VLLM is a high-throughput, memory-efficient inference serving engine tailored for Large Language Models (LLMs). It optimizes the process of serving LLMs by effectively managing memory usage, facilitating faster responses while maintaining performance integrity.

The tool supports diverse deployment environments, making it adaptable for various user groups, from small startups to large enterprises. Notably, VLLM allows for multi-node configurations, enhancing scalability and load management during peak requests.