vllm

vllm addresses the challenge of efficiently serving large language models (LLMs) in production environments. It provides a high-throughput and memory-efficient inference engine, making it particularly beneficial for ML/AI teams that require scalable solutions for handling complex models. With over 70,000 stars on GitHub, it indicates a strong community interest and support, suggesting that it is a production-ready solution. However, teams should consider alternatives when working with smaller models or when they need extensive customisation that vllm does not support.

This is a strong choice when teams need to deploy large language models at scale with minimal resource overhead. Consider alternatives if your project involves smaller models or requires specific features not offered by vllm.

Data scientists, machine learning engineers, and AI researchers will find vllm particularly useful in their workflows. It is commonly integrated into products and systems that require real-time inference capabilities, such as chatbots, recommendation engines, and other AI-driven applications.

Latest commit: 2026-02-14. Over the past 96 days, this repository gained 7.5k stars (+12.0% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.