ONNX Runtime Node.js binding enables Node.js applications to run ONNX model inference.
Install the latest stable version:
npm install onnxruntime-node
Install the nightly version:
npm install onnxruntime-node@dev
Refer to ONNX Runtime JavaScript examples for samples and tutorials.
ONNXRuntime works on Node.js v16.x+ (recommend v20.x+) or Electron v15.x+ (recommend v28.x+).
The following table lists the supported versions of ONNX Runtime Node.js binding provided with pre-built binaries.
| EPs/Platforms | Windows x64 | Windows arm64 | Linux x64 | Linux arm64 | MacOS x64 | MacOS arm64 |
|---|---|---|---|---|---|---|
| CPU | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ |
| WebGPU | ✔️ [1] | ✔️ [1] | ✔️ [1] | ✔️ [1] | ✔️ [1] | ✔️ [1] |
| DirectML | ✔️ | ✔️ | ❌ | ❌ | ❌ | ❌ |
| CUDA | ❌ | ❌ | ✔️[2] | ❌ | ❌ | ❌ |
| CoreML | ❌ | ❌ | ❌ | ❌ | ✔️ | ✔️ |
- [1]: WebGPU support is currently experimental.
- [2]: CUDA v12. See CUDA EP Installation for details.
To use on platforms without pre-built binaries, you can build Node.js binding from source and consume it by npm install <onnxruntime_repo_root>/js/node/. See also instructions for building ONNX Runtime Node.js binding locally.
Right now, the Windows version supports WebGPU execution provider and DML execution provider. Linux x64 can use CUDA and TensorRT.
To use CUDA EP, you need to install the CUDA EP binaries. By default, the CUDA EP binaries are installed automatically when you install the package. If you want to skip the installation, you can pass the --onnxruntime-node-install=skip flag to the installation command.
npm install onnxruntime-node --onnxruntime-node-install=skip
You can also use this flag to specify the version of the CUDA: (v11 or v12) CUDA v11 is no longer supported since v1.22.
License information can be found here.