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Quickstart

Verify the install

Run the following command to enumerate available devices and execution providers on your machine:

uv run winml sys --list-device --list-ep

--list-device and --list-ep print only the hardware and EP inventory. If the command exits without error, your winml-cli install is ready. See winml sys for the full flag reference.

Inspect the model

Before downloading any models, confirm that winml-cli recognises the model:

uv run winml inspect -m microsoft/resnet-50

+--------------------------- microsoft/resnet-50 ---------------------------+
| Task          image-classification                                         |
| Model Class   ResNetForImageClassification                                 |
| Exporter      OptimumExporter                                              |
| WinML Class   WinMLImageClassificationModel                                |
| Status        Supported                                                    |
+---------------------------------------------------------------------------+

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-quant

winml 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/, so you can reuse any stage independently.

After a successful build, you will find the following outputs in resnet_out/:

  • A standard ONNX file for each completed stage — load, inspect, or pass any of these to a downstream tool independently.
  • analyze_result.json — detailed model compatibility insights for each Windows ML EP, including supported, partially supported, and unsupported operators, detected optimization patterns, and recommended optimization workflows.
  • A declarative winml_build_config file — automatically generated after the build step to capture the full workflow end-to-end.

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.

What's next

  • How winml-cli Works — understand what each command does under the hood.
  • BERT sample — see the config + build + perf workflow in detail with a representative model.

See also