diff --git a/onnxruntime/core/providers/webgpu/math/binary_elementwise_ops.cc b/onnxruntime/core/providers/webgpu/math/binary_elementwise_ops.cc
index 13004af25726d..6891b8159b090 100644
--- a/onnxruntime/core/providers/webgpu/math/binary_elementwise_ops.cc
+++ b/onnxruntime/core/providers/webgpu/math/binary_elementwise_ops.cc
@@ -4,15 +4,18 @@
 #include "core/providers/common.h"
 #include "core/providers/webgpu/math/binary_elementwise_ops.h"
 #include "core/providers/webgpu/shader_helper.h"
+#include "core/providers/webgpu/string_macros.h"
 #include "core/providers/webgpu/webgpu_supported_types.h"
 
 namespace onnxruntime {
 namespace webgpu {
 Status BinaryElementwiseProgram::GenerateShaderCode(ShaderHelper& shader) const {
-  const auto& a = shader.AddInput("input_a", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias);
-  const auto& b = shader.AddInput("input_b", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias);
+  const auto& a = shader.AddInput("input_a", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias | ShaderUsage::UseElementTypeAlias);
+  const auto& b = shader.AddInput("input_b", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias | ShaderUsage::UseElementTypeAlias);
   const auto& c = shader.AddOutput("output", ShaderUsage::UseUniform | ShaderUsage::UseValueTypeAlias);
 
+  shader.AdditionalImplementation() << additional_impl_;
+
   shader.MainFunctionBody() << shader.GuardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size");
 
   // check whether can use element-wise mode.
@@ -142,8 +145,15 @@ Status BinaryElementwise::ComputeInternal(ComputeContext& context) const {
   }
 
   uint32_t vec_size = onnxruntime::narrow<uint32_t>((size + 3) / 4);
+
+  std::string additional_impl;
+  if (get_additional_impl_) {
+    additional_impl = get_additional_impl_(lhs_tensor->GetElementType(), rhs_tensor->GetElementType());
+  }
+
   BinaryElementwiseProgram program{kernel_name_,
                                    expression_,
+                                   additional_impl,
                                    is_broadcast,
                                    is_lhs_scalar,
                                    is_rhs_scalar,
@@ -273,7 +283,28 @@ WEBGPU_BINARY_VERSIONED_KERNEL(Sub, 7, 12, Sub, WebGpuSupportedNumberTypes())
 WEBGPU_BINARY_VERSIONED_KERNEL(Sub, 13, 13, Sub, WebGpuSupportedNumberTypes())
 WEBGPU_BINARY_KERNEL(Sub, 14, Sub, WebGpuSupportedNumberTypes())
 
-WEBGPU_BINARY_IMPL(Pow, "output_value_t(pow(vec4<f32>(a), vec4<f32>(b)))")
+std::string GetPowImpl(int lhs_element_type, int /* rhs_element_type */) {
+  SS(s, 1024);
+  std::string round_str;
+  if (lhs_element_type == ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32) {
+    round_str = "round";
+  }
+
+  s << "fn pow_custom(a : input_a_element_t, b : f32) -> input_a_element_t {\n"
+       "  if (b == 0.0) {\n"
+       "    return input_a_element_t(1.0);\n"
+       "  } else if (a < input_a_element_t(0.0) && b != floor(b)) {\n"
+       "    return input_a_element_t(pow(f32(a), b)); // NaN\n"
+       "  }\n"
+    << "  return select(sign(a), input_a_element_t(1.0), round(abs(b) % 2.0) != 1.0) * input_a_element_t(" << round_str << "(pow(f32(abs(a)), b)));\n"
+    << "}\n"
+       "fn pow_v(a : vec4<input_a_element_t>, b : vec4<input_b_element_t>) -> vec4<input_a_element_t> {\n"
+       "  return vec4<input_a_element_t>(pow_custom(a.x, f32(b.x)), pow_custom(a.y, f32(b.y)), pow_custom(a.z, f32(b.z)), pow_custom(a.w, f32(b.w)));\n"
+       "}\n";
+  return SS_GET(s);
+}
+
+WEBGPU_BINARY_IMPL(Pow, "pow_v(a, b)", GetPowImpl)
 WEBGPU_BINARY_VERSIONED_KERNEL(Pow, 7, 11, Pow, WebGpuSupportedNumberTypes())
 WEBGPU_BINARY_VERSIONED_KERNEL_2(Pow, 12, 12, Pow, WebGpuSupportedNumberTypes(), WebGpuSupportedNumberTypes())
 WEBGPU_BINARY_VERSIONED_KERNEL_2(Pow, 13, 14, Pow, WebGpuSupportedNumberTypes(), WebGpuSupportedNumberTypes())
diff --git a/onnxruntime/core/providers/webgpu/math/binary_elementwise_ops.h b/onnxruntime/core/providers/webgpu/math/binary_elementwise_ops.h
index 84cbcdf3244d8..f80accfb934f8 100644
--- a/onnxruntime/core/providers/webgpu/math/binary_elementwise_ops.h
+++ b/onnxruntime/core/providers/webgpu/math/binary_elementwise_ops.h
@@ -14,11 +14,13 @@ class BinaryElementwiseProgram final : public Program<BinaryElementwiseProgram>
  public:
   BinaryElementwiseProgram(const std::string& kernel_name,
                            const std::string& expression,
+                           const std::string& additional_impl,
                            const bool is_broadcast,
                            const bool is_lhs_scalar,
                            const bool is_rhs_scalar,
                            const bool vectorize) : Program{kernel_name},
                                                    expression_{expression},
+                                                   additional_impl_{additional_impl},
                                                    is_broadcast_{is_broadcast},
                                                    is_lhs_scalar_{is_lhs_scalar},
                                                    is_rhs_scalar_{is_rhs_scalar},
@@ -29,7 +31,8 @@ class BinaryElementwiseProgram final : public Program<BinaryElementwiseProgram>
   WEBGPU_PROGRAM_DEFINE_UNIFORM_VARIABLES({"vec_size", ProgramUniformVariableDataType::Uint32});
 
  private:
-  std::string expression_;
+  std::string_view expression_;
+  std::string_view additional_impl_;
   bool is_broadcast_;
   bool is_lhs_scalar_;
   bool is_rhs_scalar_;
@@ -38,11 +41,15 @@ class BinaryElementwiseProgram final : public Program<BinaryElementwiseProgram>
 
 class BinaryElementwise : public WebGpuKernel {
  public:
+  using GetAdditionalImplementationFunction = std::string (*)(int lhs_element_type, int rhs_element_type);
+
   BinaryElementwise(const OpKernelInfo& info,
                     const std::string& kernel_name,
-                    const std::string& expression) : WebGpuKernel{info},
-                                                     kernel_name_{kernel_name},
-                                                     expression_{expression} {}
+                    const std::string& expression,
+                    const GetAdditionalImplementationFunction get_additional_impl = nullptr) : WebGpuKernel{info},
+                                                                                               kernel_name_{kernel_name},
+                                                                                               expression_{expression},
+                                                                                               get_additional_impl_{get_additional_impl} {}
 
  protected:
   Status ComputeInternal(ComputeContext& context) const final;
@@ -50,6 +57,7 @@ class BinaryElementwise : public WebGpuKernel {
  private:
   std::string kernel_name_;
   std::string expression_;
+  const GetAdditionalImplementationFunction get_additional_impl_;
 };
 
 }  // namespace webgpu