vLLM
High-throughput LLM inference engine with PagedAttention
About vLLM
vLLM is an open-source high-throughput LLM serving engine using PagedAttention for efficient memory management. Provides 24x higher throughput than Hugging Face Transformers for LLM inference.
Best for
Best for teams self-hosting LLMs wanting maximum inference throughput
Pros & Cons
Pros
- 24x higher throughput than standard inference
- PagedAttention for efficient GPU memory use
- Growing standard for LLM serving
Cons
- Requires GPU infrastructure to run
- Focused on inference — not training
- Operational complexity at scale
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