MobiLLM introduces a server-assisted architecture that enables large language model fine-tuning directly on mobile devices, preserving privacy while optimizing for limited resources.

• Employs side-tuning technique that maintains a small trainable network alongside a frozen base model
• Distributes computation intelligently between mobile device and server
• Significantly reduces memory requirements and improves training speed
• Preserves user privacy by keeping sensitive data on-device

This breakthrough enables personalized AI experiences on everyday devices without compromising data security or requiring expensive hardware upgrades.

Original Paper: MobiLLM: Enabling LLM Fine-Tuning on the Mobile Device via Server Assisted Side Tuning