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Artificial Intelligence
Rolling cost of AI Model Capabilities
The cheapest token basket at each ECI score, grouped by model release date.
Methodology
Assumptions
The chart uses Epoch AI's ECI scores and input and output token prices from the November 9, 2026 snapshot.[^1] It includes 195 distinct model versions with a score, release date, and both prices. Duplicate model/date/score/price rows are counted once. Different dated or priced versions remain eligible.
A token basket contains 750,000 input tokens and 250,000 output tokens. Prices are held at snapshot values across release dates, including retired endpoints; the colors do not reconstruct historical prices. The basket standardizes prices rather than estimating the tokens a task needs.
Formulas and methods
basket_cost = 0.75 × input_price + 0.25 × output_price
cheapest(date, ECI) = min basket_cost among released models with score ≥ ECIFor each release date and each distinct eligible ECI threshold, select the cheapest qualifying model available by that date. The upper edge is the best available ECI, and blank space means no priced model qualifies. The display spans ECI 110–170 and uses no annual bins. Colors use a logarithmic price scale from $0.03 to $100; values outside that range use the nearest endpoint color.
The hover detail also gives a modeled METR TH1.1 80% task horizon, not a measured horizon for that ECI level. Fit the log of METR p80 hours to ECI for 20 matched models using the tracker's version matches.[^2][^3]
ln(p80_hours) = -22.20441287 + 0.14432844 × ECI
n = 20; R² = 0.970768Walkthrough
Calculate the basket cost for every eligible row. At a selected date and target, such as ECI 150, discard models not yet released and those below ECI 150, then take the lowest remaining basket cost. Repeat at every release date and threshold. The hover's optional time estimate at ECI 150 is exp(-22.20441287 + 0.14432844 × 150) = 0.574 hours, about 34 minutes.
Notes
Missing prices and scores are excluded. Real costs may differ with provider, context length, cache or batch discounts, tool fees, and tokens used. The displayed ECI and cheapest price are based on the snapshot; their accuracy depends on the source scores and listed prices.
The hover's ECI-to-time fit has residual standard deviation 0.3128 log hours, roughly a 1.37× scatter factor. The matched scores span ECI 121.87–157.82, so hover estimates outside that range extrapolate. Model matching, benchmark scores, scaffolds, and METR sampling add uncertainty; the scatter is not a full prediction interval. METR cautions that horizons above 16 hours are unreliable with its current task suite.[^2]
The downloadable package contains the frozen source, priced rows, calibration pairs, and script. Run python3 script.py to reproduce the chart data with Python 3.11 or newer; the upstream ECI and METR experiments are not reproduced.