#environmental-impact2 articles

2 articles

AINeutralarXiv – CS AI · 5h ago1

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SEALing the Gap: A Reference Framework for LLM Inference Carbon Estimation via Multi-Benchmark Driven Embodiment

Researchers have developed SEAL, a reference framework for measuring carbon emissions from Large Language Model inference at the prompt level. The framework addresses the growing sustainability concerns as LLM inference emissions are rapidly surpassing training emissions due to massive usage volumes.

AINeutralarXiv – CS AI · 5h ago1

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The Price of Prompting: Profiling Energy Use in Large Language Models Inference

Researchers introduce MELODI, a framework for monitoring energy consumption during large language model inference, revealing substantial disparities in energy efficiency across different deployment scenarios. The study creates a comprehensive dataset analyzing how prompt attributes like length and complexity correlate with energy expenditure, highlighting significant opportunities for optimization in LLM deployment.