rtp-llm

RTP-LLM is a high-performance LLM inference acceleration engine developed by the Alibaba Foundation Model Inference team. This engine has been widely applied in various Alibaba business scenarios such as Taobao and Tmall, supporting multiple mainstream model formats and hardware backends. It provides efficient production-level services for large language models by integrating advanced operator optimization, quantization techniques, and distributed inference capabilities.

RTP-LLM is a production-grade large model inference acceleration engine developed by the Alibaba Foundation Model Inference Team. Its core design philosophy lies in achieving extreme optimization for complex inference scenarios through a high-performance C++ scheduling and batching framework. This project addresses the urgent need for high-throughput, low-latency inference in large-scale commercial applications and widely supports core Alibaba businesses such as Taobao and Tmall. By integrating advanced kernels like PagedAttention and FlashAttention, as well as various quantization techniques, RTP-LLM significantly improves hardware utilization while ensuring model accuracy, and demonstrates powerful scalability for multi-hardware backends and heterogeneous computing.