Introduction to vLLM and PagedAttention

Jul 11, 2026

vLLM achieves higher throughput than Hugging Face Transformers by using PagedAttention to eliminate memory waste and boost inference. This technique optimizes memory management for large language models, resulting in more efficient deployment.

Why it matters: PagedAttention addresses a key bottleneck in LLM inference, enabling faster and more efficient deployment of large models.

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