Paper ID: 2312.12472

A Performance Evaluation of a Quantized Large Language Model on Various Smartphones

Tolga Çöplü, Marc Loedi, Arto Bendiken, Mykhailo Makohin, Joshua J. Bouw, Stephen Cobb

This paper explores the feasibility and performance of on-device large language model (LLM) inference on various Apple iPhone models. Amidst the rapid evolution of generative AI, on-device LLMs offer solutions to privacy, security, and connectivity challenges inherent in cloud-based models. Leveraging existing literature on running multi-billion parameter LLMs on resource-limited devices, our study examines the thermal effects and interaction speeds of a high-performing LLM across different smartphone generations. We present real-world performance results, providing insights into on-device inference capabilities.

Submitted: Dec 19, 2023