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Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights

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学术前沿 5.5 分 — 中等偏上:有一定信息增量和参考价值
原文: cs.AI updates on arXiv.org

评分 5.5 · 来源:cs.AI updates on arXiv.org · 发布于 2026-04-14

评分依据:中等偏上:有一定信息增量和参考价值

Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights

arXiv:2504.06307v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) has led to significant energy consumption and carbon emissions, posing a critical challenge to the sustainability of generative AI technologies. This paper explores the integration of energy-efficient optimization techniques in the deployment of LLMs to address these environmental concerns. We present a case study and framework that demonstrate how strategic quantization and local…