligence (AI) infrastructure. The company posted record revenue, strong profitability, and ambitious forward guidance — underscoring its dominant position in the booming AI era.

1. Overview of Performance

In Q3 FY 2026 (ended October 26, 2025), NVIDIA reported total revenue of $57.0 billion, marking a 22% increase from the prior quarter and a staggering 62% year-over-year jump compared to Q3 of fiscal 2025. (NVIDIA Newsroom)

On the profitability front, the company generated GAAP net income of $31.91 billion, up 21% sequentially and 65% year-over-year. (NVIDIA Newsroom) Diluted GAAP earnings per share (EPS) stood at $1.30, also up from $1.08 in Q2 FY 2026 and $0.78 in Q3 FY 2025. (NVIDIA Newsroom)

Gross margins remained strong — 73.4% on a GAAP basis, and 73.6% on a non-GAAP basis. (NVIDIA Newsroom) Operating expenses rose, but operating income remained robust at $36.01 billion (GAAP), up 27% quarter-over-quarter. (NVIDIA Newsroom)

2. Data Center: The Engine of Growth

The standout segment continues to be NVIDIA’s Data Center business, which delivered a record $51.2 billion in revenue for the quarter. This figure reflects a 25% quarter-over-quarter increase and an astounding 66% year-over-year growth. (NVIDIA Newsroom)

This surge is largely driven by the demand for NVIDIA’s Blackwell architecture, particularly its Ultra variants, which have set new performance and efficiency benchmarks. In fact, NVIDIA revealed that Blackwell achieved top rankings in the SemiAnalysis InferenceMAX benchmarks, delivering 10× more throughput per megawatt compared with the previous generation. (NVIDIA Newsroom)

On the partnerships front, NVIDIA made several strategic announcements:

It committed to a significant deployment with OpenAI, providing at least 10 gigawatts of NVIDIA systems for OpenAI’s next-gen AI infrastructure. (NVIDIA Newsroom)
It forged alliances with major cloud providers — Google Cloud, Microsoft, Oracle, and xAI — to build out large-scale AI data centers using NVIDIA GPUs. (NVIDIA)
For the first time, Anthropic will run and scale using NVIDIA infrastructure, initially building 1 gigawatt of capacity using Grace Blackwell and Vera Rubin systems. (NVIDIA)
NVIDIA also announced a collaboration with Intel to co-develop custom data center and PC products leveraging NVLink, enabling tighter interconnects. (NVIDIA)

Moreover, NVIDIA laid out plans for seven new supercomputers, including one at the U.S. Department of Energy (DOE) site: “Solstice,” which will include 100,000 Blackwell GPUs, and “Equinox,” which will use 10,000 Blackwell GPUs. (NVIDIA) They also announced efforts to revitalize U.S.-based production: the first Blackwell wafer was produced in Arizona via TSMC, highlighting NVIDIA’s push for domestic GPU manufacturing. (NVIDIA Newsroom)

Other product and architectural innovations include:

Rubin CPX, a new GPU class designed to handle massive-context processing workloads. (NVIDIA)
NVQLink™, an open architecture that tightly couples NVIDIA GPUs with quantum processors, an exciting step for hybrid classical-quantum systems. (NVIDIA Newsroom)
NVLink Fusion™, designed to bring NVIDIA’s NVLink high-speed interconnect to Arm’s Neoverse platform — showing a cross-architecture ambition. (NVIDIA)
Omniverse DSX, a blueprint for building AI factories at gigawatt scale, integrating compute, design, and orchestration. (NVIDIA Newsroom)
BlueField-4, a data center processor tailored for AI “operating systems,” with partners such as Dell, Oracle, and Red Hat already building on it. (NVIDIA)
Spectrum-X™ Ethernet switches, to enable high-performance networking in AI data centers, adopted by companies including Meta, Microsoft, and Oracle. (NVIDIA)
Collaborating with Nokia to bring AI-powered RAN (Radio Access Network) to 5G-Advanced and future 6G networks. (NVIDIA)
Working with Palantir to integrate AI operations and infrastructure, building a combined stack for operational AI. (NVIDIA)

Finally, NVIDIA expanded its market reach globally. It announced:

A £2 billion investment in the U.K. to build AI infrastructure with partners like Microsoft and Nscale. (NVIDIA)
A collaboration with the South Korean government and industrial leaders such as Hyundai, Samsung, SK Group, NAVER Cloud, aiming to deploy over a quarter-million Blackwell GPUs across the country. (NVIDIA)

3. Other Business Segments

While Data Center is NVIDIA’s star performer, other segments also contributed to Q3 FY 2026’s strong results:

Gaming & AI PCs

Gaming revenue came in at $4.3 billion, which is a modest 1% decline quarter-over-quarter but represents a 30% year-over-year growth. (NVIDIA)
NVIDIA spotlighted several important gaming-related launches: titles like Borderlands 4, Battlefield 6, and ARC Raiders all leveraged DLSS 4 with Multi-Frame Generation and NVIDIA Reflex, improving performance and responsiveness. (Nasdaq)
The company also celebrated the 25th anniversary of its GeForce brand at the GeForce Gamer Festival held in Seoul. (NVIDIA)
On the tools side, NVIDIA introduced an RTX Remix update for modders (adding path-traced particle systems) and released a 3D object generation “Blueprint”, optimized for RTX AI PCs, plus performance boosts for AI tools running on RTX platforms. (NVIDIA)

Professional Visualization

This segment saw $760 million in revenue, up 26% from the prior quarter and 56% versus a year ago. (NVIDIA)
A key product highlight: DGX Spark™, billed as the world’s smallest AI supercomputer, started shipping — bringing NVIDIA’s AI stack into a highly compact form factor. (NVIDIA)

Automotive & Robotics

Revenue reached $592 million, up 1% from the previous quarter and 32% from the same quarter last year. (NVIDIA)
NVIDIA introduced the DRIVE AGX Hyperion 10 platform, a reference architecture for Level 4 autonomous vehicles, combining compute, sensors, and software. (NVIDIA)
It also announced a long-term mobility partnership with Uber, targeting 100,000 level-4-ready vehicles by 2027. (NVIDIA)
In robotics, NVIDIA is working with companies like Agility Robotics, Amazon Robotics, Lucid, Toyota, Figure, Skild AI, and others in “physical AI” and next-gen manufacturing. (NVIDIA)

4. Capital Return to Shareholders

NVIDIA has been aggressively returning capital to shareholders. During the first nine months of fiscal 2026, the company returned $37.0 billion in the form of share repurchases and cash dividends. (NVIDIA Newsroom)

As of the end of Q3, NVIDIA still has $62.2 billion remaining in its repurchase authorization. (NVIDIA Newsroom)

The next cash dividend is set at $0.01 per share, payable on December 26, 2025, to shareholders of record as of December 4, 2025. (NVIDIA Newsroom)

5. Guidance & Outlook

NVIDIA provided a bullish outlook for Q4 of fiscal 2026, forecasting:

Revenue of $65.0 billion, plus or minus 2%. (NVIDIA)
GAAP gross margin of ~74.8% and non-GAAP gross margin of ~75.0%, each with a ±50 basis points range. (NVIDIA Newsroom)
Operating expenses are expected to be about $6.7 billion (GAAP) and $5.0 billion (non-GAAP). (NVIDIA)
Other income/expense (GAAP and non-GAAP) is estimated to result in net income of around $500 million, excluding gains/losses from investments in publicly held or non-marketable equity securities. (NVIDIA)
Tax rate is projected to be 17.0% ± 1% (both GAAP and non-GAAP), excluding discrete items. (NVIDIA Newsroom)

6. Strategic Insights & Implications

The Q3 fiscal 2026 report underscores several larger themes about NVIDIA’s business and the broader AI market:

a) AI Compute Demand Is Exploding

NVIDIA’s record data center revenue, especially driven by Blackwell chips, demonstrates that demand for AI training and inference infrastructure remains explosive. The company’s commentary suggests that compute demand is not just accelerating — it’s compounding, as both training workloads (foundation models) and inference (real-time AI) grow exponentially. (NVIDIA Newsroom)

Jensen Huang, CEO of NVIDIA, described the moment as a “virtuous cycle of AI,” emphasizing that “the AI ecosystem is scaling fast” — with more foundational model makers, AI startups, and industries embracing generative and agentic AI. (NVIDIA Newsroom)

b) Strategic Partnerships & Infrastructure Expansion

NVIDIA is cleverly pairing its technology leadership with strategic alliances to cement its role in the global AI infrastructure. The tie-up with OpenAI (10 GW of compute), partnerships with major cloud players, and newly announced supercomputing projects reveal that NVIDIA is not just selling chips — it's enabling next-generation AI factories.

The development of supercomputers like Solstice (100,000 Blackwell GPUs) and Equinox (10,000 GPUs) suggests NVIDIA is planning for sustained, large-scale AI workloads. (NVIDIA)

c) Diversification Across Verticals

While data center remains the powerhouse, NVIDIA’s presence in gaming, professional visualization, automotive, and robotics is growing. Their launch of compact but powerful DGX Spark, their roadmap in autonomous driving (DRIVE AGX Hyperion 10), and their engagement in robotics and physical AI show that NVIDIA is not putting all its eggs in one basket.

This diversification helps NVIDIA hedge risks and also positions it to monetize AI compute across industries.

d) Capital Return Indicates Confidence

Returning $37 billion in the first nine months of fiscal 2026, while still holding a large repurchase authorization, signals strong cash flow generation and confidence from management. The modest dividend (while small per share) complements the aggressive buyback — a typical strategy for tech companies flush with cash.

e) Forward Guidance is Very Bullish

The forecast of $65 billion in Q4 revenue represents significant sequential growth (~14% from Q3), suggesting NVIDIA expects continued scaling of its business. The projected margin expansion (to 74.8–75.0%) also indicates operational leverage, even as they increase spending (e.g., R&D, partnerships, infrastructure buildout).

7. Risks and Considerations

Despite the remarkably strong quarter, there are several risk factors and uncertainties:

Supply Constraints: As demand for Blackwell systems surges, NVIDIA may face production constraints. While management claims “cloud GPUs are sold out,” such strong demand could strain supply chains, particularly for high-performance wafers. (NVIDIA Newsroom)
Manufacturing Risk: Building Blackwell wafers domestically (e.g., TSMC in Arizona) is a major move, but scaling production reliably in new facilities comes with risks — yield issues, ramp-up delays, or cost pressures could emerge.
Competition: As AI becomes a cornerstone of future compute infrastructure, competition from rivals (other GPU makers, specialized AI chipmakers, or custom accelerators) could intensify.
Macroeconomic Uncertainty: Global economic conditions — inflation, interest rates, geopolitical risks — could affect enterprise spending on AI infrastructure.
Policy and Regulation: Export controls, trade policies, and regulation around AI could disrupt NVIDIA’s ability to ship or maintain partnerships globally. Also, taxation and regulatory scrutiny of large tech firms remain persistent risks.
Technology Risk: The AI landscape is evolving fast. New architectures, potentially novel compute paradigms (e.g., beyond Blackwell), or shifts in how models are trained / inferred could change NVIDIA’s roadmap.

8. Market Reaction & Analyst Sentiment

NVIDIA’s Q3 earnings came in well above expectations, surprising many analysts. The strong top-line beat and bullish Q4 outlook reinforced investor confidence in NVIDIA’s long-term AI narrative. Some Wall Street observers have interpreted the results as validation that the ongoing AI boom is not peaking yet.

Analysts like Dan Ives (Wedbush) and others have argued that concerns of an “AI bubble” are overblown, pointing to continued structural demand in both cloud training and inference as driving forces. (Business Insider)

Moreover, they highlight that NVIDIA’s deep partnerships (OpenAI, cloud providers), infrastructure plays (supercomputers), and manufacturing strength (domestic wafer production) could create durable competitive advantages.

9. Strategic Implications & Long-Term Impact

The Q3 FY 2026 results further cement NVIDIA’s role not just as a chipmaker, but as a platform builder for the AI era. Here are some potential long-term strategic implications:

AI Infrastructure Leader: With its Blackwell architecture, large-scale deployments, and supercomputing roadmap, NVIDIA could define the backbone of the next generation of AI infrastructure for both cloud providers and AI-focused enterprises.
Edge / On-Prem AI: While much of the growth is in cloud data centers, NVIDIA is also pushing into edge and on-prem contexts (via Omniverse, robotics, AI factories). This diversification strengthens its long-term relevance across compute environments.
AI + Quantum Convergence: The NVQLink architecture hints at NVIDIA’s ambition to build bridges between classical GPU compute and quantum computing — a bet on the convergence of future compute paradigms.
Industrial & Communications AI: By working with telecom (Nokia, 5G/6G), manufacturing (AI factories), and mobility (autonomous vehicles), NVIDIA is positioning itself to be a foundational compute provider in multiple physical sectors beyond traditional datacenters.
Sustainable Growth via Reinvestment: The ongoing capital returns and reinvestment into R&D, manufacturing, and partnerships reflect a balanced strategy: rewarding shareholders now while building the infrastructure and products that will drive future growth.

NVIDIA’s Q3 fiscal 2026 financial results were nothing short of extraordinary. With $57 billion in revenue, sky-high data center demand, and robust profitability, the company is riding the AI wave with tremendous momentum. Its guidance — $65 billion for Q4 — suggests that management believes this is only the beginning.

Critically, NVIDIA is doing more than selling GPUs. It is building the infrastructure (supercomputers, quantum interconnects), forging global partnerships, and pushing into new verticals (robotics, telecom, automotive). These moves reflect a long-term strategy to dominate as AI becomes deeply embedded in every aspect of technology and industry.

That said, the path ahead is not without risks: manufacturing scale, supply chain constraints, rising competition, and macro or regulatory shocks could pose challenges. But for now, NVIDIA appears to be executing at a level that many once thought unattainable — reinforcing its position as the bedrock of the AI compute world.

As the AI ecosystem accelerates, investors and industry watchers alike will be watching whether NVIDIA can sustain this pace, continue to innovate, and maintain its leadership. If Q3 is any indicator, the company is not just riding the AI wave — it’s helping to define it.