vLLM Serving

High-throughput and memory-efficient LLM inference serving engine

AI Infrastructure & MLOpsFree

vLLM is an open-source, high-throughput and memory-efficient serving engine for large language models that uses a novel memory management technique called PagedAttention to dramatically improve LLM inference performance. It achieves 10-20x higher throughput than standard HuggingFace implementations by efficiently managing key-value cache memory. vLLM supports continuous batching, multiple model architectures, and distributed serving across multiple GPUs. AI infrastructure teams, cloud providers, and organizations serving LLMs at scale use vLLM for production-grade, high-performance model serving.

Key Features

• ✓PagedAttention
• ✓High throughput
• ✓Continuous batching
• ✓Distributed serving
• ✓Open-source