You read the headlines stating that GenAI is a true energy hog? Still questioning what your personal use of AI means in terms of energy consumption? Here is your answer:
Let’s proceed, then, with two types of users:
A conservative user: Uses a model that has an energy use of 2 mWh per token and that leans towards 200 tokens on average per response. The user performs 10 queries per day.
A heavy user: Uses a model that has an energy use of 9 mWh per token and that has longer responses of on average 1000 tokens. The user performs 500 queries per day.
With the numbers found above, the conservative user would have an energy footprint of 4 Wh per day, from their use of LLMs. The heavy user, on the other hand, will have a footprint of 4.5 kWh per day. 4 Wh is less than an efficient LED bulb will use in an hour, while 4.5 kWh is about the amount of energy my panel heater uses to keep my bedroom at 22 °C on a typical winter day. (I live in Norway.) The average data center uses 1.7 liters of water per kWh of energy consumed [2], which means the conservative user spends an extra 7 mL of water a day on their LLM use, while the heavy user spends 7.6 L — about the minutely water consumption of an efficient shower.
