// Run models locally
vllmv0.31.0
A high-throughput and memory-efficient inference and serving engine for LLMs
Open source Maintained Dual-use For developers
IN ONE PARAGRAPH
vllm is A high-throughput and memory-efficient inference and serving engine for LLMs.
Good for: Developers and teams who want to run models locally.
01How to start
- 1Read the official quick-start (link above).
- 2Install from the official package registry:
pip install vllm - 3Try it on a small example before wiring it into a project.
02Alternatives & comparison
Compare side by side → sglang SGLang is a high-performance serving framework for large language models and multimodal models. ★ 38k gpustack A GPU cluster manager for high-performance AI model serving (vLLM, SGLang) and on-demand SSH-accessible GPU instances. ★ 5.9k Ollama Get up and running with Kimi, GLM, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. ★ 184k LMCache LMCache: Supercharge Your LLM with the Fastest KV Cache Layer ★ 12k TensorRT-LLM TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way. ★ 15k