FlexInfer introduces a novel offloading framework that enables large language models to run efficiently on memory-limited devices without sacrificing performance.

• Employs asynchronous prefetching to load model components in advance, reducing latency
• Implements balanced memory locking to optimize resource allocation
• Uses flexible tensor preservation to intelligently manage memory usage
• Significantly outperforms existing offloading methods while maintaining accuracy

This engineering breakthrough makes advanced LLMs accessible on everyday devices, expanding AI capabilities beyond high-end hardware and enabling broader application development opportunities.

FlexInfer: Breaking Memory Constraint via Flexible and Efficient Offloading for On-Device LLM Inference