---
title: "vLLM High-Throughput LLM Serving Engine with PagedAttention"
description: "vLLM is a fast and memory-efficient inference and serving engine for large language models. It uses PagedAttention for efficient memory management, supports continuous batching, and provides an OpenAI-compatible API server for production-grade LLM deployment."
verification: "security_reviewed"
source: "https://github.com/vllm-project/vllm"
category:
  - "Developer Tools"
framework:
  - "Multi-Framework"
tool_ecosystem:
  github_repo: "vllm-project/vllm"
  github_stars: 75090
---

# vLLM High-Throughput LLM Serving Engine with PagedAttention

vLLM is a fast and memory-efficient inference and serving engine for large language models. It uses PagedAttention for efficient memory management, supports continuous batching, and provides an OpenAI-compatible API server for production-grade LLM deployment.

## Installation

Choose whichever fits your setup:

1. Copy this skill folder into your local skills directory.
2. Clone the repo and symlink or copy the skill into your agent workspace.
3. Add the repo as a git submodule if you manage shared skills centrally.
4. Install it through your internal provisioning or packaging workflow.
5. Download the folder directly from GitHub and place it in your skills collection.

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/vllm-high-throughput-llm-serving/)