Sustained FuturesChangemakers Collective

Upskill

Take it at your own pace.

Prompts and repos from people in the Collective, plus the demos, academies, books, podcasts and research worth your time. Find what fits where you work and who you are, and upvote what is worth copying.

Using AI has an energy, carbon and water cost. Calculators give a quick estimate of your own use, leaderboards compare models before you choose one, and libraries track the footprint of what you build. Most are open-source projects run by researchers.

Estimates the energy, emissions and water use of your conversations with different generative AI models.

Library

EcoLogits

Tracks the energy and environmental impact of generative AI used through APIs, including OpenAI, Anthropic and Mistral AI.

Comparison

compar:IA

French government tool: compare two AI answers blind and see the environmental impact of each. Mostly in French.

How much energy open AI models use per answer, and the trade-offs with speed and quality.

The Green Algorithms carbon calculator, with a version for AI training jobs. From the University of Cambridge.

Calculator

ML CO2 Impact

Estimates the carbon footprint of machine learning work on GPUs, from the makers of CodeCarbon.

Library

CodeCarbon

Python library that tracks the energy and CO2 of code you run, on your own machine or in the cloud.

C

Python package that measures the carbon footprint of training machine learning models.

E

Library

Eco2AI

Python library that tracks CPU and GPU energy and turns it into emissions using your region's grid figures.

AP

Library that monitors the energy use of machine learning programs on CPU and GPU.

Library

ZEUS

Measures and reduces the energy use of deep learning work. Part of the ML.ENERGY project.

Links checked 16 October 2026.