vLLM
An open-source, ultra-high-throughput inference engine specifically designed for massive language models, utilizing novel memory management techniques.
Think of It Like This
Like swapping a slow, single-lane toll booth for an automated, multi-lane express toll system to process thousands of cars instantly.
At its core, vLLM relies on PagedAttention to eliminate memory fragmentation in the KV cache. This allows it to batch significantly more simultaneous user requests on a single GPU compared to standard HuggingFace implementations. It has become the de-facto industry standard for hosting and serving open-source models in production.