AI’s Energy Toll: Greenly Compares ChatGPT-4 and DeepSeek
As generative AI expands in reach and complexity, so too does its environmental impact.
A study from carbon accounting platform Greenly compares the sustainability profile of two major AI systems – OpenAI’s ChatGPT-4 and Chinese AI-powered chatbot, DeepSeek.
Greenly’s study is shedding light on the urgent need to rethink energy use and environmental cost in artificial intelligence development.
The climate cost of intelligent computing
Building and running large language models (LLMs) such as ChatGPT-4 and DeepSeek requires substantial computing power.
This involves not only high electricity use but also dependence on water for cooling and energy-intensive chip manufacturing.
AI hardware production involves mining rare earth minerals, a process that can result in soil erosion, water contamination and wider pollution.
ChatGPT-4, for example, operates with 1.8 trillion parameters – 20 times more than earlier versions.
With that scale comes a growing carbon footprint.
In a scenario where an organisation relies on ChatGPT-4 to answer one million emails per month, Greenly calculates the yearly emissions at 7,138 tCO₂e – equivalent to 4,300 round-trip flights from Paris to New York.
Even small tasks carry energy costs.
According to research from Carnegie Mellon University and Hugging Face, a single text-based prompt consumes as much energy as charging a smartphone to 16%.
Under routine conditions, the same email use would still produce 514 tCO₂e per year.
Greenly found that text-to-image models like DALL-E produce up to 60 times more CO₂e than standard text generation.
DeepSeek’s alternative approach
Amid concerns about AI’s energy demands, DeepSeek offers a potential way forward.
The Chinese-developed model employs a Mixture-of-Experts (MoE) architecture, meaning it only activates relevant sub-models for each task rather than the entire model.
This drastically reduces the power required per operation.
Whereas ChatGPT-4 was trained using 25,000 NVIDIA GPUs and Meta’s Llama 3.1 used 16,000, DeepSeek used just 2,000 NVIDIA H800 chips.
These chips also draw less power than previous models.
As a result, DeepSeek consumed a tenth of the GPU hours compared to Meta’s model.
This not only brings down its carbon footprint but also lessens the load on servers and reduces water usage needed for cooling.
However, Greenly warns that improved efficiency may not be enough on its own.
“DeepSeek’s emergence has put energy efficiency at the heart of the battle between AI models,” says Alexis Normand, CEO and Co-Founder of Greenly.
“But it remains to be seen if other players will follow this path, or continue to prioritise raw processing power at the expense of the environment.”
Regulation and a route to sustainability
With AI use scaling globally, regulators are stepping in.
The European Union’s AI Act introduces rules to ensure AI growth aligns with human rights, ethics and environmental goals.
“AI has the potential to change the way we work and live and promises enormous benefits for citizens, our society and the European economy,” says Margrethe Vestager, Executive Vice President for a Europe Fit for the Digital Age.
“The European approach to technology puts people first and ensures that everyone’s rights are preserved. With the AI Act, the EU has taken an important step to ensure that AI technology uptake respects EU rules in Europe.”
AI does offer a sustainability upside if used well.
Greenly notes that AI can aid decarbonisation, improve power grid efficiency and support the global sustainability agenda.
Deployed wisely, it could help cut worldwide emissions by 1.5% to 4% by 2030.
Strategies to lower AI’s environmental impact include energy-efficient design, shifting to renewable-powered data centres, leveraging edge computing and encouraging reuse of open-source models.
“This act marks a major milestone in Europe's leadership in trustworthy AI,” says Thierry Breton, Commissioner for Internal Market.
“With the entry into force of the AI Act, European democracy has delivered an effective, proportionate and world-first framework for AI, tackling risks and serving as a launchpad for European AI startups.”
The path ahead requires balance. While DeepSeek offers signs of progress, the wider industry must pursue energy efficiency and transparency alongside innovation.
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