The Token Dollar
Oil is scarce because of war. Tokens are scarce because of physics.
Good morning. It’s the weekend. Pour yourself a cup of coffee and settle in.
Here’s the argument: AI compute may be becoming to the dollar what oil was for the last fifty years.
Oil scarcity is geopolitical. Compute scarcity is industrial. One can ease with diplomacy. The other runs into fabrication limits, memory bottlenecks, packaging constraints, power shortages, and software lock-in.
That distinction matters more than most macro investors realize — especially this week.
The world has more oil than it knows what to do with. It does not have enough tokens.
Brent crude has surged above $100. The Strait of Hormuz is effectively closed. The IEA has described the disruption as the largest in the history of the global oil market, with crude and product export flows from the Gulf reduced by millions of barrels per day. This is what vulnerability looks like when your economic leverage depends on a physical chokepoint that someone else can close. The petrodollar system — the foundation of American financial power for fifty years — is being stress-tested in real time.
Jonathan Ross posted a thread this week arguing that AI compute is replacing oil as the resource that forces the world to transact in dollars. Ross created the Google TPU, founded Groq, and joined NVIDIA through the approximately $20 billion Groq licensing-and-talent deal in late 2025, where he now leads inference architecture. His frame is directionally right but incomplete. He names the destination without mapping the mechanism.
The mechanism is what matters. The Token Dollar thesis is simple: if the world’s most important new industrial input is AI compute, and the chokepoints that produce it are priced in dollars, then rising global demand for compute reinforces dollar demand the way oil once did. The difference is that the compute chokepoint stack is more concentrated than oil ever was, the demand curve is self-reinforcing through Jevons paradox dynamics, and there is no strait that anyone can close.
Oil scarcity is often geopolitical and reversible. Compute scarcity is industrial and slower to relieve. That distinction is about to matter a great deal.
Three things converged this week that pushed me to write this piece. The MLPerf v6.0 results showed the same NVIDIA hardware producing 2.7x more tokens through software alone — confirming that the token cost curve is deflating even faster than the hardware cycle implies. Ross’s thread named the geopolitical implication nobody in macro is framing. And some proprietary data work I’ve been doing on token unit economics keeps pointing to the same conclusion: the dollar-denominated compute supply chain is creating structural demand at a scale that rivals oil.
What the Petrodollar Actually Was
Most people get the petrodollar wrong. It wasn’t a single deal. It was a system.
After Nixon ended dollar-gold convertibility in August 1971, the dollar needed a new anchor. Henry Kissinger and Treasury Secretary William Simon brokered the framework with Saudi Arabia in 1974: the Saudis would price oil in dollars and invest their proceeds in US Treasuries. In exchange, they got military protection and economic partnership. By 1975, all OPEC nations priced oil in dollars.
The result was elegant and self-reinforcing. Because oil traded in dollars, every country on earth needed dollars to fuel its economy. That structural demand allowed the US to run persistent deficits at artificially low borrowing costs — what Valéry Giscard d’Estaing called the “exorbitant privilege,” estimated at $50–100 billion annually in reduced financing costs. Roughly 80% of global oil trade — approximately $3.1 trillion per year — generated continuous dollar demand.
That system is now fraying. The dollar’s share of global foreign exchange reserves has declined from a peak of 72% in 2001 to approximately 57% in Q3 2025. Saudi Treasury holdings rank only 17th globally. Gulf sovereign wealth funds have shifted from Treasuries to equities. Brad Setser, the former Treasury economist, documents that petrodollar flows have “more or less dried up” at current oil prices.
Yet dollar dominance persists through sheer institutional inertia. The BIS 2025 Triennial Survey shows the dollar involved in 89% of all forex transactions. The network effects — deep capital markets, rule of law, unmatched liquidity — remain formidable even as the commodity that once underpinned them weakens.
The question is whether a new commodity is emerging to fill that role.
The Compute Chokepoint Stack
Here’s why the Token Dollar thesis is more than an analogy. The entire AI compute supply chain is denominated in dollars and controlled by American or American-aligned entities. And the concentration is more extreme than oil ever was.
I want to be precise about what “American-controlled” means here — because the obvious objection is that TSMC is Taiwanese and SK Hynix is Korean. That’s true. But the Token Dollar thesis doesn’t require every company to be headquartered in America. It requires every transaction to settle in dollars. And they do. TSMC prices exclusively in USD. SK Hynix sells HBM in dollars. ASML sells EUV systems in dollars. The entire supply chain, regardless of where a company’s headquarters sits, transacts in American currency.
Oil could be drilled in Nigeria, Venezuela, Russia, Saudi Arabia. The production base was geographically distributed even if pricing was dollar-denominated. AI compute has no equivalent distribution. The chokepoint architecture runs through a handful of companies:
NVIDIA holds an estimated 80–92% of the AI accelerator market by revenue. Broadcom controls approximately 60% of the custom ASIC co-design market. TSMC manufactures roughly 90% of the world’s most advanced AI chips. ASML holds a 100% monopoly on EUV lithography — without which advanced fabrication is impossible. SK Hynix and Micron dominate High Bandwidth Memory, with the HBM market projected to reach approximately $55 billion in 2026.
And then there’s the software layer — which has no oil-world equivalent at all.
As I wrote in The Memory Wall: “You can’t separate the silicon from the software from the model architecture.” NVIDIA’s CUDA ecosystem encompasses 4 million developers and 40,000 organizations built over nearly two decades. The integrated stack — CUDA, TensorRT-LLM, Dynamo, the proprietary NVFP4 format — creates switching costs measured in months of engineering time. This is the co-design moat I’ve been documenting across the entire series. Hardware-software co-design doesn’t just make the product better. It makes the dollar dependency structural.
Every GPU sold, every cloud instance rented, every API call made — from Mumbai to Munich to Riyadh — settles in dollars. Not because of a political arrangement like the petrodollar. Because the physics of the supply chain requires it.
CSIS published a paper in December 2025 that named this directly: the compute-dollar system offers comparable strategic advantage to the petrodollar — if the US architects it deliberately.
