vLLM
An open-source high-performance engine that runs large language models efficiently — the motor, not the operating layer.
vLLM is a widely used open-source inference engine for large language models. At its core is efficient memory and batch management that can process many requests at once. It answers the question ‘how do I run a model fast?’.
What vLLM alone does not answer: who is allowed to access it? What happens under overload? How are multiple nodes orchestrated and access logged? These are operational questions — and exactly where a layer like the Quinta gateway comes in.
In Quinta’s benchmark the same engine runs in both variants. ‘Plain vLLM’ stands for operation without admission control; the comparison shows how much the operating layer adds on top.