{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/5"}],"enrichment":{"capability":"Provides pre-compiled GPU kernel binaries (cubins) for FlashInfer's high-performance attention, GEMM, and MoE operations across diverse NVIDIA GPU architectures.","skillfed_tags":["gpu-inference","llm-optimization","cuda-kernels"],"use_cases":["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"],"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.\n\nThe 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.","worth_installing":"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."},"id":"flashinfer-cubin","links":{"html":"https://skillfed.io/packages/flashinfer-cubin","md":"https://skillfed.io/packages/flashinfer-cubin.md","pypi":"https://pypi.org/project/flashinfer-cubin/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-25","license_spdx":null,"license_treatment":"permissive","name":"flashinfer-cubin","python_support":"supports_current","summary":"Pre-compiled cubins for FlashInfer"},"popularity":{"monthly_downloads":3028913,"position":2781,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.6.13"}