Energy, Efficiency, and Sustainability in LLMs, RAG, and Agent Architectures

Yash Agrawal

Energy, Efficiency, and Sustainability in LLMs, RAG, and Agent Architectures

Author(s)	Yash Agrawal
Country	United States
Abstract	Artificial Intelligence now underpins consumer applications, enterprise systems, and national infrastructure through Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents. Their rapid adoption, however, raises concerns over energy use, carbon emissions, and environmental impact. This review synthesizes scattered research on the sustainability challenges of these three paradigms and proposes a comparative framework that highlights both inefficiencies and opportunities for greener design. We examine (i) the compute and carbon costs of training and inference, (ii) RAG’s potential as a lower-impact alternative to retraining, (iii) the energy overhead of agent orchestration, and (iv) emerging eco-efficiency benchmarks. We conclude with design patterns, policy directions, and future research priorities for aligning AI innovation with sustainable computing.
Keywords	Retrieval-Augmented Generation (RAG), sustainable AI, carbon footprint, green computing, eco-benchmarks, hybrid inference, energy-aware orchestration, hardware-software co-design, carbon-aware scheduling, federated RAG, responsible AI, sustainable architecture, AI lifecycle emissions.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 5, Array 2025
Published On	2025-05-09
Cite This	Energy, Efficiency, and Sustainability in LLMs, RAG, and Agent Architectures - Yash Agrawal - IJTAS Volume 16, Issue 5, Array 2025.

View / Download PDF File

About IJTAS Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us	Message on WhatsApp	+91-9687-182-185	editor@ijtas.com

International Journal of Technology and Applied Science

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Energy, Efficiency, and Sustainability in LLMs, RAG, and Agent Architectures

Share this