SGLang is a fast serving framework for large language models and vision language models. It focuses on efficient serving and controllable interaction through co-designed backend runtime and frontend language.
This blog post benchmarks and compares the performance of SGLang, TensorRT-LLM, and vLLM for serving large language models (LLMs). SGLang demonstrates superior or competitive performance in offline and online scenarios, often outperforming vLLM and matching or exceeding TensorRT-LLM.