{
  "id": 13381193,
  "title": "How to Run vLLM Natively on Windows",
  "url": "https://urgent.news/2026/10/09/how-to-run-vllm-natively-on-windows",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-10-09T22:18:02.000Z",
  "source": {
    "name": "HackerNoon",
    "slug": "hackernoon",
    "url": "https://hackernoon.com/how-to-run-vllm-natively-on-windows?source=rss"
  },
  "original_language": "en",
  "account": "Running vLLM natively on Windows is possible through the vllm-windows-build open-source project. Developed and maintained by the author of the project, this tool patches, provides prebuilt wheels, and offers portable installer scripts to run vLLM directly on Windows 10/11 without the need for a Linux layer or WSL.\n\nThe project releases three versions: stable (0.27.1), regular (0.29.0), and prerelease (0.29.0). All utilize Triton for Windows 3.7.1 and support RTX 20/30/40/50 series GPUs with 12GB+ VRAM. The 0.27.1 wheel includes kernels for SM 7.5, 8.6, 8.9, and 12.0, FlashAttention 2, the Rust frontend and tool parser, and optional CPU/filesystem prompt-KV offload.\n\nTo install, the recommended approach is the portable installer. Download the desired version (0.27.1 in this case) from the release page, unzip it into a separate directory, and run the install.bat script. This script will download Python, PyTorch, and the matching prebuilt vLLM and Multi-TurboQuant wheels, ensuring everything runs smoothly without the need for pre-installed software.\n\nOnce installed, start the server using launch.bat. By default, it provides a model picker to scan models in the same directory as the script. Alternatively, you can pass a specific model and port number, such as launch.bat --model E:\\models\\Qwen3-14B-AWQ-4bit --port 8000. The installer checks for necessary components and repairs incomplete installations when rerun.",
  "summary": "Running vLLM natively on Windows 10/11 with CUDA and an OpenAI-compatible server, no WSL or Docker, via the open-source vllm-windows-build patches and wheels.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}