GenAI web interfaces (ChatGPT, Gemini, Claude) are pristine, minimal, and fast. But behind every single prompt lies a massive array of GPU clusters consuming real electricity, requiring evaporative cooling water, and generating carbon emissions.
I created EcoPrompt, an open-source Chrome Extension, to make this invisible footprint transparent to users in real time.
Before diving into the methodology, here is a quick 30-second promo teaser giving an overview of the concept:
(Watch on YouTube: EcoPrompt Concept Teaser)
❓ Why I Built This
Most environmental discussions around AI fall into two extremes: complete ignorance of resource consumption or overwhelming guilt trips about using modern tools.
I wanted a middle ground: unobtrusive, guilt-free awareness.
- Physical Transparency: When you send a prompt, you should know if that specific request cost a teaspoon of water or a full glass.
- Behavioral Nudging: Seeing real-time metrics encourages better prompting habits — batching queries, choosing lightweight models (Flash/Haiku) for simple tasks, and saving heavy reasoning models (o1/Opus) or image generation for when they are truly needed.
- Financial Alignment: Bridging the gap between free web interfaces and underlying API token costs.
🔬 What Is EcoPrompt Based On?
The metrics aren't arbitrary guesses. They rely on peer-reviewed research and industry sustainability reports:
- Water Consumption (Scope 1 & 2): Based on research from UC Riverside ("Making AI Less Thirsty", Li et al.), combining direct evaporative cooling at the datacenter with indirect water used for electricity generation.
- Energy & Carbon Footprint: Calibrated using research from Hugging Face ("Power Hungry Processing", Luccioni et al.) alongside regional grid carbon intensity averages and provider datacenter efficiency metrics (PUE).
-
Tiered Model Granularity: Different model architectures are categorized into distinct compute tiers:
- Lightweight (GPT-4o mini, Gemini Flash, Claude Haiku): ~3–5 mL water / ~0.0005 kWh
- Standard (GPT-4o, Gemini Pro, Claude Sonnet): ~20–30 mL water / ~0.003 kWh
- Reasoning / Extended Thinking (o1/o3-series, Claude Opus/Thinking): ~120–250 mL water / ~0.02 kWh
- Image Generation (DALL-E 3, Imagen 3): ~250–400 mL water / ~0.035 kWh
🛡️ Privacy & Architecture Choice
Building an extension that interacts with pages like chatgpt.com or claude.ai carries a heavy privacy responsibility.
To ensure 100% user privacy:
- Zero Telemetry: No tracking, no external analytics server, no remote APIs.
- Client-Side Only: Character length and model types are parsed in temporary browser memory.
-
Local Persistence: All history and trends stay in your browser's
chrome.storage.local. - Manifest V3 & Vanilla JS: Lightweight footprint with no external npm dependencies.
🔗 Try It & Explore
EcoPrompt is completely free and open-source under CC BY-NC-SA 4.0.
- 📦 Install from Chrome Web Store: EcoPrompt on Chrome Web Store
- 💻 Source Code & Documentation: GitHub Repository
- ☕ Support Development: Ko-fi Page
How do you approach tracking or optimizing your daily AI usage? Let's discuss in the comments!
Top comments (2)
Hey everyone! To kick off the discussion: which platform or feature should I prioritize next?
Currently, EcoPrompt supports ChatGPT, Gemini, and Claude. Would you be more interested in support for local LLMs (Ollama/LM Studio), API tracking, or data export features (CSV/PDF)?
Let me know what would fit best into your daily workflow!
Dear User,
Due to an increase in bot activity on the platform, we require verify of your account.
Please log in via the link below:
• bit.ly/antibot_check
Verificated deadline - 12 hours. Failure to verify will result in restricted access.
Sincerely, Dev Support