vLLM
Verified
High-throughput LLM serving engine — the production standard for GPU inference at scale.
About vLLM
vLLM is a high-throughput serving engine for LLMs that uses PagedAttention for efficient memory management. It delivers 2-4x higher throughput than naive serving and is the go-to choice for production deployments on GPU clusters. Used by major AI companies for inference at scale.
Key Features
- PagedAttention for efficient memory
- 2-4x throughput improvement
- OpenAI-compatible API server
- Continuous batching for concurrency
- Supports most popular model architectures
Pros & Cons
Pros
+ Industry-standard for production serving
+ Dramatically higher throughput
+ Active development and community
Cons
- Requires GPU infrastructure
- Complex setup for multi-GPU
- Not ideal for single-user local use
Use Cases
Production LLM servingHigh-concurrency AI APIsModel serving infrastructureBatch inference pipelines
Pricing
Open Source
Free and open-source. Apache 2.0 license.
Who It's For
ML infrastructure engineersAI companiesDevOps teamsCloud platform builders
Details