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vLLM

Fastest open-source LLM inference engine — production-grade serving

Inference Apache 2.0 Self-hosted Advanced

Stats

GitHub stars★ 45k+
LicenseApache 2.0
HostingSelf-hosted
DifficultyAdvanced

Get started

Official docs and GitHub repo

Visit vLLM ↗ View on GitHub ↗

What is vLLM?

vLLM is the industry-standard inference engine for serving open-source LLMs at scale. It uses PagedAttention to dramatically improve GPU memory efficiency, enabling higher throughput and lower latency than naive PyTorch serving. Used in production by dozens of companies to serve Llama, Mistral, and other open models.

Quick start

1
pip install vllm
2
python -m vllm.entrypoints.openai.api_server --model meta-llama/Llama-3.3-70B
3

Your local server now has an OpenAI-compatible API

4

Point any OpenAI SDK to http://localhost:8000

Use cases

Production LLM serving

High-throughput inference

OpenAI-compatible API endpoint

Multi-GPU deployment

Compatible models

Llama 3.3MistralDeepSeekQwenAny HuggingFace model

Why this matters for India

// india context

If you have a GPU server (even a single A100 from AWS), vLLM turns it into a powerful private LLM API.