The following table shows ONNX
operators and the supported opset domain/versions in WebNN EP by ONNX Runtime Web. For example,
7-12, 13+ means ONNX Runtime Web currently supports opset version 7 to 12, 13 and above.
(Note: ONNX Runtime only guarantees support for models stamped with opset version 7 or above for opset domain 'ai.onnx'.)
WebNN API provides two device types cpu and gpu to leverage different on-device accelerators. WebNN API implementation in Chromium uses TFLite XNNPack delegate backend for cpu device type and DirectML backend for gpu device type. The op support status behind these two backends is inconsistent.
| Operator | Opset | WebNN API | WebNN CPU | WebNN GPU | Comments |
|---|---|---|---|---|---|
| Abs | ai.onnx(7-12, 13+) | abs | ✓ | ✓ | |
| Add | ai.onnx(7-12, 13, 14+) | add | ✓ | ✓ | |
| ArgMax | ai.onnx(7-10, 11, 12, 13+) | argMax | ✓ | ✓ | |
| ArgMin | ai.onnx(7-10, 11, 12, 13+) | argMin | ✓ | ✓ | |
| AveragePool | ai.onnx(7-9, 10, 11, 12-18, 19+) | averagePool2d | ✓ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'count_include_pad' value is 0 |
| BatchNormalization | ai.onnx(7-8, 9-13, 14, 15+) | batchNormalization | ✓ | ✓ | Only supports 'training_mode' value is 0, one output |
| Cast | ai.onnx(7-8, 9-12, 13-18, 19-20, 21+) | cast | ✓ | ✓ | WebNN CPU backend doesn't support casting to uint64 data type |
| Ceil | ai.onnx(7-12, 13+) | ceil | ✓ | ✓ | |
| Clip | ai.onnx(7-10, 11, 12, 13+) | clamp | ✓ | ✓ | WebNN CPU backend only supports 3 specific ranges: [0.0, infinity], [-1.0, 1.0], [0.0, 6.0] (Chromium issue: https://issues.chromium.org/issues/326156496) |
| Concat | ai.onnx(7-10, 11-12, 13+) | concat | ✓ | ✓ | |
| Conv | ai.onnx(7-10, 11+) | conv2d | ✓ | ✓ | Only supports 3-D or 4-D input and 'W' (weight) |
| ConvTranspose | ai.onnx(7-10, 11+) | convTranspose2d | ✓ | ✓ | Only supports 3-D or 4-D input and 'W' (weight). WebNN CPU backend only supports default dilations and group |
| Cos | ai.onnx(7+) | cos | ✓ | ✓ | |
| Div | ai.onnx(7-12, 13, 14+) | div | ✓ | ✓ | |
| DequantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | dequantizeLinear | ✗ | ✓ | |
| Dropout | ai.onnx(7-9, 10-11, 12, 13-21, 22+) | identity | ✓ | ✓ | Only supports test mode |
| Elu | ai.onnx(7+) | elu | ✓ | ✓ | WebNN CPU backend only supports 'alpha' value is 1.0 |
| Equal | ai.onnx(7-10, 11-12, 13-18, 19+) | equal | ✓ | ✓ | |
| Erf | ai.onnx(7-9, 10-12, 13+) | erf | ✓ | ✓ | |
| Exp | ai.onnx(7-12, 13+) | exp | ✓ | ✓ | |
| Expand | ai.onnx(8-12, 13+) | expand | ✓ | ✓ | 'shape' input should be a constant |
| Flatten | ai.onnx(7-8, 9-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | |
| Floor | ai.onnx(7-12, 13+) | floor | ✓ | ✓ | |
| Gather | ai.onnx(7-10, 11-12, 13+) | gather | ✓ | ✓ | |
| Gelu | ai.onnx(20+) | gelu | ✓ | ✓ | |
| Gemm | ai.onnx(7-8, 9-10, 11-12, 13+) | gemm | ✓ | ✓ | Only supports 1-D 'C' input |
| GlobalAveragePool | ai.onnx(7+) | averagePool2d | ✓ | ✓ | Only supports 4-D input |
| GlobalMaxPool | ai.onnx(7+) | maxPool2d | ✓ | ✓ | Only supports 4-D input |
| GlobalLpPool | ai.onnx(7+) | l2Pool2d | ✗ | ✓ | Only supports 4-D input, 'p' value is 2 |
| Greater | ai.onnx(7-8, 9-12, 13+) | greater | ✓ | ✓ | |
| GreaterOrEqual | ai.onnx(12-15, 16+) | greaterOrEqual | ✓ | ✓ | |
| GRU | ai.onnx(7-13, 14-21, 22+) | gru | ✓ | ✓ | Only supports 'layout' == 0. 'clip' is not supported. The activation functions in 'activations' must be one of 'Relu', 'Tanh', 'Sigmoid'. Forward and backward activations must be the same if bidirectional. 'sequence_lens' if present should be constant with values equal to the first dimension length of input 'X' |
| HardSigmoid | ai.onnx(7+) | hardSigmoid | ✓ | ✓ | |
| HardSwish | ai.onnx(14+) | hardSwish | ✓ | ✓ | |
| Identity | ai.onnx(7-13, 14-15, 16-18, 19-20, 21+) | identity | ✓ | ✓ | |
| InstanceNormalization | ai.onnx(7+) | instanceNormalization | ✓ | ✓ | |
| LayerNormalization | ai.onnx(7-16, 17+) | layerNormalization | ✓ | ✓ | |
| LeakyRelu | ai.onnx(7-15, 16+) | leakyRelu | ✓ | ✓ | |
| Less | ai.onnx(7-8, 9-12, 13+) | lesser | ✓ | ✓ | |
| LessOrEqual | ai.onnx(12-15, 16+) | lesserOrEqual | ✓ | ✓ | |
| Log | ai.onnx(7-12, 13+) | log | ✓ | ✓ | |
| LpPool | ai.onnx(7-10, 11-17, 18+) | l2Pool2d | ✗ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'p' value is 2 |
| LSTM | ai.onnx(7-13, 14-21, 22+) | lstm | ✓ | ✓ | Only supports 'layout' == 0, 'input_forget' == 0. 'clip' is not supported. The activation functions in 'activations' must be one of 'Relu', 'Tanh', 'Sigmoid'. Forward and backward activations must be the same if bidirectional. 'sequence_lens' if present should be constant with values equal to the first dimension length of input 'X' |
| MatMul | ai.onnx(7-8, 9-12, 13+) | matmul | ✓ | ✓ | |
| Max | ai.onnx(7, 8-11, 12, 13+) | max | ✓ | ✓ | |
| MaxPool | ai.onnx(7, 8-9, 10, 11, 12+) | maxPool2d | ✓ | ✓ | Only supports 4-D input, 2-D 'kernel_shape', 'storage_order' != 1, one output |
| Min | ai.onnx(7, 8-11, 12, 13+) | min | ✓ | ✓ | |
| Mul | ai.onnx(7-12, 13, 14+) | mul | ✓ | ✓ | |
| Neg | ai.onnx(7-12, 13+) | neg | ✓ | ✓ | |
| Not | ai.onnx(7+) | logicalnot | ✓ | ✓ | |
| Pad | ai.onnx(7-10, 11-12, 13-17, 18, 19-20, 21+) | pad | ✓ | ✓ | modes == 'wrap' is not supported |
| Pow | ai.onnx(7-11, 12, 13-14, 15+) | pow | ✓ | ✓ | |
| PRelu | ai.onnx(7-8, 9-15, 16+) | prelu | ✓ | ✓ | WebNN CPU backend restricts the last dimension of input and slope to be same (Chromium issue: https://issues.chromium.org/issues/335517470) |
| QuantizeLinear | ai.onnx(10-12, 13-18, 19-20, 21-22, 23+) | quantizeLinear | ✗ | ✓ | |
| Reciprocal | ai.onnx(7-12, 13+) | reciprocal | ✓ | ✓ | |
| ReduceL1 | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceL1 | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceL2 | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceL2 | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceLogSum | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceLogSum | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceLogSumExp | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceLogSumExp | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceMax | ai.onnx(7-10, 11, 12, 13-17, 18-19, 20+) | reduceMax | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceMean | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceMean | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceMin | ai.onnx(7-10, 11, 12, 13-17, 18-19, 20+) | reduceMin | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceProd | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceProduct | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceSum | ai.onnx(7-10, 11-12, 13+) | reduceSum | ✓ | ✓ | Input 'axes' if present should be a constant |
| ReduceSumSquare | ai.onnx(7-10, 11-12, 13-17, 18+) | reduceSumSquare | ✓ | ✓ | Input 'axes' if present should be a constant |
| Relu | ai.onnx(7-12, 13, 14+) | relu | ✓ | ✓ | |
| Reshape | ai.onnx(7-12, 13, 14-18, 19-20, 21+) | reshape | ✓ | ✓ | Input 'shape' should be a constant, 0 dimension value in 'shape' is not supported |
| Resize | ai.onnx(11-12, 13-17, 18, 19+) | resample2d | ✓ | ✓ | Only supports 4-D input, exclude_outside != 0, input 'scales' and 'sizes' if present must be a constant, 'linear' and 'nearest' modes |
| Shape | ai.onnx(7-12, 13-14, 15-18, 19-20, 21+) | slice | ✓ | ✓ | |
| Sigmoid | ai.onnx(7-12, 13+) | sigmoid | ✓ | ✓ | |
| Softplus | ai.onnx(7+) | softplus | ✓ | ✓ | |
| Softsign | ai.onnx(7+) | softsign | ✓ | ✓ | |
| Sin | ai.onnx(7+) | sin | ✓ | ✓ | |
| Slice | ai.onnx(7-9, 10, 11-12, 13+) | slice | ✓ | ✓ | Input 'starts', 'ends', 'axes', and 'steps' if present must be a constant, only supports 'steps' value 1 |
| Softmax | ai.onnx(7-10, 11-12, 13+) | softmax | ✓ | ✓ | |
| Split | ai.onnx(7-10, 11-12, 13-17, 18+) | split | ✓ | ✓ | Input 'split' if present should be a constant |
| Sqrt | ai.onnx(7-12, 13+) | sqrt | ✓ | ✓ | |
| Squeeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | Input 'axes' if present should be a constant |
| Sub | ai.onnx(7-12, 13, 14+) | sub | ✓ | ✓ | |
| Tan | ai.onnx(7+) | tan | ✓ | ✓ | |
| Tanh | ai.onnx(7-12, 13+) | tanh | ✓ | ✓ | |
| Transpose | ai.onnx(7-12, 13-20, 21+) | transpose | ✓ | ✓ | |
| Trilu | ai.onnx(14+) | triangular | ✓ | ✓ | Input 'k' (option 'diagonal' for WebNN) if present should be a constant |
| Unsqueeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | |
| Where | ai.onnx(7-8, 9-15, 16+) | where | ✓ | ✓ |