Understanding the Energy Scaling of Large Language Model Inference Across Context Lengths and Attention Architectures

英文标题：Understanding the Energy Scaling of Large Language Model Inference Across Context Lengths and Attention Architectures

arXiv:2608.25096v1 Announce Type: new Abstract: The growing adoption of large language models (LLMs) has raised increasing concerns about the energy consumption and environmental impact of inference. This paper presents a systematic empirical study of decode-phase energy consumption across represen

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