Windows ML CLI is a command line tool for building portable, performant, and high-quality AI models for Windows ML. It takes you from a source model — whether from Hugging Face or your own pipeline — to a hardware-optimized artifact in a reproducible workflow.
Purpose-built for Windows hardware diversity, the CLI handles conversion, graph optimization, and compilation across AMD, Intel, NVIDIA, and Qualcomm targets. The CLI fits naturally into CI/CD pipelines so teams can validate and ship models easily.
What you can do¶
- Build once, run across hardwares. Compose your own workflow from primitive commands (
export,analyze,optimize,quantize,compile), or use an auto-generated config withwinml build- both produce portable models that run across hardware. - Drill into the details. Deep insights into operator compatibility, shape mismatches, graph optimizations, and EP-aware tuning at any stage of the pipeline.
- AI-ready. CLI-driven tools with built-in skills, friendly to work with mainstream agents.
What you get out of the box¶
- All Windows ML EPs supported. Every supported execution provider is available behind the same commands.
- Curated model catalog. A verified set of models that run across all Windows ML EPs - a reliable starting point.
- Bring your own ONNX. Not only for converting from PyTorch - bring an existing ONNX model to get operator-compatibility insights and optimize it based on the analysis.
| Component | Details |
|---|---|
| Windows | Windows 11 24H2 or later (required for NPU support; earlier versions work for CPU/GPU) |
| Python | 3.11 |
| Package manager | uv |
| WinML CLI | PyPI |
WinML CLI requires Python 3.11 and is distributed as a Python wheel. We recommend uv for fast, reproducible environment setup.
1. Create an environment
uv venv --python 3.11Activate it:
# Windows (PowerShell)
.venv\Scripts\activate
# Windows (Git Bash / WSL)
source .venv/Scripts/activate2. Install winml-cli
uv pip install winml-cli3. Verify your environment
uv run winml sys --list-device --list-epThis command enumerates available compute devices and execution providers on your machine. If an expected device or execution provider is missing, winml sys is the right place to diagnose it. See winml sys for the full flag reference and troubleshooting tips.
Inspect the model¶
Before downloading any models, confirm that winml-cli recognises the model:
uv run winml inspect -m microsoft/resnet-50💡 Tip: Always inspect before build to catch unsupported architectures early.
Build the model¶
uv run winml build -m microsoft/resnet-50 -o resnet_out/ --no-quantwinml build runs all pipeline steps in sequence — export, optimize, quantize. You can start a model build without a config file, or provide one to configure each step in the sequence (see winml config to customize). All intermediate artifacts land in resnet_out/. For more details, see Output Layout - Windows ML CLI.
Benchmark the model¶
uv run winml perf -m resnet_out/model.onnx --device auto --iterations 50 --monitor--device auto lets the CLI resolve the best available device on your machine — NPU first, then GPU, then CPU.
- Use with AI Agent — See details at Use with AI Agent - Windows ML CLI.
- UI Quickstart — See also UI Quickstart - Windows ML CLI.
- Full Documentation — Access the complete wiki for detailed guides, API references, and troubleshooting.
- Supported Models — Browse the curated catalog of verified models that run across all Windows ML EPs.
- Execution provider compatibility — Browse the compatible EP alias and device combinations.
We welcome contributions! Please see the contribution guidelines.
For feature requests or bug reports, please file a GitHub Issue.
See CODE_OF_CONDUCT.md.
This project is licensed under the MIT License.