1 citations · 1 across the 2 of their papers we have counts for
2 papers
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…
cs.CY2025★ 1 cited
Carbon Footprint Evaluation of Code Generation through LLM as a Service
Tina Vartziotis, Maximilian Schmidt, George Dasoulas +7
Due to increased computing use, data centers consume and emit a lot of energy and carbon. These contributions are expected to rise as big data analytics, digitization, and large AI…