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Windows ML supports a wide variety of ONNX models for different AI scenarios. This page provides samples for using Windows ML from different frameworks and languages, as well as ready-to-use model samples for common AI tasks.
AI Dev Gallery
The AI Dev Gallery is the easiest way to explore Windows ML samples. It provides:
- Interactive demos for each model scenario
- Full source code for every sample
- One-click export to a Visual Studio project so you can use the model in your own app
Tip
Each model sample in the AI Dev Gallery includes complete source code. Use the Export to Visual Studio feature to quickly create a working project with your chosen model.
Framework integration samples
The Windows App SDK Samples repository on GitHub contains sample applications that demonstrate how to integrate Windows ML into different languages and frameworks.
| Language | Framework | Packaging type | Dependency type | Link |
|---|---|---|---|---|
| C# | Console | Unpackaged | Framework-dependent | Link |
| C# | WPF | Unpackaged | Framework-dependent | Link |
| C# | WinUI | MSIX | Framework-dependent | Link |
| C# | WinForms | Unpackaged | Framework-dependent | Link |
| C++ | Console | DLL w/ separate EXE | Framework-dependent | Link |
| C++ | Console | Unpackaged | Self-contained | Link |
| C++ | Console | MSIX | Framework-dependent | Link |
| Python | Console | Unpackaged | Framework-dependent | Link |
Model samples by scenario
The following sections list available models for each AI scenario, along with their size and hardware support. Click "Try it yourself" to open the sample in the AI Dev Gallery app.
Large Language Models (LLMs) - Text generation
Generate conversational text responses using state-of-the-art language models.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| Phi 4 Mini CPU | CPU | 4.6 GB |
| Phi 3.5 Mini CPU ACC4 | CPU | 2.6 GB |
| Phi 3 Mini CPU | CPU | 2.5 GB |
| Phi 3 Mini CPU ACC4 | CPU | 2.5 GB |
| Phi 3 Medium CPU ACC4 | CPU | 8.6 GB |
| Mistral 7B Instruct 0.2 CPU | CPU | 4.6 GB |
| Mistral 7B Instruct 0.2 CPU ACC4 | CPU | 4.6 GB |
Large Language Models (LLMs) - Multi-modal
Analyze images and generate text descriptions using vision-enabled language models.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| Phi 3 Vision CPU | CPU | 3.0 GB |
| Phi 3.5 Vision CPU | CPU | 3.0 GB |
Text embedding (Semantic search)
Convert text into vector embeddings for semantic search and similarity matching.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| all-MiniLM-L12-v2 | CPU, GPU | 127.2 MB |
| all-MiniLM-L6-v2 | CPU, GPU | 86.4 MB |
Image generation
Create images from text prompts using diffusion models.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| Stable Diffusion v1.4 | CPU, GPU | 5.1 GB |
Image classification
Classify images into predefined categories.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| MobileNet v2 1.0 | CPU, GPU | 13.3 MB |
| ResNet101 v1 7 | CPU, GPU | 170.6 MB |
| ResNet50 v1 7 | CPU, GPU | 97.8 MB |
| SqueezeNet 1.1 | CPU, GPU, NPU | 4.7 MB |
Image object detection
Detect and locate objects within images.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| Faster RCNN 10 | CPU, GPU | 159.6 MB |
| Faster RCNN 12 | CPU, GPU | 168.5 MB |
| YOLOv4 | CPU, GPU | 245.5 MB |
Image segmentation (Background detection)
Separate foreground subjects from backgrounds in images.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| SINet | CPU, GPU, NPU | 404.7 KB |
Human pose detection
Detect human body poses and key points in images.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| HRNet Pose | CPU, GPU, NPU | 108.9 MB |
Street segmentation
Segment street photographs into detectable zones for autonomous driving and mapping applications.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| FFNet 78s | CPU, GPU, NPU | 104.9 MB |
| FFNet 54s | CPU, GPU, NPU | 68.8 MB |
Face detection
Detect and locate human faces in images.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| FaceDetLite | CPU, GPU, NPU | 3.4 MB |
Audio transcription (Voice-to-text)
Convert spoken audio into written text using speech recognition models.
Try it yourself in the AI Dev Gallery app
| Model | Hardware | Size |
|---|---|---|
| Whisper Tiny CPU | CPU | 73.8 MB |
| Whisper Small CPU | CPU | 422.5 MB |
| Whisper Medium CPU | CPU | 1.3 GB |