AI Energy Calculator

How much electricity does your AI usage cost the planet? Pick a model, enter your usage, and see the numbers.

Per Query

6.00 Wh

Per Month

18.0 kWh

CO2 / Month

8.8 kg

kWh / Day

0.600 kWh

That's equivalent to...

5.9 min

of passenger flight time per month

42.0 mi

of driving an average car per month

1800 hrs

of a 10W LED bulb per month

Energy per query (all models)

ModelkWh/Queryvs Google Search
GPT-40.010033x
GPT-4o0.006020x
GPT-4o Mini0.00155x
GPT-3.5 Turbo0.00207x
o10.0300100x
Claude Opus 40.011037x
Claude Sonnet 40.005017x
Claude 3.5 Haiku0.00124x
Gemini 2.0 Pro0.005518x
Gemini 2.0 Flash0.00103x
Llama 3.1 405B0.015050x
Llama 3.1 70B0.004013x
Llama 3.1 8B0.00083x
Mistral Large 20.006020x
DeepSeek V30.003512x
DALL-E 30.0500167x
Midjourney v60.0450150x
Stable Diffusion XL0.020067x
Google Search (baseline)0.00031x

Where these numbers come from

Exact energy per query is hard to pin down because inference costs depend on hardware, batch size, datacenter efficiency (PUE), and model optimizations. The numbers here are estimates based on the best publicly available data.

Key sources:

  • IEA "Electricity 2024" report on AI energy consumption
  • De Vries, A. (2023). "The growing energy footprint of artificial intelligence." Joule.
  • Luccioni, A. et al. (2023). "Power Hungry Processing." NeurIPS.
  • SemiAnalysis inference cost estimates
  • Google Environmental Reports (2023, 2024)
  • Epoch AI compute analysis

CO2 calculations use the global average grid carbon intensity of 0.49 kg CO2/kWh (IEA 2023). Your actual carbon footprint depends on where the datacenter is located. A query processed on France's nuclear grid (0.05 kg/kWh) produces 10x less CO2 than the same query on a coal-heavy grid (0.9 kg/kWh).

These numbers will change as hardware gets more efficient and models get optimized. I update them quarterly.