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.
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---
name: "vLLM High-Throughput LLM Serving Engine with PagedAttention"
slug: "vllm-high-throughput-llm-serving"
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."
github_stars: 75090
verification: "listed"
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
No source-backed install or usage instructions could be extracted automatically. Review the upstream project before running this skill in a sensitive workflow.
- Source: https://github.com/vllm-project/vllm
## Source
- [Agent Skill Exchange](https://agentskillexchange.com/skills/vllm-high-throughput-llm-serving/)
