Greenly: How Sustainable Can ChatGPT and DeepSeek Really Be?
As generative AI accelerates, so does its environmental cost.
A study conducted by Greenly, a specialist in enterprise carbon accounting, has compared the sustainability performance of two global AI platforms, OpenAI’s ChatGPT-4 and DeepSeek, a Chinese AI-powered chatbot.
The study raises urgent questions about the climate impact and sustainability of these next-generation AI models.
The high carbon cost of smarter AI
Generative AI, particularly large language models (LLMs), demand immense computing power.
Training and running these systems requires vast amounts of electricity and water, generating carbon emissions and contributing to mounting electronic waste.
The impact is especially evident in models like ChatGPT-4, which has 1.8 trillion parameters, 20 times more than its predecessor.
This evidence proves that as complexity grows, so does its climate footprint.
In a hypothetical business case where an organisation employs ChatGPT-4 to respond to one million emails each month, Greenly found that AI could generate 7,138 tCO₂e annually – the equivalent of 4,300 round-trip flights between Paris and New York.
A single text-based request consumes as much energy as charging a smartphone to 16% according to research from Carnegie Mellon University and Hugging Face.
Even basic and quick use of generative AI quickly adds up.
Under the same scenario, routine annual use would result in 514 tCO₂e.
Emissions rise further with more energy-intensive tools, the study found that the use of text-to-image tools like DALL-E, emit 60 times more CO₂e than generating text.
Is DeepSeek a cleaner competitor?
China’s DeepSeek offers a potential path to lower-impact AI.
This generative AI model uses a Mixture-of-Experts (MoE) architecture, activating only the relevant sub-models per task – significantly reducing the computing power needed.
The model was trained using just 2,000 NVIDIA H800 chips, compared to ChatGPT-4’s 25,000 and Meta Llama 3.1’s 16,000.
These H800 chips are also less energy-intensive.
Overall, DeepSeek requires a tenth of the GPU hours used by Meta’s model, lowering its carbon footprint, reducing server usage and decreasing water demand for cooling.
Despite this, Greenly cautions that such gains might be fleeting, with AI usage surging globally, efficiency improvements could be outpaced by sheer volume.
“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.”
Regulating AI’s emission output
As AI adoption scales, regulators are stepping in to set ethical and sustainability boundaries.
The European Union’s landmark AI Act is one of the most recent to do just that.
“AI has the potential to change the way we work and live and promises enormous benefits for citizens, our society and the European economy,” explains 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.”
Despite the negative output, there are signs of progress.
AI is being harnessed to accelerate decarbonisation, improve energy efficiency and support sustainable development goals.
If applied strategically, it could help reduce global emissions by 1.5-4% by 2030.
Energy-efficient design, renewable-powered data centres, edge computing and open-source model reuse are among the most promising strategies to reduce the sector’s footprint.
“This act marks a major milestone in Europe's leadership in trustworthy AI,” comments 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.”
While DeepSeek signals a promising shift toward greener design, the broader industry must also align innovation with environmental responsibility.
Ultimately, the path forward is clear, performance gains cannot come at the planet’s expense.
A sustainable AI future is possible, if energy efficiency, transparency and regulation progresses as fast as the technology itself.
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