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20242026
most citedCarbon Footprint Evaluation of Code Generation through LLM as a Service

1 citations · 2 across the 5 of their papers we have counts for

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cs.LG2026

From Tokens to Watt-hours: Analytical Energy Estimation for LLM Inference on Modern GPUs

Tina Vartziotis, Rodopi Kosteli, Elli Vartziotis +5

The operational energy consumption of large language model (LLM) inference is becoming an increasingly important component of the environmental footprint of deployed AI systems. Ho…