vLLM
High-throughput LLM serving engine
vLLM is a high-throughput, memory-efficient LLM inference engine with PagedAttention. The standard for self-hosted LLM serving with continuous batching and speculative decoding.
Panel Reviews
The Builder
Developer Perspective
“PagedAttention is a breakthrough for inference efficiency. The standard for production self-hosted LLM serving.”
The Skeptic
Reality Check
“If you're self-hosting LLMs, vLLM is the obvious choice. Battle-tested and actively maintained.”
The Futurist
Big Picture
“Self-hosted inference will remain important for latency, cost, and privacy. vLLM is the infrastructure layer.”
Community Sentiment
“PagedAttention is a genuinely novel contribution — throughput gains are not marketing fluff”
“vLLM continuous batching made our self-hosted Llama 3 actually competitive with hosted APIs”
“The speculative decoding support in recent versions pushed our latency below 100ms p50”
“Standard for self-hosted LLM serving — if you're running your own models, vLLM is the answer”