vllm-project

    vllm-project/vllm

    A high-throughput and memory-efficient inference and serving engine for LLMs

    96.6K stars
    24.6K forks
    603 GitHub watchers
    Updated Nov 10, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    5 releases in the last 90 days, the latest 7 days ago, with 451 contributors on GitHub.

    Peaked at #30 in the weekly ranking the week of Aug 31, its best in the past year.

    Use Cases & Benefits

    • Provides a high-throughput, memory-efficient inference and serving engine for large language models (LLMs).
    • Delivers state-of-the-art serving speed and memory optimization using techniques like PagedAttention and CUDA/HIP graph execution.
    • Use for deploying and serving transformer-based LLMs with efficient resource utilization in production environments.
    • Use for integrating multi-modal and mixture-of-expert LLMs with scalable distributed inference across GPUs and TPUs.
    • Use for building OpenAI-compatible API servers that support streaming outputs and various decoding algorithms.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    Apache 2.0

    Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    Easy, fast, and cheap LLM serving for everyone

    vLLM is a fast and easy-to-use library for LLM inference and serving.

    Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry.

    vLLM seamlessly supports most popular open-source models on HuggingFace, including:

    Find the full list of supported models here.

    Install vLLM with pip or from source:

    Visit our documentation to learn more.

    Excerpt from the vllm-project/vllm README on GitHub (Apache-2.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Aug 14: +40Oct 8: +30Oct 22: +435Oct 23: +281Oct 24: +100Oct 25: +91Oct 26: +151Oct 27: +132Oct 28: +86Oct 29: +76Oct 30: +78Oct 31: +69

    +7,647 stars over 89 days across 19 snapshot days; best day +435 on Oct 22.

    Forks

    24.6K+4.0K

    Open issues

    10.1K+3.6K

    Compared with peers in AI

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth

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    vllm-project/vllm96.6K—657 days ago
    Category median115.8K+4.0K75—

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