Fine-Tuning a 3B-Parameter LLM on a Smartphone: Characterizing Sustained Training

Excerpt

arXiv:2610.06325v1 Announce Type: cross Abstract: Multi-billion-parameter LLMs now run on phones for inference, and training them on the device would personalize them without user data leaving the phone. Prior work has measured individual training steps of such models on phones, but not complete training runs, and not whether adapters trained on the device improve personalization. We present the first systematic characterization of a multi-billion-parameter LLM fine-tuned on a mobile device, cov