Practice focus · Energy & Compute
Compute is congealed electricity. Almost none of it is priced that way yet.
The first new major commodity in decades is being financialised in public, and the complex is being assembled out of order — futures listed before benchmarks are governed, indices published before their denominators are measured, credit extended before any of it can be marked. This section follows the stack from the bottom up: what a GPU-hour physically is, where its electricity is priced, who gets to define the benchmark, how paper converts into racks, what the tokens on the other side are worth, and who is financing the whole thing.
Every piece runs on primary data — measured power traces, hourly settlements, contract texts and settlement metadata pulled from the venues themselves — and ships with the tooling to re-run it.
1 · The denominator — what a GPU-hour actually is
Every index, every hedge and every credit structure downstream rests on a measurement nobody publishes: how much energy a GPU-hour consumes, and how many tokens it produces. The work starts here because everything else inherits the error.
The physical layer beneath every economic question in AI, for a markets and risk audience. Serving a model is two different jobs — reading the prompt is a math problem, writing the answer is a data-moving problem — and each phase uses only half the chip you paid for, which is why decode sets the margin of the whole business. Plus the software stack that multiplies token output without buying a chip, one GPU's walk through the cascade to its shutdown floor, and the three relationships that bound a forward curve on something that cannot be stored
Measured H100 workload power against the nameplate-TDP convention: duty factors 0.795–0.880, nameplate overstating device energy 12–21%, facility derates of 73–80%
Measured facility profiles joined to 401,379 hourly DA settlements: the load-weighted price runs up to 9.4% above flat-block, and the premium peaks at 40% utilization — the ramp phase, not saturation
The heat rate of inference measured at 11.6M tokens per GPU-hour from 1,024 vLLM runs joined to NVML traces — the conversion term the whole complex needs and no administrator publishes
2 · The power leg — where the electricity is actually priced
A data center is a load shape before it is anything else. The energy work exists because the compute work needs a fuel leg that is priced hour by hour, not as a flat annual block.
Nodal will clear Compute Desk GPU futures beside its power book and let the two offset. Electricity is 3.5% of a neocloud GPU-hour and monthly compute against Dominion Hub runs −0.19 — and the expected-shortfall engine still nets the pair down by a quarter, because it nets tails rather than fundamentals. With an interactive offset table
Nodal's 168 hourly futures, ElectronX's bounded hours and ICE's TB4 — analysed on three years of ERCOT and PJM settlements, with a 24×24 spread monitor and TB4 tail distributions
430+ risk factors and 470+ contracts across ICE EU/US, NYMEX and Nodal, with positions decomposed into dated factor legs
ICE × NATIVX's COIL index — the first energy-normalized compute futures, stress-tested against 374,550 hourly settlements. What normalization removes as noise, the hourly complex sells back as basis
3 · The index layer — five administrators, no rulebooks
Once compute has a price it needs a benchmark, and a benchmark is a governance object before it is a number. This is where the practice has spent the most time, because it is where the asset class is least finished.
Every benchmark published so far prices the rent; this prototypes the index that prices the whole hour — rent less power at the meter, less space, plus the change in value. It decomposes by unit and by piece of the money and both cuts reconcile to the headline exactly, which is what makes each sub-index a leg someone is long and someone is short. Interactive: move any input and watch both cuts still add up
What a benchmark has to do before a contract can reference it — the six models of administration, the four series nobody publishes, and why the harder deficiency is independence rather than data. Including August's two exceptions: a regulated third-party administrator over Compute Desk's benchmarks, and an open-sourced construction anyone can rerun. With the insurance industry's contributor mutual as the structural precedent, antitrust case included
Transparency is not reproducibility. NATIVX published its whole index engine under Apache-2.0 — the most inspectable compute index in existence — so we cloned it and recomputed from the constituents published beside each value. Ten of thirteen equalled one vendor's list price to the cent, two matched no observation at all, and the checksums hashed nothing. NATIVX shipped a fix six days later: 64 of 64 values now reconcile exactly, and the auditable history that created falsifies its own forward curve by 6.3×
The futures settle on rent, which barely moves; tokens reprice in hours and have no index. C = T·p − r, built from a live endpoint book — with the CFTC's August 19 request for comment read as a specification the token leg mostly passes and the rent leg mostly fails
Who actually holds a floating GPU-hour exposure — read off the filings, the calls and the lender decks. Every balance sheet with a real exposure prices it fixed, no hedger is named anywhere, and the CME filing never says which Silicon Data tier settles it. Compute is running the oil sequence backwards
The Treasury and the AI build-out are selling duration to the same buyers — three crisis paths, four transmission channels, and a 100 MW project run through each, which shows the merchant case dying of rental deflation rather than of rates
The merchant power desk mapped function by function onto an inference lab — a three-leg chain from power to GPU-hour to token with two heat rates in it, only one of which is physics, and the finding that at 0.8% of token revenue the lab's trader hedges absolute dollars and the tail rather than margin
The academy's first brief on compute futures, reviewed: cost-of-carry is dead on arrival, term rentals are contaminated proxies through the physical access wedge, and hedging pressure sets the premium — plus four corrections where the market has moved past the model
The first US compute futures list on NYMEX on October 5 — and the dispersion ladder they must navigate, from 1.4× same-chip variance to a 2.6× tier spread that sits outside the settlement sample
An eleven-product audit of the administrator whose numbers the futures settle against — seven exposures mapped to five participant classes, an honest routing table, and the utilization benchmark nobody publishes
Component-level catalogue of every administrator positioned to bear settlement weight — and the finding that not one publishes a rulebook, IOSCO statement, audit or oversight committee
A fifth administrator, outside the CFTC perimeter, disclosing more of its construction than any of the four inside it — and still not reproducible. Publication answers IOSCO Principle 9, not Principle 11
Kalshi's ladders settle on Ornn OCPI, so a strip of digitals is a discretised distribution — the first continuously published compute term structure, with a $1.23/GPU-hour convenience yield measured against reserved-tier term sheets
Kalshi, Architect, CME × Silicon Data and ICE × Ornn — the race to price the GPU term structure, and how much of it settles on one index family
The six-level hierarchy the rest of the work indexes against: benchmark, grade, region, firmness, tenor, venue
4 · Delivery — where paper becomes racks
A cash-settled contract is a bet on an index. A contract that converts into capacity is forward procurement, and the difference decides whether hedgers show up at all.
Compute Desk's Nodal future and the ComputeConnect exchange-for-physical, from the seller's chair: a neocloud with 1,024 uncontracted B200s walked through the reserved contract, the cleared strip and the EFP, ten classes of buyer, and Nodal Clear's margin and waterfall as the thing that replaces a $104 billion bilateral backlog. With an interactive ledger — the strip matches the reserved contract at about 71% of hours sold at market, and a 30% rally is a $12 million cash call
Also the credit layerThe market-maker's question rather than the product question: after every announced instrument does its job, what exposure is left and who holds it. Eight risks with natural sellers, ten structures ordered by what exists, and five residuals no instrument absorbs — the tenor tail, basis, the jump wing, embedded utilization and correlated credit. Includes the SA-CCR calibration nobody has raised, and the seven observable spreads that price an inventory which cannot be hedged outright
Compute has prices worth watching, not prices you can lean on, size into and exit from. A five-part test for tradability — fungibility, two-way size, transferability, settlement integrity, credit intermediation — run against the exhibits in Liquid Compute's primer, and the finding that the one genuinely executable trade in it is executable because it needs racks and a sales team rather than financial infrastructure. Plus the $5.15 tenor discount decomposed into five strips, only the last of which, about $0.35, any instrument exists to isolate
Architect × Compute Desk's exchange-for-physical network read through the crude, gold, gas and metals precedents, with basis tables and convergence mechanics
Kalshi and Polymarket settle on the same Ornn URL — the first live compute spread with the index basis verified at zero, and still unreadable. Disclosure is necessary and visibly not sufficient
Also in Predictive Markets5 · The product leg — the tokens compute actually produces
GPU-hours are the input. Tokens are the output, and they have their own price, their own volatility and — so far — no settlement-grade index. This is the newest thread and the one with the most open ground.
Where the Flop Network actually sits, read from a v0.1 teaser and a manifesto rather than from the token. Every benchmark and contract announced this year settles on the rented hour; Flop prices the delivered floating-point operation instead, which puts it one node to the right of all of them and makes its competitors the inference routers rather than the index providers. A work market is not a capacity market: all the utilisation risk lands on the miner. Against it — the hardware guidance attracts the depreciated tail, a FLOP is not a FLOP once decode is memory-bound, and a subsidised price in a floating numeraire is not a signal
The demand-side companion. Every announced compute derivative settles on rent, but the buyer whose bill justifies the market pays for tokens, not GPU-hours — so it has no r to hedge. Its spend is S = p·h·N against the producer's C = T·p − r, which inverts the sign on price and introduces a heat rate set by prompt design rather than physics. Price is the small term and falling; quantity is the risk and rising, correlated across every buyer on the day a model generation ships
A designed-but-unsited token futures contract tested against the venue that could settle it: 56 live quotes, a 7× spread on identical open weights, and the four places the index breaks
Fixed subscriptions downstream, floating token costs upstream — a commodity retailer's book. Token forwards versus GPU futures, with the efficiency curve as the unhedgeable basis between the units
6 · The credit layer — who finances the racks
Compute became an asset class the moment lenders started underwriting it — and in August 2026 the largest alternative-asset managers in the world agreed it was underwritable collateral. This is the applied end of everything above: the index work becomes a validation program, and the measurement work becomes a collateral curve.
Where compute credit actually stands: $48B of chip loans, $155B of landlord vehicles and $61B of building-backed bonds, with a rated ledger showing that the same borrower on the same hardware pays 2.25 points over the benchmark behind a Meta contract and 5.50 when the loan outlasts its contracts. The counterparty opens the grade and the structure sets the notch. Plus the Federal Reserve paper on the multi-borrower pool nobody has issued, which finds the senior slice is the piece most understated when recovery falls in the same conditions that cause default — and the four things missing before a pool is buildable: no public default, no recovery print, no hedge requirement, no loan-to-value test against an index
The BIS models the build-out as a contest rather than a mania — so the racers won't hedge, the demand migrates to whoever financed them, and it lands in a market roughly 120× too small
Six MOUs to mobilize over $500B into vehicles issuing debt secured by GPU compute — and the only quantified NVIDIA exposure in the announcement is a written put on the depreciation of its own hardware
Settlement mechanism, standardization tier and index validation for specialty compute lenders — five checks that require no administrator cooperation, with the power leg grounded in ERCOT and Dominion
Two structures for the unrated side of the market, running the same pipe in opposite directions — exposure ladders on both sides and the hedge program each would need
7 · Synthesis — driving the whole complex
The workbench that connects every layer above: chips to megawatts to basis, with the options, margin and take-or-pay economics attached.
Where this connects
The threads that run out of this one.
The compute forward curve was extracted from event-contract ladders. The venue and settlement questions are the same questions, asked of a different underlying.
Digital & derivativesCompute credit is being financed on the same tokenized collateral rails the settlement work tracks — and margined under the same perpetual-futures mechanics.
Market structure radarIndex launches, contract filings and regulatory shifts across the compute and power complex, tracked continuously and sourced to primary filings.