This repository contains the code used to model Bitcoin mining profitability as described in "Minting Money With Megawatts", an article which appeared as a cover feature of the Proceedings of the IEEE | Vol. 104, No. 9, September 2016.
Python 3
Start with the notebook MiningProfitability.ipynb at:
https://github.com/sweyn/bitcoin-mining-profitability/blob/master/MiningProfitability.ipynb
All reference parameters were refreshed to May 2026 market and industry data. With current inputs — BTC at $78K, network hashrate at 960 EH/s, Bitmain S21 XP hardware at 13.5 J/TH, competitive electricity at $0.055/kWh, PUE 1.10, and 95% utilization — the model places the optimal total hashrate h* ≈ 947 EH/s, within ~1% of the observed network. This near-exact match reflects competitive equilibrium: miners have entered until marginal profit approaches zero, exactly as the model predicts.
The model's functional form and core insight have held up well over a decade. Its principal limitation is that it is static and deterministic — it gives a point-in-time answer in a market where BTC price, fees, and hashrate are highly volatile. At current conditions h* and h₀ are within 1% of each other, meaning small changes in any input flip the profitability conclusion. A probabilistic extension (e.g. Monte Carlo over price and hashrate scenarios) would be the most valuable next step.
- docs/claude-review.md — Full model review following May 2026 parameter refresh
- docs/market-data-update-summary.md — Summary of all parameter changes from 2016 to May 2026 values, with sources
- docs/extrema-check.md — Analytical derivation of h*, h_CAP, and h_BE with numerical verification
Content provided under a Creative Commons Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) (c)2013-2026.
Thanks to Agust Valfells, Sigurdur Johannesson and Stephen Harrington. Plots made with Matplotlib.