How to Run vLLM Natively on Windows

The vllm-windows-build project addresses a specific technical hurdle for developers seeking to run vLLM on Windows. While vLLM officially supports Linux, this initiative aims to provide a direct Windows experience, including real CUDA kernel utilization and an OpenAI-compatible server. This could simplify development workflows for those primarily operating within a Windows environment, potentially reducing the overhead associated with virtualized or containerized solutions.

The project offers different build options, with v0.27.1 being the default. This version includes kernels for SM 7.5, 8.6, 8.9, and 12.0, covering RTX 20/30/40/50 series GPUs, along with FlashAttention 2 and opt-in CPU/filesystem prompt-KV offload. Although a Python 3.14 build exists, it uses a CPU TorchAudio wheel, meaning GPU audio processing and audio-model serving were not validated, making 0.27.1 a more validated choice for core model inference.

Installation is designed to be straightforward, with portable scripts that download necessary components like Python, PyTorch, and vLLM wheels, without requiring pre-installed Visual Studio or CUDA Toolkit. The bundled launcher provides an OpenAI-compatible HTTP server, enabling basic model interaction and supporting tool call parsing from specific formats, which could be useful for integrating with AI applications.