The much-anticipated release of OpenAI’s GPT-5 has brought to light a significant and troubling issue: its potentially massive energy consumption. As OpenAI remains silent on the matter, experts are sounding the alarm. They argue that the model’s enhanced capabilities, from website creation to solving PhD-level problems, are linked to a steep and unprecedented environmental cost. This lack of transparency from a leader in the AI space is forcing a difficult conversation about the industry’s commitment to sustainability.
A key finding from a study by the University of Rhode Island’s AI lab illustrates the gravity of the situation. Researchers discovered that a single medium-length response of about 1,000 tokens from GPT-5 can consume an average of 18 watt-hours. This marks a dramatic increase from earlier models. To put that figure in context, 18 watt-hours is enough energy to power an incandescent light bulb for 18 minutes. Given that a service like ChatGPT handles billions of requests daily, the cumulative energy consumption could be staggering, potentially reaching the daily electricity demand of millions of homes.
The surge in energy use is directly tied to the model’s increased size and complexity. Experts believe GPT-5 is significantly larger than its predecessors, with a greater number of parameters. This aligns with research from the French AI company Mistral, which found a strong correlation between a model’s size and its energy consumption. The study concluded that a model ten times larger will have an impact that is an order of magnitude greater. This principle appears to be holding true for GPT-5, with some experts suggesting its resource use could be “orders of magnitude higher” than even GPT-3.
Further complicating the issue is the new model’s architecture. While it does use a “mixture-of-experts” system to improve efficiency, its advanced reasoning capabilities and ability to handle video and images likely counteract these gains. The “reasoning mode,” which involves the model computing for a longer time before generating a response, could make its energy footprint several times greater than text-only operations. This combination of size, complexity, and advanced features paints a clear picture of an AI system with a massive appetite for power, leading to urgent calls for greater transparency from OpenAI and the broader AI industry.
