GQSA introduces a novel hybrid compression technique that intelligently combines quantization and sparsification to achieve superior performance at high compression rates.

• Achieves better efficiency-accuracy tradeoff than single-strategy approaches
• Implements group-wise quantization targeted to different parameter sensitivities
• Features dynamic granularity sparsification that adapts to model architecture
• Delivers significant inference speedups with minimal accuracy loss

This breakthrough addresses a critical engineering challenge in deploying large language models at scale, enabling faster inference with reduced computational and memory requirements while maintaining model quality.

GQSA: Group Quantization and Sparsity for Accelerating Large Language Model Inference