flashinfer-cubin
Pre-compiled cubins for FlashInfer
What it is and what it does
flashinfer-cubin is a companion package that bundles pre-compiled GPU kernel binaries for FlashInfer, a library delivering optimized kernels for LLM inference workloads. Instead of compiling kernels on first use, this package provides ready-to-use cubins for attention (including paged KV-cache, decode, prefill, and sparse patterns), matrix multiplication (BF16, FP8, FP4), and mixture-of-experts operations. It targets NVIDIA GPUs from Turing (SM 7.5) through Blackwell (SM 12.1), supporting multiple compute capabilities in a single installation.
The package is designed to accelerate LLM serving by eliminating JIT compilation overhead and enabling offline deployment. It integrates with production inference frameworks and supports low-precision compute (FP8, FP4 quantization). The library is actively maintained and adopted by major inference systems.
Use it for:
- Pre-compile inference kernels for production LLM serving to eliminate startup latency and enable offline deployment
- Accelerate attention operations in batched inference with optimized paged KV-cache and decode kernels
- Deploy quantized models (FP8/FP4) with fused GEMM and MoE kernels for cost-effective inference at scale
- Support mixed-precision inference with BF16 and low-precision compute across diverse GPU architectures
- Enable CUDAGraph and torch.compile compatible serving for low-latency production workloads
Worth the install?
AI-flagged interpretation of the facts on this page — verify before relying
Provides pre-compiled GPU kernel binaries (cubins) for FlashInfer's high-performance attention, GEMM, and MoE operations across diverse NVIDIA GPU architectures.
Yes. Install this if you are deploying FlashInfer-based inference in production or development and want to avoid JIT compilation overhead. The permissive Apache-2.0 license, active maintenance, low install friction, and zero known vulnerabilities make it a safe choice. Verify that your target GPU architecture is included in the 0.6.13 release before committing.
Install
flashinfer-cubin on PyPI
pip
pip install flashinfer-cubinuv
uv add flashinfer-cubinpoetry
poetry add flashinfer-cubinInstalling flashinfer-cubin
Before you install
Low friction installation with a pure Python wheel. Active maintenance with recent releases; last commit 2026-08-14 and 6159 repository stars indicate ongoing development.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for production deployments.
Quickstart
pip install flashinfer-cubin
import flashinfer
# Pre-compiled kernels are now available for use
flashinfer.show-config
Requires CUDA 12.6, 12.8, 13.0, or 13.1 and an NVIDIA GPU with compute capability SM 7.5 or later.
Verify before relying
- Whether all GPU architectures (SM 7.5 through SM 12.1) are included in this 0.6.13 wheel or if selective compilation is needed
- Runtime memory or disk footprint of the pre-compiled cubin binaries
- Compatibility with CUDA versions other than the documented 12.6, 12.8, 13.0, 13.1
- Whether flashinfer-cubin can be used standalone or requires flashinfer-python as a runtime dependency
Package facts
| License | Apache-2.0 (permissive) |
| Python support | supports the current Python release (>=3.8) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | none |
| Maintenance | actively maintained — 50 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 3,028,913/month — #2,781 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: flashinfer_cubin-0.6.13-py3-none-any.whl
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