The raw materials of AI
What a unit of compute, a unit of memory and a unit of energy actually cost — split into CAPEX and OPEX, tracked from public sources.
There is no single price for "AI". There is a price for a TFLOP, for a gigabyte of memory, for a GPU-hour and for a megawatt-hour — and those four move for different reasons. This dashboard tracks each of them separately, from sources anyone can audit.
GPU-hour, H100
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Awaiting the first run with the ComputePrices key configured.
Compute, BF16
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Awaiting the first run with the ComputePrices key configured.
Henry Hub gas
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Awaiting the first run with the EIA key configured.
US industrial power
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Awaiting the first run with the EIA key configured.
Market — what it costs today
Daily prices. A GPU-hour and a gas contract are the two AI inputs with a real, observable, moving market price.
GPU rental price
Median on-demand quote across cloud marketplaces, USD per GPU-hour
Cost of compute
USD per PFLOP-hour — the rental price divided by the accelerator's dense BF16 throughput, which is what makes a consumer card and a datacentre module comparable
Natural gas, Henry Hub spot
USD per million BTU, daily — the marginal fuel that sets the marginal power price in most US markets
History — the long curve
The secular decline in the capital cost of compute, and the twenty-year record of the energy that runs it.
Capital cost of compute at launch
USD per TFLOP/s of dense BF16 throughput, at each accelerator's release price
Capital cost of compute at launch, FP32
USD per TFLOP/s of FP32 single precision, at each accelerator's release price — the older, non-tensor measure, which is the only one the pre-2017 hardware reports and so the only one that reaches back that far
Never compared against the BF16 chart above: the two measure different silicon paths, and a ratio between them is meaningless. · Epoch AI — Machine Learning Hardware (CC BY)
Capital cost of memory at launch
USD per GB of on-package memory, at each accelerator's release price
Energy efficiency at launch
Dense BF16 TFLOP/s per watt of TDP — the hinge between the CAPEX you buy and the OPEX you then pay
US retail electricity price
US cents per kWh, monthly average by end-use sector and state
Natural gas, monthly since 1997
USD per million BTU, monthly average of the Henry Hub spot price
Semiconductor producer prices
US producer price index for semiconductor and related device manufacturing — the closest free proxy for what the supply chain charges
How to read this
- Dense throughput, never sparsity
- Every TFLOP figure is dense BF16/FP16. Vendors often quote a doubled number that assumes 2:4 structured sparsity; mixing the two conventions would silently halve the cost per TFLOP of newer parts.
- A launch price is not a market price
- Datacentre accelerators have no public list price — they are sold on contract. Those figures are the best public estimates, and they describe the moment of launch, not what the same silicon costs today.
- Rental is the only observable price
- A GPU-hour is transacted continuously and quoted publicly, which makes it the one genuine market price for AI compute. It bundles capital, power, cooling and margin — that is a feature for a cost dashboard, and a caveat for a hardware comparison.
- The history accumulates from here
- Snapshot sources publish today and nothing else, and no one backfills them for free. Each scheduled run commits one dated observation, so the archive is built forward rather than bought.
- Energy prices are averages, not your bill
- Retail sector averages are published; the power purchase agreements that actually supply large data centres are private. Virginia and Texas are broken out because they carry the largest data-centre loads in the US.
Sources
| Source | Used for | Licence |
|---|---|---|
| Epoch AI — Data on Machine Learning Hardware | Accelerator release prices, throughput, memory and TDP | CC BY 4.0 |
| ComputePrices.com | Cloud GPU rental quotes | Public API |
| U.S. Energy Information Administration | Henry Hub gas price, retail electricity prices | Public domain |
| FRED — Federal Reserve Bank of St. Louis | Producer price indices, redundant energy series | Attribution requested |