Nvidia Will Keep At Least 70% of AI Data‑Center GPU Revenue

The Market Thinks the King Is Tired

The consensus story is simple: Nvidia had a great run, now the wealth spreads out. Intel, AMD, Micron, Corning, even the ghosts of SanDisk and Western Digital suddenly look like the smart AI trade. Nvidia, the most valuable company on Earth, is merely keeping pace with the Nasdaq while everyone else doubles for sport.

My call: the stock rotation is real, the power shift is not. By the end of 2026, Nvidia still controls at least 70% of global AI data‑center GPU revenue. The share might bleed a little. It does not crack.

If this is a changing of the guard, someone forgot to take the scepter out of Jensen Huang’s hand.

The Forecast: A Scorable Line in the Sand

Let us be specific enough that you can shove this back in my face later. I am betting that when the big market‑share shops, think Omdia, Mercury, IDC, publish their 2026 wrap‑ups, Nvidia’s share of AI data‑center GPU revenue is still at or above 70% globally.

That is revenue share, not units. It is only for GPUs used in data centers for AI, not every gaming card or mystery accelerator edge box. Whatever methodology those firms use today, I am assuming they keep it broadly consistent. If they print 69 point anything, I am wrong. If they print 70 or higher, the king kept the crown.

The Drivers: Lock‑In, Logistics, and Loan Sharking

Start with demand. AI workloads are mutating from cute chatbots into full‑time multimodal goblins that never shut off. Hyperscalers are about to throw roughly $755 billion in capex in 2026 at this problem, basically their entire operating cash flow, and most of that is AI infrastructure. Vendor choices they make now are not six‑month experiments. They are multi‑year, multibillion‑dollar marriage contracts.

Nvidia walked into that wedding with the only suit that fits. CUDA, cuDNN, NCCL, all the messy software and tooling that make giant GPU clusters actually work at scale, are already standard issue. The alternatives, AMD’s ROCm and Intel’s software stack, are catching up. Catching up is not the same as being the default on every major AI research paper, every production LLM stack, and every harried infra team’s mental model of what will not catch fire at 3 a.m.

That is the first reason I think sub‑70% is a reach by 2026: you do not re‑platform the world’s most expensive science project in under two years just because Wall Street discovered Micron again.

The second reason is more awkward. Nvidia is not just selling chips. It is now the most aggressive capital allocator in the AI economy. Over $40 billion in equity and financing commitments this year alone, into suppliers and customers and even a nominal competitor. A $5 billion Intel stake that has already quintupled. Multi‑billion structures with Corning so more fiber and glass gets pulled for Nvidia‑heavy data centers. Rights to pour up to $2.1 billion into IREN, the ex‑crypto miner that rewired itself into an AI landlord.

This is vendor financing with a GPU sticker on it. Nvidia funds your build, you buy Nvidia hardware, and maybe lease some of that compute back to Nvidia itself. Critics compare it to the dot‑com bubble’s worst habits. That is fair. It is also how you make sure the third‑party capacity boom, from IREN to Hut 8 to whatever Blackstone is incubating in an ex‑mall, speaks fluent CUDA.

The Rivals Are Real, The Clock Is Not

If you stare only at tickers, you would think Nvidia is getting outflanked. Intel and AMD are up well over 200% this year. Micron just printed cloud memory revenue of $5.28 billion at 66% gross margin. SanDisk is putting up 250% year‑over‑year growth in data‑center revenue. Corning’s fiber business is on a tear. CNBC hosts have upgraded the AI conversation from “is this real” to “changing of the guard.”

Some of that is true. The AI value chain is broadening. Memory and storage vendors are enjoying what looks like a genuine supercycle in high‑bandwidth memory, NAND, and fat hard drives. The bottlenecks are no longer just GPUs. They are glass, bits, and megawatts.

But bottlenecks moving does not automatically mean GPU share collapsing on a two‑year horizon. It mostly means incremental profit flows sideways. Every extra dollar of margin Micron squeezes out of HBM is a dollar that data‑center operators cannot cheerfully overpay Nvidia for chips. That caps pricing power. It does not instantly gift AMD 20 points of GPU revenue share.

For Nvidia to fall below 70% by 2026 you need a lot to happen very fast. You need AMD and Intel not just to ship competitive accelerators, but to:

• Land multi‑billion, multi‑year hyperscaler contracts at scale, across both training and inference.
• Show up in teardown after teardown of real clusters, not just in slide decks.
• Close most of the software and tooling gap, so switching feels like a hassle, not a career risk.
• Actually have wafers, packaging, and power lined up when the orders arrive.

That is a tall order in any environment. It is taller when Nvidia is helping design the data centers, footing part of the bill, and sending you a nice term sheet if you agree to standardize on its stack.

The Wildcards: Power, Politics, and Private Equity

There are real ways this bet can go wrong.

Power constraints could become so acute that buyers suddenly favor lower‑power or cheaper accelerators, and AMD or Intel leans into that niche faster. Memory or packaging shortages could hit Nvidia’s roadmap hardest, pushing frustrated hyperscalers into the arms of the nearest rival that can actually ship. Regulators could notice that the world’s most valuable company is financing its own buyers and decide that maybe this is not the purest form of competition.

There is also the private‑equity wild card. Giants like Blackstone, Blue Owl, and Ares see a $900 billion non‑hyperscaler data‑center opportunity. They are building fresh, they like optionality, and they like not explaining to LPs why their shiny new AI campus is single‑sourced to one chip vendor. If those platforms choose heterogeneous by default, Nvidia’s incremental share of that build‑out will be more modest.

Still, watch what the ex‑crypto miners are actually doing. IREN is writing off mining rigs, building hundreds of megawatts of AI capacity, signing a $3.4 billion Nvidia contract, and then promising another 5 gigawatts of infrastructure. Hut 8 jumps 35% on a giant Nvidia‑based training center lease. The early non‑hyperscaler wave is not rebelling against Nvidia. It is applying for franchise rights.

Stakes: Who Loses if I Am Right

If Nvidia holds 70% or more of AI data‑center GPU revenue through 2026, the loser is not AMD or Intel, who can still grow nicely from a tiny base. The loser is the story that concentration risk would force a faster shift than technology and logistics allow.

It also means regulators and big buyers spent years complaining about dependency on one supplier, then, when handed hundreds of billions in capex, mostly kept doing what was familiar. It would confirm that the real moat was not just performance, it was institutional cowardice.

If I am wrong and Nvidia ends 2026 in the mid‑60s, it will mean at least one hyperscaler truly swallowed the cost and pain of diversification, private‑equity‑backed data centers refused to be annexed by CUDA, and the vendor‑financing experiment backfired or got muzzled. That is a healthier market and a worse look for my forecasting record.

Until then, I am betting the supposed changing of the guard looks a lot like the same guard, just renting out half the palace at interest.