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+## Operators Support Table
+
+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](https://webmachinelearning.github.io/webnn) provides two device types `cpu` and `gpu` to leverage different on-device accelerators. WebNN API implementation in Chromium uses XNNPack backend for `cpu` device type and DirectML backend for `gpu` device type. [The op support status](https://webmachinelearning.github.io/webnn-status/) behind these two backends is inconsistent since XNNPack backend currently supports limited op scope.
+
+
+| 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 | ✗ | ✓ | |
+| Ceil | ai.onnx(7-12, 13+) | ceil | ✓ | ✓ | |
+| Clip | ai.onnx(7-10, 11, 12, 13+) | clamp | ✓ | ✓ | |
+| 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). WebNN CPU requires the 'W' (weight) input to be a constant |
+| ConvTranspose | ai.onnx(7-10, 11+) | convTranspose2d | ✓ | ✓ | Only supports 3-D or 4-D input and 'W' (weight). WebNN CPU requires the 'W' (weight) input to be a constant |
+| Cos | ai.onnx(7+) | cos | ✗ | ✓ | |
+| Div | ai.onnx(7-12, 13, 14+) | div | ✓ | ✓ | |
+| Elu | ai.onnx(7+) | elu | ✓ | ✓ | |
+| 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 | ✗ | ✓ | |
+| 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 |
+| MatMul | ai.onnx(7-8, 9-12, 13+) | matmul | ✓ | ✓ | WebNN CPU doesn't support broadcasting for 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 restricts slope to be a static value |
+| 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, WebNN CPU backend only supports 'linear' mode, WebNN GPU backend only supports '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 | ✓ | ✓ | Only supports input rank >= 2 |
+| Split | ai.onnx(7-10, 11-12, 13-17, 18+) | split | ✓ | ✓ | Input 'split' if present should be a constant, WebNN CPU backend only supports up to 4 outputs |
+| 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 | ✓ | ✓ | |
+| Unsqueeze | ai.onnx(7-10, 11-12, 13-20, 21+) | reshape | ✓ | ✓ | |
+| Where | ai.onnx(7-8, 9-15, 16+) | where | ✗ | ✓ | |