What Happened
In June 2023, the vLLM team introduced vLLM as an open-source library focused on high-throughput LLM inference and serving, built around the PagedAttention approach to KV-cache management.
Why It Matters
As LLM usage shifted from demos to production workloads, inference throughput and memory efficiency became bottlenecks. vLLM helped popularize a “serving-first” mindset and contributed to a broader ecosystem of specialized inference engines.
Technical Details
vLLM’s design emphasizes continuous batching and more efficient KV-cache memory use to improve throughput under real-world, variable-length request patterns.