onnxruntime/js/web/docs/webgpu-operators.md

Operators Support Table

The following table shows ONNX operators and the supported opset domain/versions in WebGPU EP by ONNX Runtime Web. For example, 4-6, 8+ means ONNX Runtime Web currently support opset version 4 to 6, 8 and above.

This file is automatically generated from the def files via this script. Do not modify directly.

Operator	Opset	Comments
Abs	ai.onnx(6-12,13+)
Acos	ai.onnx(7+)
Acosh	ai.onnx(9+)
Add	ai.onnx(7-12,13,14+)
ArgMax	ai.onnx(1-10,11-12,13+)
ArgMin	ai.onnx(1-10,11-12,13+)
Asin	ai.onnx(7+)
Asinh	ai.onnx(9+)
Atan	ai.onnx(7+)
Atanh	ai.onnx(9+)
AveragePool	ai.onnx(7-9,10,11+); com.ms.internal.nhwc(11+)	need perf optimization; need implementing activation
BiasAdd	com.microsoft(1+)
BiasSplitGelu	com.microsoft(1+)
Cast	ai.onnx(6-8,9-12,13-18,19+)
Ceil	ai.onnx(6-12,13+)
Clip	ai.onnx(6-10,11,12,13+)
Concat	ai.onnx(1-3,4-10,11-12,13+)
Conv	ai.onnx(1-10,11+); com.ms.internal.nhwc(11+)	need perf optimization; conv3d is not supported; need implementing activation
ConvTranspose	ai.onnx(1-10,11+); com.ms.internal.nhwc(11+)	need perf optimization; ConvTranspose3d is not supported; need implementing activation
Cos	ai.onnx(7+)
Cosh	ai.onnx(9+)
Div	ai.onnx(7-12,13,14+)
Einsum	ai.onnx(12+)
Elu	ai.onnx(6+)
Equal	ai.onnx(7-10,11-12,13-18,19+)
Erf	ai.onnx(9-12,13+)
Exp	ai.onnx(6-12,13+)
Expand	ai.onnx(8-12,13+)
Flatten	ai.onnx(1-8,9-10,11-12,13+)
Floor	ai.onnx(6-12,13+)
Gather	ai.onnx(1-10,11-12,13+)
GatherElements	ai.onnx(11-12,13+)
Gelu	com.microsoft(1+)
Gemm	ai.onnx(7-8,9-10,11-12,13+)
GlobalAveragePool	ai.onnx(1+); com.ms.internal.nhwc(1+)
GlobalMaxPool	ai.onnx(1+); com.ms.internal.nhwc(1+)
Greater	ai.onnx(7-8,9-12,13+)
GreaterOrEqual	ai.onnx(12-15,16+)
If	ai.onnx(1-10,11-12,13-18,19+)
InstanceNormalization	ai.onnx(6+); com.ms.internal.nhwc(6+)
LayerNormalization	ai.onnx(17+)
LeakyRelu	ai.onnx(6-15,16+)
Less	ai.onnx(7-8,9-12,13+)
LessOrEqual	ai.onnx(12-15,16+)
Log	ai.onnx(6-12,13+)
MatMul	ai.onnx(1-12,13+)
MaxPool	ai.onnx(1-7,8-9,10,11,12+); com.ms.internal.nhwc(11,12+)	need perf optimization; need implementing activation
MemcpyFromHost	ai.onnx(1+)
MemcpyToHost	ai.onnx(1+)
Mul	ai.onnx(7-12,13,14+)
Neg	ai.onnx(6-12,13+)
Not	ai.onnx(1+)
Pad	ai.onnx(2-10,11-12,13-17,18,19+)
Pow	ai.onnx(7-11,12,13-14,15+)
Range	ai.onnx(11+)
Reciprocal	ai.onnx(6-12,13+)
ReduceL1	ai.onnx(1-10,11-12,13-17,18+)
ReduceL2	ai.onnx(1-10,11-12,13-17,18+)
ReduceLogSum	ai.onnx(1-10,11-12,13-17,18+)
ReduceLogSumExp	ai.onnx(1-10,11-12,13-17,18+)
ReduceMax	ai.onnx(1-10,11,12,13-17,18+)
ReduceMean	ai.onnx(1-10,11-12,13-17,18+)
ReduceMin	ai.onnx(1-10,11,12,13-17,18+)
ReduceProd	ai.onnx(1-10,11-12,13-17,18+)
ReduceSum	ai.onnx(1-10,11-12,13+)
ReduceSumSquare	ai.onnx(1-10,11-12,13-17,18+)
Relu	ai.onnx(6-12,13,14+)
Reshape	ai.onnx(5-12,13,14+)	no GPU kernel
Resize	ai.onnx(10,11-12,13-17,18,19+); com.ms.internal.nhwc(11-12,13-17,18,19+)	CoordinateTransformMode align_corners is not supported with downsampling
Shape	ai.onnx(1-12,13-14,15+)	no GPU kernel; an ORT warning is generated - need to fix
Sigmoid	ai.onnx(6-12,13+)
Sin	ai.onnx(7+)
Sinh	ai.onnx(9+)
SkipLayerNormalization	com.microsoft(1+)
Slice	ai.onnx(1-9,10,11-12,13+)
Softmax	ai.onnx(1-10,11-12,13+)
Split	ai.onnx(1,2-10,11-12,13-17,18+)
Sqrt	ai.onnx(6-12,13+)
Squeeze	ai.onnx(1-10,11-12,13+)
Sub	ai.onnx(7-12,13,14+)
Tan	ai.onnx(7+)
Tanh	ai.onnx(6-12,13+)
ThresholdedRelu	ai.onnx(10+)
Tile	ai.onnx(6-12,13+)
Transpose	ai.onnx(1-12,13+)	need perf optimization
Unsqueeze	ai.onnx(1-10,11-12,13+)
Where	ai.onnx(9-15,16+)