<ul><li>Generative AI, such as Large Language Models (LLMs), is becoming more accessible for the general consumer.</li><li>However, there are concerns regarding reliance on network access, privacy, and security risks.</li><li>To address this, researchers are optimizing LLMs for running locally on edge devices.</li><li>A recent study focuses on characterizing commercially available embedded hardware (Jetson Orin) for LLMs and provides a utility for batch testing.</li></ul>

Large Language Models on Small Resource-Constrained Systems: Performance Characterization, Analysis and Trade-offs

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