Evaluating and Comparing LLM Models for CO2 Footprint and Sustainable Green AI
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Science and Information Technology | United States of America | Volume 14 Issue 3, March 2025 | Popularity: 4.8 / 10


     

Evaluating and Comparing LLM Models for CO2 Footprint and Sustainable Green AI

Gaurav Sharma


Abstract: Large Language Models (LLMs) have significantly advanced artificial intelligence applications across various domains. However, these developments come at environmental cost in terms of carbon emissions, energy consumption, and water usage for cooling data centers. This paper evaluates and compares popular LLMs based on their sustainability and carbon footprint, analyzing key factors such as training and computing CO2 emissions, inference emissions, energy consumption, and water usage. We also discuss concerns and strategies for optimizing AI systems to reduce their environmental impact, emphasizing the need for responsible and sustainable AI development.


Keywords: Artificial Intelligence, Green AI, AI Co2 footprint, Sustainable AI, LLM (Large Language Models), Global Impact


Edition: Volume 14 Issue 3, March 2025


Pages: 1242 - 1246


DOI: https://www.doi.org/10.21275/SR25304105212


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Gaurav Sharma, "Evaluating and Comparing LLM Models for CO2 Footprint and Sustainable Green AI", International Journal of Science and Research (IJSR), Volume 14 Issue 3, March 2025, pp. 1242-1246, https://www.ijsr.net/getabstract.php?paperid=SR25304105212, DOI: https://www.doi.org/10.21275/SR25304105212

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