Measure AI model carbon footprint with Ecologits.ai methodology

This template provides a straightforward technique to measure and raise awareness about the environmental impact of your AI automations.

By adding a simple calculation step to your workflow, you can estimate the carbon footprint (in grams of CO₂ equivalent) generated by each call to a Large Language Model.

Based on the open methodology from Ecologits.ai, this workflow empowers you to build more responsible AI applications. You can use the calculated footprint to inform your users, track your organization's impact, or simply be more mindful of the resources your workflows consume.

Who is this for?

Environmentally-conscious developers: Build AI-powered applications with an awareness of their ecological impact. Businesses and organizations: Track and report on the carbon footprint of your AI usage as part of your sustainability goals. Any n8n user using AI: A simple and powerful snippet that can be added to almost any AI workflow to make its invisible environmental costs visible. Educators and advocates: Use this as a practical tool to demonstrate and discuss the real-world impact of AI technologies.

What problem does this solve?

Makes the abstract tangible: The environmental cost of a single AI call is often overlooked. This workflow translates it into a concrete, measurable number (grams of CO₂e). Promotes responsible AI development: Encourages builders to consider the efficiency of their prompts and models by showing the direct impact of the generated output. Provides a standardized starting point: Offers a simple, transparent, and extensible method for carbon accounting in your AI workflows, based on a credible, open-source methodology. Facilitates transparent communication: Gives you the data needed to transparently communicate the impact of your AI features to stakeholders and users.

How it works