vLLM
vLLM is a high-throughput and memory-efficient open-source library for LLM inference and serving.
FreeLinuxDockerAPIOpen sourceKoreanMultimodal
Visit websitevllm.ai
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vLLM is a high-throughput and memory-efficient open-source library for LLM inference and serving. By utilizing PagedAttention, it effectively manages KV cache memory, delivering up to 24x higher throughput than traditional systems. It supports continuous batching and various hardware backends including NVIDIA GPUs, AMD, and AWS Inferentia, making it a top choice for deploying large-scale AI models in production.
Key features
- PagedAttention memory management
- Continuous batching
- OpenAI-compatible API server
- Support for various quantization
- Distributed inference
- Multi-hardware support
- Prefix caching
Pricing
Use cases
- Deploying large-scale LLM services
- Reducing inference costs
- Building private LLM servers
- Real-time chatbot backends
Who it is for
MLOps EngineersAI Infrastructure DevelopersData scientists
Integrations
RayKubernetesHugging FaceLangChainBentoML
Tags
MLOpsPagedAttention
How we verified this
Company, pricing, and feature details come from the primary sources below and our latest verification pass. When sources disagree, the official source and the most recent check win.
Last verified 08/30/2026Verified sources: 1
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