NVIDIA Earnings Smash Expectations: Why the AI Bubble Is Set to Stretch Into 2026

NVIDIA Earnings Smash Expectations once again as the chipmaker posted another record quarter in 2025. The company reported $57 billion in revenue for Q3 2025, beating Wall Street forecasts by $2 billion. The results come as demand for AI chips continues to surge across the global tech sector.

The strong showing pushed fresh optimism across the AI industry. Many companies depend on NVIDIA’s GPU supply chain to power their large-scale models. The latest outlook suggests the momentum could continue well into 2026, even as questions about an AI bubble remain.

How NVIDIA’s AI Revenue Surged Past Forecasts

NVIDIA’s data center division delivered the bulk of the upside. This segment produces the Blackwell-series cloud GPUs used in generative AI training and inference. According to Reuters, the company’s latest chips have seen unprecedented demand across cloud providers. Jensen Huang called sales “off the charts” and confirmed that cloud GPU inventory is already sold out.

NVIDIA now expects $65 billion in revenue for Q4 2025. This projection strengthens confidence for enterprise buyers and AI developers who rely on the company’s roadmap. It also extends the financial runway for major AI labs, including OpenAI, Anthropic, and Microsoft, even as their own revenue models continue to evolve.

NVIDIA’s gaming unit was the only division that fell short of estimates. But the shortfall had little impact on the company’s overall performance. Industry analysts told Associated Press that the AI boom has fully eclipsed consumer GPU cycles.

The strong revenue numbers arrive during a key moment in the AI economy. Some executives, including Google’s leadership, have openly acknowledged froth in the sector. Yet NVIDIA’s results indicate sustained demand for training and deployment infrastructure. That pattern supports the idea that core AI compute might remain resilient into 2026.

How Rivals Like Google Could Shift the AI Chip Battle

Google introduced a new complication for NVIDIA this month. The company revealed that its Gemini 3 model was trained entirely on Google’s own Tensor Processing Units. This announcement marks another step toward reducing reliance on NVIDIA hardware. BBC News noted that Google sees its TPUs as a long-term cost advantage for its AI division.

If Google pushes deeper into custom chip manufacturing, the AI landscape could shift. A price war is possible as cloud providers seek alternatives to NVIDIA’s high-end GPUs. That competition may eventually lower AI infrastructure costs across the industry. For developers and consumers, cheaper compute would drive broader adoption of AI tools.

The long-term question is whether these competing chip ecosystems can grow without oversaturating the market. For now, NVIDIA’s dominance remains intact. Its earnings provide temporary relief for companies betting heavily on AI adoption. But the rise of Google’s TPU strategy shows that the market is entering a new phase.

NVIDIA Earnings Smash Expectations again this quarter, reinforcing the strength of the AI buildout heading into 2026. The coming months will reveal whether rivals like Google can meaningfully challenge NVIDIA’s lead or simply expand the market further. For now, the AI bubble appears stable—at least until the next earnings cycle.

FYI (keeping you in the loop)-

Q1: Why did NVIDIA earnings rise so sharply in 2025?

NVIDIA saw huge demand for its Blackwell cloud GPUs. Most sales came from its data center business. The AI sector continues to require large-scale compute.

Q2: Is the AI bubble close to bursting?

Some leaders believe a bubble exists. But NVIDIA’s revenue strength suggests demand remains strong into 2026. Competing chip ecosystems may influence the timeline.

Q3: How will Google’s Gemini 3 impact NVIDIA?

Gemini 3 was trained on Google TPUs. This could reduce Google’s dependence on NVIDIA chips. It may also push competition in AI hardware.

Q4: What does NVIDIA’s forecast mean for AI companies?

The strong forecast gives AI labs more time to build revenue models. It also suggests cloud GPU availability will remain tight.

Q5: Will AI chip prices drop in 2026?

Prices could fall if competition between NVIDIA and TPU manufacturers increases. Lower compute costs would benefit AI developers and consumers.