flashinfer-ai

    flashinfer-ai/flashinfer

    FlashInfer: Kernel Library for LLM Serving

    graphics
    machine-learning
    attention
    cuda
    distributed-inference
    gpu
    jit
    Cuda
    Apache-2.0
    6.8K stars
    1.7K forks
    6.8K GitHub watchers
    Updated Nov 1, 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 1 day ago, with 432 contributors on GitHub.

    Use Cases & Benefits

    • Provides a high-performance CUDA kernel library for efficient Large Language Model (LLM) serving and inference.
    • Delivers state-of-the-art GPU kernels with customizable attention variants and memory-efficient scheduling for low-latency LLM inference.
    • Use for accelerating LLM inference workloads requiring sparse and dense attention on NVIDIA GPUs with PyTorch integration.
    • Use for developing custom attention mechanisms via JIT compilation to optimize novel LLM architectures and research.
    • Use for integrating efficient LLM serving kernels into distributed inference systems needing load-balanced scheduling and low-precision support.

    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

    Watch-outs

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    From the README

    FlashInfer is a library and kernel generator for Large Language Models that provides high-performance implementation of LLM GPU kernels such as FlashAttention, SparseAttention, PageAttention, Sampling, and more. FlashInfer focuses on LLM serving and inference, and delivers state-of-the-art performance across diverse scenarios.

    Check our v0.2 release blog for new features!

    FlashInfer supports PyTorch, TVM and C++ (header-only) APIs, and can be easily integrated into existing projects.

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

    Daily snapshots

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    Forks

    1.7K+451

    Open issues

    1.4K+466

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