diff --git a/onnxruntime/core/providers/webgpu/reduction/reduction_ops.cc b/onnxruntime/core/providers/webgpu/reduction/reduction_ops.cc
index 255ad9cdf66c6..1a56cafdb3952 100644
--- a/onnxruntime/core/providers/webgpu/reduction/reduction_ops.cc
+++ b/onnxruntime/core/providers/webgpu/reduction/reduction_ops.cc
@@ -38,12 +38,50 @@ REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMax, 1, 10);
 REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMax, 11, 11);
 REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMax, 12, 12);
 REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMax, 13, 17);
-REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceMax, 18);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMax, 18, 19);
+REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceMax, 20);
+
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMin, 1, 10);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMin, 11, 11);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMin, 12, 12);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMin, 13, 17);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceMin, 18, 19);
+REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceMin, 20);
 
 REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceSum, 1, 10);
 REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceSum, 11, 12);
 REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceSum, 13);
 
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceProd, 1, 10);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceProd, 11, 12);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceProd, 13, 17);
+REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceProd, 18);
+
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceL1, 1, 10);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceL1, 11, 12);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceL1, 13, 17);
+REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceL1, 18);
+
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceL2, 1, 10);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceL2, 11, 12);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceL2, 13, 17);
+REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceL2, 18);
+
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceLogSum, 1, 10);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceLogSum, 11, 12);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceLogSum, 13, 17);
+REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceLogSum, 18);
+
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceSumSquare, 1, 10);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceSumSquare, 11, 12);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceSumSquare, 13, 17);
+REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceSumSquare, 18);
+
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceLogSumExp, 1, 10);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceLogSumExp, 11, 12);
+REGISTER_UNARY_ELEMENTWISE_VERSIONED_KERNEL(ReduceLogSumExp, 13, 17);
+REGISTER_UNARY_ELEMENTWISE_KERNEL(ReduceLogSumExp, 18);
+
 Status ReduceKernelProgram::GenerateShaderCode(ShaderHelper& shader) const {
   const auto& output = shader.AddOutput("output", ShaderUsage::UseUniform | ShaderUsage::UseIndicesTypeAlias | ShaderUsage::UseValueTypeAlias);
   if (is_input_empty_) {
@@ -126,14 +164,28 @@ Status ReduceKernel<allow_multi_axes>::ComputeInternal(ComputeContext& context)
   if (input_axes.empty()) {
     if (noop_with_empty_axes_ || rank == 0) {
       // If axes is empty and noop_with_empty_axes_ is true, it is a no-op according to the spec
-      // If input tensor is a scalar, return the input tensor as is.
-      // This is not correct for ReduceLogSum and ReduceSumSquare
-      // TODO handle these cases separately.
-      auto output = context.Output(0, input_tensor->Shape());
-      if (output->DataRaw() != input_tensor->DataRaw()) {
-        ORT_RETURN_IF_ERROR(Info().GetDataTransferManager().CopyTensor(*input_tensor, *output));
+      // If input tensor is a scalar and it's not a ReduceLogSum or ReduceSumSquare, return the input tensor as is.
+      if (rank == 0 && (name_ == "ReduceLogSum" || name_ == "ReduceSumSquare" || name_ == "ReduceL1" || name_ == "ReduceL2")) {
+        // For ReduceLogSum with scalar input, output = log(input)
+        // For ReduceSumSquare with scalar input, output = input * input
+        auto output = context.Output(0, input_tensor->Shape());
+        // We need to run the operation even for scalar inputs for these ops
+        const auto code = GetOpSpecificCode(input_tensor);
+        ReduceKernelProgram program(name_, keepdims_, noop_with_empty_axes_, input_axes, code, false);
+        std::vector<uint32_t> reduce_axes = {0};
+        program.AddInput({input_tensor, ProgramTensorMetadataDependency::TypeAndRank})
+            .AddOutput({output, ProgramTensorMetadataDependency::TypeAndRank})
+            .SetDispatchGroupSize(1)
+            .AddUniformVariables({{1}, {static_cast<uint32_t>(noop_with_empty_axes_ ? 1 : 0)}, {reduce_axes}});
+        return context.RunProgram(program);
+      } else {
+        // For other ops, or when axes is empty with noop_with_empty_axes_ true, just copy the input
+        auto output = context.Output(0, input_tensor->Shape());
+        if (output->DataRaw() != input_tensor->DataRaw()) {
+          ORT_RETURN_IF_ERROR(Info().GetDataTransferManager().CopyTensor(*input_tensor, *output));
+        }
+        return Status::OK();
       }
-      return Status::OK();
     } else {
       // If axes is empty and noop_with_empty_axes_ is false, it is a reduction over all axes
       input_axes.resize(rank);
@@ -211,6 +263,14 @@ ReduceOpSpecificCode ReduceMax::GetOpSpecificCode(const Tensor* input_tensor) co
   ReduceOpSpecificCode code({loop_header, loop_body, loop_footer});
   return code;
 }
+ReduceOpSpecificCode ReduceMin::GetOpSpecificCode(const Tensor* input_tensor) const {
+  ORT_UNUSED_PARAMETER(input_tensor);
+  std::string loop_header = "var min_element = first_element;";
+  std::string loop_body = "min_element = min(min_element, current_element);";
+  std::string loop_footer = "let output_value = output_value_t(min_element);";
+  ReduceOpSpecificCode code({loop_header, loop_body, loop_footer});
+  return code;
+}
 ReduceOpSpecificCode ReduceSum::GetOpSpecificCode(const Tensor* input_tensor) const {
   ORT_UNUSED_PARAMETER(input_tensor);
   std::string loop_header = "var sum = f32(0);";
@@ -219,6 +279,54 @@ ReduceOpSpecificCode ReduceSum::GetOpSpecificCode(const Tensor* input_tensor) co
   ReduceOpSpecificCode code({loop_header, loop_body, loop_footer});
   return code;
 }
+ReduceOpSpecificCode ReduceProd::GetOpSpecificCode(const Tensor* input_tensor) const {
+  ORT_UNUSED_PARAMETER(input_tensor);
+  std::string loop_header = "var prod = f32(1);";
+  std::string loop_body = "prod *= f32(current_element);";
+  std::string loop_footer = "let output_value = output_value_t(prod);";
+  ReduceOpSpecificCode code({loop_header, loop_body, loop_footer});
+  return code;
+}
+ReduceOpSpecificCode ReduceL1::GetOpSpecificCode(const Tensor* input_tensor) const {
+  ORT_UNUSED_PARAMETER(input_tensor);
+  std::string loop_header = "var l1 = f32(0);";
+  std::string loop_body = "l1 += abs(f32(current_element));";
+  std::string loop_footer = "let output_value = output_value_t(l1);";
+  ReduceOpSpecificCode code({loop_header, loop_body, loop_footer});
+  return code;
+}
+ReduceOpSpecificCode ReduceL2::GetOpSpecificCode(const Tensor* input_tensor) const {
+  ORT_UNUSED_PARAMETER(input_tensor);
+  std::string loop_header = "var l2 = f32(0);";
+  std::string loop_body = "let t = f32(current_element); l2 += (t * t);";
+  std::string loop_footer = "l2 = sqrt(l2); let output_value = output_value_t(l2);";
+  ReduceOpSpecificCode code({loop_header, loop_body, loop_footer});
+  return code;
+}
+ReduceOpSpecificCode ReduceLogSum::GetOpSpecificCode(const Tensor* input_tensor) const {
+  ORT_UNUSED_PARAMETER(input_tensor);
+  std::string loop_header = "var sum = f32(0);";
+  std::string loop_body = "sum += f32(current_element);";
+  std::string loop_footer = "let log_sum = log(sum); let output_value = output_value_t(log_sum);";
+  ReduceOpSpecificCode code({loop_header, loop_body, loop_footer});
+  return code;
+}
+ReduceOpSpecificCode ReduceSumSquare::GetOpSpecificCode(const Tensor* input_tensor) const {
+  ORT_UNUSED_PARAMETER(input_tensor);
+  std::string loop_header = "var sum_square = f32(0);";
+  std::string loop_body = "let t = f32(current_element); sum_square += (t * t);";
+  std::string loop_footer = "let output_value = output_value_t(sum_square);";
+  ReduceOpSpecificCode code({loop_header, loop_body, loop_footer});
+  return code;
+}
+ReduceOpSpecificCode ReduceLogSumExp::GetOpSpecificCode(const Tensor* input_tensor) const {
+  ORT_UNUSED_PARAMETER(input_tensor);
+  std::string loop_header = "var sum_exp = f32(0);";
+  std::string loop_body = "sum_exp += exp(f32(current_element));";
+  std::string loop_footer = "let log_sum_exp = log(sum_exp); let output_value = output_value_t(log_sum_exp);";
+  ReduceOpSpecificCode code({loop_header, loop_body, loop_footer});
+  return code;
+}
 
 }  // namespace webgpu
-}  // namespace onnxruntime
+}  // namespace onnxruntime
\ No newline at end of file
diff --git a/onnxruntime/core/providers/webgpu/reduction/reduction_ops.h b/onnxruntime/core/providers/webgpu/reduction/reduction_ops.h
index 1c7dba89b7144..291d931f41c05 100644
--- a/onnxruntime/core/providers/webgpu/reduction/reduction_ops.h
+++ b/onnxruntime/core/providers/webgpu/reduction/reduction_ops.h
@@ -71,11 +71,53 @@ class ReduceMax final : public ReduceKernel<true> {
   ReduceOpSpecificCode GetOpSpecificCode(const Tensor* input_tensor) const override;
 };
 
+class ReduceMin final : public ReduceKernel<true> {
+ public:
+  ReduceMin(const OpKernelInfo& info) : ReduceKernel<true>(info, "ReduceMin") {}
+  ReduceOpSpecificCode GetOpSpecificCode(const Tensor* input_tensor) const override;
+};
+
 class ReduceSum final : public ReduceKernel<true> {
  public:
   ReduceSum(const OpKernelInfo& info) : ReduceKernel<true>(info, "ReduceSum", true) {}
   ReduceOpSpecificCode GetOpSpecificCode(const Tensor* input_tensor) const override;
 };
 
+class ReduceProd final : public ReduceKernel<true> {
+ public:
+  ReduceProd(const OpKernelInfo& info) : ReduceKernel<true>(info, "ReduceProd", true) {}
+  ReduceOpSpecificCode GetOpSpecificCode(const Tensor* input_tensor) const override;
+};
+
+class ReduceL1 final : public ReduceKernel<true> {
+ public:
+  ReduceL1(const OpKernelInfo& info) : ReduceKernel<true>(info, "ReduceL1", true) {}
+  ReduceOpSpecificCode GetOpSpecificCode(const Tensor* input_tensor) const override;
+};
+
+class ReduceL2 final : public ReduceKernel<true> {
+ public:
+  ReduceL2(const OpKernelInfo& info) : ReduceKernel<true>(info, "ReduceL2", true) {}
+  ReduceOpSpecificCode GetOpSpecificCode(const Tensor* input_tensor) const override;
+};
+
+class ReduceLogSum final : public ReduceKernel<true> {
+ public:
+  ReduceLogSum(const OpKernelInfo& info) : ReduceKernel<true>(info, "ReduceLogSum", true) {}
+  ReduceOpSpecificCode GetOpSpecificCode(const Tensor* input_tensor) const override;
+};
+
+class ReduceSumSquare final : public ReduceKernel<true> {
+ public:
+  ReduceSumSquare(const OpKernelInfo& info) : ReduceKernel<true>(info, "ReduceSumSquare", true) {}
+  ReduceOpSpecificCode GetOpSpecificCode(const Tensor* input_tensor) const override;
+};
+
+class ReduceLogSumExp final : public ReduceKernel<true> {
+ public:
+  ReduceLogSumExp(const OpKernelInfo& info) : ReduceKernel<true>(info, "ReduceLogSumExp", true) {}
+  ReduceOpSpecificCode GetOpSpecificCode(const Tensor* input_tensor) const override;
+};
+
 }  // namespace webgpu
 }  // namespace onnxruntime
diff --git a/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc b/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc
index 0ff07f0581475..71d46bc4fb2cc 100644
--- a/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc
+++ b/onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc
@@ -144,7 +144,8 @@ class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxD
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 11, ReduceMax);
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 12, 12, ReduceMax);
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceMax);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceMax);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, 19, ReduceMax);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 20, ReduceMax);
 
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceMean);
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceMean);
@@ -155,7 +156,8 @@ class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxD
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 11, ReduceMin);
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 12, 12, ReduceMin);
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceMin);
-class ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceMin);
+class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, 19, ReduceMin);
+class ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 20, ReduceMin);
 
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceProd);
 class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceProd);
@@ -517,7 +519,8 @@ std::unique_ptr<KernelRegistry> RegisterKernels() {
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 11, ReduceMax)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 12, 12, ReduceMax)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceMax)>,
-      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceMax)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, 19, ReduceMax)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 20, ReduceMax)>,
 
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceMean)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceMean)>,
@@ -528,45 +531,46 @@ std::unique_ptr<KernelRegistry> RegisterKernels() {
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, Unsqueeze)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, Unsqueeze)>,
 
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceMin)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 11, ReduceMin)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 12, 12, ReduceMin)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceMin)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceMin)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceMin)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 11, ReduceMin)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 12, 12, ReduceMin)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceMin)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, 19, ReduceMin)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 20, ReduceMin)>,
 
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceProd)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceProd)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceProd)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceProd)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceProd)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceProd)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceProd)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceProd)>,
 
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceSum)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceSum)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, ReduceSum)>,
 
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceL1)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceL1)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceL1)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceL1)>,
-
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceL2)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceL2)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceL2)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceL2)>,
-
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceLogSum)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceLogSum)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceLogSum)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceLogSum)>,
-
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceSumSquare)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceSumSquare)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceSumSquare)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceSumSquare)>,
-
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceLogSumExp)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceLogSumExp)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceLogSumExp)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceLogSumExp)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceL1)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceL1)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceL1)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceL1)>,
+
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceL2)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceL2)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceL2)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceL2)>,
+
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceLogSum)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceLogSum)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceLogSum)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceLogSum)>,
+
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceSumSquare)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceSumSquare)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceSumSquare)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceSumSquare)>,
+
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 10, ReduceLogSumExp)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, ReduceLogSumExp)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 17, ReduceLogSumExp)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 18, ReduceLogSumExp)>,
 
       KERNEL_CREATE_INFO_VERSIONED(9, 15, Where),
       KERNEL_CREATE_INFO(16, Where),
diff --git a/onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc b/onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc
index 61a16d41e3e59..4bc97d035c7f7 100644
--- a/onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc
+++ b/onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc
@@ -6044,6 +6044,7 @@ void test_empty_set(const std::string& op, int opset, bool axes_as_input, float
           kQnnExecutionProvider,
           kRocmExecutionProvider,
           kTensorrtExecutionProvider,
+          kWebGpuExecutionProvider,
       });
 }