diff --git a/onnxruntime/core/providers/webnn/builders/impl/pad_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/pad_op_builder.cc
index 80e72875072ea..9852db0abc9d2 100644
--- a/onnxruntime/core/providers/webnn/builders/impl/pad_op_builder.cc
+++ b/onnxruntime/core/providers/webnn/builders/impl/pad_op_builder.cc
@@ -89,14 +89,14 @@ Status PadOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
     ORT_RETURN_IF_NOT(ReadIntArrayFrom1DTensor(pads_tensor, pads, logger), "Error while read pads tensor");
 
     // Constant value and axes are optional. Make sure they are not empty.
-    if (input_defs.size() >= 3 && !GetTensorName(input_defs, 2).empty()) {
+    if (!GetTensorName(input_defs, 2).empty()) {
       const auto value_tensor = *initializers.at(input_defs[2]->Name());
       emscripten::val value = emscripten::val::object();
       ORT_RETURN_IF_NOT(ReadScalarTensorData(value_tensor, value, logger), "Cannot read constant value");
       options.set("value", value);
     }
 
-    if (input_defs.size() == 4 && !GetTensorName(input_defs, 3).empty()) {
+    if (!GetTensorName(input_defs, 3).empty()) {
       const auto input_rank = input_shape.size();
       std::vector<int64_t> axes;
       const auto& axes_tensor = *initializers.at(input_defs[3]->Name());
diff --git a/onnxruntime/core/providers/webnn/builders/impl/reduction_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/reduction_op_builder.cc
index 5e2888317f4f5..c0954f7cf6fb1 100644
--- a/onnxruntime/core/providers/webnn/builders/impl/reduction_op_builder.cc
+++ b/onnxruntime/core/providers/webnn/builders/impl/reduction_op_builder.cc
@@ -65,7 +65,7 @@ Status ReductionOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
   if (opset >= 18 || (op_type == "ReduceSum" && opset >= 13)) {
     // 'axes' is an optional input.
     const auto noop_with_empty_axes = helper.Get("noop_with_empty_axes", 0);
-    if (input_defs.size() > 1 && !GetTensorName(input_defs, 1).empty()) {
+    if (!GetTensorName(input_defs, 1).empty()) {
       // Optional input axes is provided, use axes initializer data.
       const auto& initializers(model_builder.GetInitializerTensors());
       const auto& axes_tensor = *initializers.at(input_defs[1]->Name());
diff --git a/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc
index bcc2c9a86ebab..9819e4ce7ac5b 100644
--- a/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc
+++ b/onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc
@@ -57,7 +57,7 @@ Status SplitOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
   axis = SafeInt<int32_t>(HandleNegativeAxis(axis, rank));
   options.set("axis", axis);
 
-  if (input_defs.size() == 2 && !GetTensorName(input_defs, 1).empty()) {
+  if (!GetTensorName(input_defs, 1).empty()) {
     // Inputs contains optional 'split' input
     std::vector<int32_t> splits;
     const auto& initializers(model_builder.GetInitializerTensors());
diff --git a/onnxruntime/core/providers/webnn/builders/impl/squeeze_unsqueeze_op_builder.cc b/onnxruntime/core/providers/webnn/builders/impl/squeeze_unsqueeze_op_builder.cc
index 0192e33f22d8d..8e6feb62fa8c4 100644
--- a/onnxruntime/core/providers/webnn/builders/impl/squeeze_unsqueeze_op_builder.cc
+++ b/onnxruntime/core/providers/webnn/builders/impl/squeeze_unsqueeze_op_builder.cc
@@ -58,7 +58,7 @@ Status SqueezeUnsqueezeOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_buil
   std::vector<int32_t> axes_data;
   auto rank = input_rank;
 
-  if (node.SinceVersion() >= 13 && input_defs.size() > 1 && !GetTensorName(input_defs, 1).empty()) {
+  if (node.SinceVersion() >= 13 && !GetTensorName(input_defs, 1).empty()) {
     // Input axes is provided, use axes initializer data.
     const auto& initializers = model_builder.GetInitializerTensors();
     const auto& axes_tensor = *initializers.at(input_defs[1]->Name());