MC EXPLAINER Boom or bubble? What Nvidia’s blockbuster quarter reveals about AI’s future and India’s place in it

Wall Street has been living in a strange split screen.

On one side: AI is the future. Everyone knows it. Big Tech is pouring hundreds of billions into data centres as if tomorrow depends on it.

On the other: the market is starting to twitch. Valuations look stretched. Returns are still patchy. The phrase 'AI bubble' has moved from water-cooler chatter to dinner-table anxiety.

Then Nvidia reported earnings.

What Nvidia delivered, and why it mattered

Nvidia’s latest quarter wasn’t just 'good.' It was the kind of quarter that resets a conversation.

For the three months ending October, the company said:

• Revenue hit $57 billion, up 62 percent from a year ago, above Wall Street’s expectations, as cited by CNBC.
• Profit rose to $31.9 billion, up 65 percent year-on-year.
• Data-centre revenue, the AI engine, was $51.2 billion, up 66 percent, and now accounts for nearly all of Nvidia’s growth.
• Next quarter guidance was about $65 billion, comfortably ahead of consensus near $62 billion.

The stock rose roughly 4–5 percent after hours. A sigh of relief.

Nvidia had been sliding with the market in early November as AI scepticism crept in.

That reaction matters because Nvidia is no longer just another tech company. It’s a market mood-setter. It recently became the first listed firm to briefly surpass $5 trillion in value, surpassing the size of almost every economy except those of the US and China. So when it sneezes, indices catch a cold.

This quarter did more than beat expectations. It put some backbone back into the AI story.

'There’s been a lot of talk about an AI bubble.'

On the earnings call, the Nvidia CEO Jensen Huang addressed the elephant in the room before anyone else could: “There’s been a lot of talk about an AI bubble. From our vantage point, we see something very different.”

His case was deliberate, and simple:

First, he said we’re in a structural computing shift. Moore’s Law, the old rhythm of chips doubling in power every couple of years, is slowing. So the world is moving to accelerated computing using GPUs. Nvidia’s turf.

Second, he argued that AI demand is spreading. This isn’t just OpenAI and the US cloud giants anymore. He pointed to enterprises, national governments building 'sovereign AI,' and the next frontier of agentic and physical AI,  software agents, robotics, and autonomous systems.

Third: the order book is already gigantic. Nvidia says it sees about $500 billion of demand for its Blackwell and Rubin platforms through 2026. Blackwell systems are 'off the charts,' Huang said, and cloud GPUs are still 'sold out.'

CFO Colette Kress added the scale behind the boom: hyperscalers have pushed AI data-centre capex to roughly $600 billion this year, more than $200 billion above what they planned at the start of the year.

The message from the top: this isn’t hype. It’s infrastructure.

And yet, the market still has two minds...

For now, the numbers have done their job. AI-linked stocks from AMD to TSMC, Broadcom and Oracle all traded higher in sympathy after Nvidia’s print, and futures for the S&P 500 and Nasdaq turned up as the earnings hit the tape.

But the doubts that sparked the 'bubble' chatter haven’t disappeared.

A few big signals have spooked investors in recent weeks:

1.) According to Bloomberg, SoftBank’s Masayoshi Son and Peter Thiel’s hedge fund Thiel Macro have both sold out of Nvidia, crystallising huge gains and feeding the sense that insiders are taking money off the table.

2.) In the latest quarter, as per Investing.com, just four big customers, think Microsoft, Amazon, Google and Meta, accounted for about 61 percent of Nvidia’s sales, up from 56 percent in the previous quarter. If even one of those giants slows AI capex or pushes harder into in-house chips, Nvidia’s growth profile changes quickly.

3.) Nvidia isn’t only selling to AI companies like OpenAI and Anthropic. It is also investing in them.

As per the coverage by Reuters, two deals stand out:

• A letter of intent to invest up to $100 billion in OpenAI, as the ChatGPT maker builds at least 10 gigawatts of Nvidia-powered AI data centres.
• A new partnership where Nvidia will invest up to $10 billion in Anthropic, alongside Microsoft’s $5 billion, while Anthropic commits to spending $30 billion on Microsoft Azure compute powered by Nvidia’s Grace Blackwell and Vera Rubin systems.

In plain English: Nvidia puts money into AI firms, those firms use the money to buy Nvidia hardware (often via cloud partners), and Nvidia books the revenue.

Goldman Sachs (AI: IN A BUBBLE? - published on October 25, 2025) estimates that such 'circular' deals could account for roughly 15 percent of Nvidia’s sales next year, raising questions about how much of the apparent demand is truly independent.

4.) Nvidia is also spending more to rent capacity back from cloud providers that can’t fully utilise the GPUs they’ve already bought. Those “capacity contracts” nearly doubled in the quarter to about $26 billion, according to Reuters.

5.) Michael Burry, the 'Big Short' investor who called the subprime crisis, has taken public short positions against Nvidia and Palantir and accused parts of the AI complex of 'suspicious revenue recognition'. He has warned about what he calls suspicious revenue dynamics and argues hyperscalers are depreciating GPU fleets over five to six years even though product cycles look closer to two to three.

6.) Nvidia shares are up over 1,200 percent in three years, briefly making it the world’s most valuable company, but also volatile enough to drop sharply on AI jitters.

So what did this quarter really prove? That demand for Nvidia’s chips is real, huge and still accelerating. It did not prove that this level of spending will remain rational indefinitely.

That tension is the core of the AI-bubble debate.

AI is now geopolitics with a chip inside it

With top-end exports to China still constrained, Nvidia is steering the build-out elsewhere.

In the last couple of days:

• Saudi Arabia’s Humain has announced massive Nvidia-powered AI campuses, scaling to hundreds of thousands of GPUs over time.
• AWS and Humain plan an 'AI Zone' in Riyadh using up to 150,000 accelerators, mixing Nvidia chips and Amazon’s Trainium.
• The US has approved exports of up to 35,000 advanced Nvidia chips/servers to Saudi Arabia and the UAE, reversing earlier resistance.

Huang’s thesis is that every serious economy will build sovereign AI infrastructure. Nvidia wants to be the default supplier for all of them.

Why this matters to India

For India, Nvidia’s quarter isn’t an abstract Wall Street story. It sits directly on top of New Delhi’s own AI ambitions and the compute crunch at home.

1. India is racing to fix its GPU gap

In March 2024, the Union Cabinet approved the IndiaAI Mission with an outlay of about Rs 10,372 crore over five years. A core pillar is IndiaAI Compute Capacity, building a public-private AI infrastructure with 10,000+ GPUs and an AI cloud marketplace that Indian startups, researchers and enterprises can tap into.

2. India is already inside Nvidia’s ecosystem

Nvidia is not a distant player in India. In 2023, it announced deep partnerships with both Reliance Industries and Tata Group:

• With Reliance Jio, Nvidia is helping build up to 2,000 MW of AI data centres and large language models trained on Indian languages.
• With Tata Group, it is co-developing large-scale AI infrastructure and an AI supercomputer based on the GH200 Grace Hopper platform, intended to support thousands of enterprises and startups.

If Nvidia keeps scaling supply and costs fall over time, India benefits. If supply tightens or prices stay high, India’s AI build-out becomes more expensive.

3. Indian IT and startups ride the same wave

From TCS and Infosys to fintech and SaaS unicorns, Indian firms are building AI copilots and tools that rely on Nvidia GPUs through global clouds.

4. Indian investors are already exposed

• Even if they never touch Nvidia stock directly, Indian investors are tied in through:
• Global ETFs and funds tracking the Nasdaq 100 or AI/tech indices.
• Sovereign wealth and pension allocations abroad.

The broader macro impact: AI capex has added about 0.5 percentage points to US GDP growth in early 2025, according to Pantheon Macroeconomics, and US growth feeds back into exports, risk appetite and capital flows to emerging markets like India.

Nvidia’s earnings are not just a US tech story; they’re an input into India’s AI mission, data centre plans, IT strategy and even retail portfolios.