Will GPU Futures Ever Work?
The case for financializing compute runs straight into benchmarks, refresh cycles, and cartel dynamics that could kill the market before it begins
In my last post, I discussed why a futures market for GPU compute may develop. I argued that if a futures market for GPU compute does develop, it would transform AI infrastructure finance, allowing data center builders to hedge costs and lower their cost of capital. In this post, I look at the obstacles that such a market would have to overcome. And they’re significant.
Since people want definite answers more than they want speculation, I will cut this short for you, if that’s your interest: I don’t know what will happen. A market for GPU futures may develop or it may not. Much will turn on hyperscalers’ decisions. If they choose to participate in a futures market, because doing so will lower their cost of capital for infra buildouts, then the market might thrive. If their AI-associated revenues scale as quickly as many assume they will, the hyperscalers might see no need to seek cheaper capital for their AI infra buildout.
An important note: the obstacles laid out below are numerous and seem significant. That said, there are reasons to be optimistic that a futures market for GPU compute will work, which will be the subject of my next post.
What’s the biggest risk?
Index failure. Futures need a trusted benchnark for spot prices. Corn has bushels, oil has WTI and Brent. GPUs? Nothing. Prices today are opaque, wrapped in bundles (compute + storage + networking), subject to discounting and waitlists. Without a credible index, settlement is a nightmare.
The Trump Administration’s AI Action Plan calls for the development of a spot and forward market in GPU compute, and those are necessary, but not sufficient, precursors to a futures market. It is important to note, though, that the AI Action Plan is an advisory document, not an executive order.
If no transparent benchmark emerges, the market can’t launch. Or worse, it launches and gets gamed into oblivion. If there is no neutral, auditable index with enough reported volume to resist manipulation, the market will die.
Doesn’t concentration make it worse?
Yes. Corn has thousands of farmers. Oil has hundreds of producers. GPUs have Nvidia and a handful of hyperscalers. That’s a cartel, not a market. If three or four players can influence the curve, hedgers and speculators won’t trust it. Liquidity evaporates. If too few independent sellers exist to provide real short-side depth, the market will die.
What about hardware refresh cycles?
Futures work when the underlying is stable. One barrel of oil is the same as the next. GPUs, on the other hand, mutate every 18-24 months. Contracts tied to H100s get orphaned when B100s arrive.
This is why I suggest that the underlying ought to be a standardized amount of compute, not a specific GPU. But even if you abstract the underlying to compute you need to design a spec that withstands market scrutiny. If you make the underlying a specific GPU, then basis risk explodes across chip generations.
Without a spec freeze (for example, a benchmark or throughput metric), liquidity fragments. If the benchmark can’t straddle GPU refresh cycles without becomong obsolete, then the market will die.
Can’t inference just move to the edge?
Yes, and some of it will. Futures thrive in opex markets, where costs recur. If inferene shifts to devices such as phones, laptops, and cars, compute becomes capex, bundled into the purchase price, which is not hedgeable. If too much inference migrates to the edge, the hedgeable surface shrinks. No artery of cloud demand means no futures curve. If cloud inference’s share falls below the level needed to sustain liquidity and volatility, the market will die.
Isn’t settlement itself messy?
Very. GPU contracts aren’t simply hours of compute. They vary by:
firm vs interruptible access,
latency and throughput guarantees,
regional delivery points.
If settlement standards aren’t bulletproof, the first few disputes will kill trust. Not trust means no liquidity. If arbitration shows the contracts don’t map to enforceable delivery, then the market will die.
What about regulators?
This is a wild card. GPUs aren’t corn or oil, but rather dual-use strategic assets. On the one hand, yes, the Trump Administration’s AI Action Plan makes reference to some precursors of a futures market, specifically, spot and forward markets. However, as noted earlier, the AI Action Plan is an advisory document, not an executive order.
Washington, Brussels, and Beijing all view GPUs as national security checkpoints. Regulators could block an open futures market on national security grounds. No CFTC/SEC approval, no CME listing. If export control enforecement collides with the neutrality required for global futures, then the market dies.
Could speculators blow it up?
Yes. Futures are leveraged. Thin spot markets plus leverage equals volatility. One export control shock or supply squeeze could cause margin call cascades. If early blow ups scare hedgers away, the market will never recover. If the first few squeezes wipe out liquidity providers, the market will die.
Is there a simple alternative?
Absolutely. The competition isn’t simply no futures. It’s other financialization tools:
Long-term cloud contracts securitized by banks,
OEM-backed notes tied to device shipments,
ETFs on GPU-cloud providers.
If those instruments solve hedging faster and cleaner, GPU futures never reach critical mass. If securitized forwards outcompete futures before the first contract hits scale, then the market will die before it is born.
Aren’t futures supposed to converge to spot?
Yes. Convergence is the acid test. If futures can’t reliably settle at spot, the market collapses. In GPUs, spot prices are thin, fragmented, and cornerable. Without credible deliverable supply, convergence breaks. This invites squeezes, fails to hedge, and discredits the curve. If convergence fails in the first few expiries, the market will die.
Could benchmarks themselves be gamed?
Absolutely. Goodhart’s Law looms large. Any standardized throughput test will be optimized for, rather than correlated with real workloads. Providers can inflate benchmark scores with driver tweaks, quantization tricks, or pinned kernels. Hedgers discover they’ve hedged a benchmark, not their P&L. If benchmark gaming drives a wedge between contract performance and actual inference costs, the market will die.
Aren’t inference tokens themselves non-fungible?
Yes. Tokenization differs across models and vendors. Even the same model can change tokenization across versions. A million tokens isn’t invariant. Without a stable unit of account, the curve is untradeable If participants can’t agree on a fungible measure of output, the market will die.
What about software shocks?
Software can collapse demand overnight: quantization, speculative decoding, KV-cache tricks, MoE routing, compiler optimizations. These can halve the required compute per token in a quarter. Futures assume stable demand for compute. If software cuts usage dramatically, hedges fail. If exogenous software shocks repeatedly break the correlation between workload demand and the futures curve, the market will die.
Is compute really a standalone commodity?
Not exactly. GPUs don’t run in isolation. Compute depends on:
power (availability, cost, curtailment risk),
networking (latency, bandwidth),
cooling and real estate.
If contracts don’t price these co-factors, you embed multi-commodity basis risk. If power and network shocks overwhelm the GPU signal, the market will die.
Where do shorts come from?
Futures need natural commercial shorts to provide depth. Farmers sell forward crops. Oil producers sell forward barrels. For GPUs, the natural shorts would be hyperscalers and cloud providers, but they prefer bilateral long-term agreements that lock in customers.
If commercial shorts avoid the exchange, the book is spec-vs-spec, fragile and thin. If no natural sellers appear to balance buyers, the market will die.
Could jurisdiction fragment the market?
Yes. US (CFTC/SEC), EU (MiFID II/EMIR), UK, Singapore, and China will each regulate differently. Add export controls on top, and liquidity may fracture along legal borders. Without harmonized global rules, the market splinters into regional niches. If regulatory fragmentation prevents a deep, unified curve, the market will die.
What about clearinghouses?
Clearing members may also be capacity providers. Stress events hit both operational revenues and margin capacity. Wrong way risk undermines the system. If clearing plumbing isn’t robust, liquidity disappears in stress. If wrong way risk wipes out clearing members during a squeeze, the market will die.
Could antitrust kill it?
Yes. A public curve cold act as a signalling device among hyperscalers. Legal teams will resist anything that looks like price coordination. If antritrust scrutiny mounts, big players will stay away. If futures are viewed as collusion rather than hedging, the market will die.
Is substitution a problem?
Yes. If contracts are written on Tier-1 inference throughput, but workloads shift to TPUs or ASICs, the economic reference good changes. Futures designed for GPUs may decouple from the true marginal compute source. If substitution drains liquidity away from GPU-based hedges, then the market dies.
Won’t there be too many grades?
Almost certainly. Latency (p50 vs p95), memory size, interconnect topology, virtualization slice size: all beg for differentials. Too may grades dilutes liquidity. Without simplicity, the market fragments. If grade explosion overwhelms standardization, then the market dies.
Is compute really a commodity?
Maybe not. GPU time is more like an option on capacity conditioned by queue time, quality of sevice, and regulatory constraints. It’s not a barrel of oil. If the underlying isn’t fungible, futures fail. If the contract is revealed to be an option in disguise, not a commodity, the market will die.
Bottom line?
GPU futures are fragile. To work, the market would need:
A neutral, auditable benchmark,
enough inference left in the cloud,
regulatory green lights,
credible convergence,
commercial shorts with real depth,
tolerance for refresh cycles and software shocks.
If those conditions fail, the dream dies. Financialization won’t disappear, but it will operate with different products: securitized forward strips, OEM-backed notes, cloud contract ETFs, bilateral swaps.
Either way, the future of compute finance isn’t guaranteed by Chicago commodities traders. It will be decided in Cupertino, Seattle and Shenzhen by engineers and hardware designers whose choices ripple into the financial system.
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Arrow and Debreu posited the idea of complete markets, where every state of the world could be traded. https://en.wikipedia.org/wiki/Complete_market That's an aspiration, not a possibility.
But enough states can be approximated that we benefit from the widest "wisdom of crowds" in history.
Your idea of compute vs. chips has merit, but will face the same challenge as mortgage backed securities, 50 years ago. With MBS, it immediately ran into "cheapest to deliver." That means the lowest value collateral always appeared, no matter how detailed the definitions.
For chips, we should discuss better metrics/ Best we can do is minimize the variance and structure offsets.