diff --git a/onnxruntime/core/providers/cpu/cpu_execution_provider.cc b/onnxruntime/core/providers/cpu/cpu_execution_provider.cc
index 22b0d0ce60..8968d499d2 100644
--- a/onnxruntime/core/providers/cpu/cpu_execution_provider.cc
+++ b/onnxruntime/core/providers/cpu/cpu_execution_provider.cc
@@ -289,6 +289,7 @@ class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOn
 class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, ThresholdedRelu);
 class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, 12, uint8_t, DequantizeLinear);
 class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, 12, int8_t, DequantizeLinear);
+class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, 12, int32_t, DequantizeLinear);
 class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, 12, uint8_t, QuantizeLinear);
 class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, 12, int8_t, QuantizeLinear);
 class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, QLinearMatMul);
@@ -446,6 +447,7 @@ class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, Ca
 class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, Clip);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint8_t, DequantizeLinear);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int8_t, DequantizeLinear);
+class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int32_t, DequantizeLinear);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, float, Expand);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, double, Expand);
 class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int8_t, Expand);
@@ -1066,6 +1068,8 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
                                                                             DequantizeLinear)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, 12, int8_t,
                                                                             DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, 12, int32_t,
+                                                                            DequantizeLinear)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, 12, uint8_t,
                                                                             QuantizeLinear)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 10, 12, int8_t,
@@ -1362,6 +1366,8 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
                                                                   DequantizeLinear)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int8_t,
                                                                   DequantizeLinear)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int32_t,
+                                                                  DequantizeLinear)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, uint8_t,
                                                                   QuantizeLinear)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 13, int8_t,
diff --git a/onnxruntime/core/providers/cpu/tensor/quantize_linear.cc b/onnxruntime/core/providers/cpu/tensor/quantize_linear.cc
index 5cfa4d1887..7c1f481d2c 100644
--- a/onnxruntime/core/providers/cpu/tensor/quantize_linear.cc
+++ b/onnxruntime/core/providers/cpu/tensor/quantize_linear.cc
@@ -59,11 +59,13 @@ static void PrepareForQDQ(const TensorShape& input_shape,
 
 REGISTER_DEQUANTIZELINEAR(int8_t)
 REGISTER_DEQUANTIZELINEAR(uint8_t)
+REGISTER_DEQUANTIZELINEAR(int32_t)
 REGISTER_DEQUANTIZELINEAR_VERSIONED(int8_t)
 REGISTER_DEQUANTIZELINEAR_VERSIONED(uint8_t)
+REGISTER_DEQUANTIZELINEAR_VERSIONED(int32_t)
 
-template <typename T>
 // formula is Y = (X - ZeroPoint) * Scale
+template <typename T>
 Status DequantizeLinear<T>::Compute(OpKernelContext* ctx) const {
   auto& x = *ctx->Input<Tensor>(0);
   auto& x_scale = *ctx->Input<Tensor>(1);
@@ -78,11 +80,19 @@ Status DequantizeLinear<T>::Compute(OpKernelContext* ctx) const {
 
   PrepareForQDQ(x.Shape(), x_scale, x_zero_point, axis_, N, broadcast_dim, block_size);
 
-  const T* zero_point = x_zero_point ? x_zero_point->template Data<T>() : nullptr;
   const float* scale = x_scale.template Data<float>();
   const T* input = x.template Data<T>();
   float* output = y.template MutableData<float>();
 
+  const T* zero_point = x_zero_point ? x_zero_point->template Data<T>() : nullptr;
+  if (std::is_same<T, int32_t>::value) {
+    ORT_ENFORCE(zero_point == nullptr ||
+                    std::all_of(zero_point,
+                                zero_point + x_zero_point->Shape().Size(),
+                                [](int32_t zp) { return zp == 0; }),
+                "DequantizeLinear with type int32 should have no zero point or all zero points should be 0");
+  }
+
   for (size_t n = 0; n < static_cast<size_t>(N); n++) {
     for (size_t bd = 0; bd < static_cast<size_t>(broadcast_dim); bd++) {
       auto zp = zero_point ? static_cast<int32_t>(zero_point[bd]) : 0;
@@ -123,8 +133,8 @@ REGISTER_QUANTIZELINEAR(uint8_t)
 REGISTER_QUANTIZELINEAR_VERSIONED(int8_t)
 REGISTER_QUANTIZELINEAR_VERSIONED(uint8_t)
 
-template <typename T>
 // formula is Y = X / Scale + ZeroPoint
+template <typename T>
 Status QuantizeLinear<T>::Compute(OpKernelContext* ctx) const {
   auto& x = *ctx->Input<Tensor>(0);
   auto& y_scale = *ctx->Input<Tensor>(1);
diff --git a/onnxruntime/test/providers/cpu/tensor/quantize_linear_test.cc b/onnxruntime/test/providers/cpu/tensor/quantize_linear_test.cc
index 8a85330ce9..716b7240de 100644
--- a/onnxruntime/test/providers/cpu/tensor/quantize_linear_test.cc
+++ b/onnxruntime/test/providers/cpu/tensor/quantize_linear_test.cc
@@ -28,6 +28,16 @@ TEST(DequantizeLinearOpTest, Int8) {
   test.Run();
 }
 
+// scalar zero & scale with int8
+TEST(DequantizeLinearOpTest, Int32) {
+  OpTester test("DequantizeLinear", 10);
+  std::vector<int64_t> dims{4};
+  test.AddInput<int32_t>("x", dims, {-30, -3, 100, 127});
+  test.AddInput<float>("x_scale", {}, {2.0f});
+  test.AddOutput<float>("y", dims, {-60.f, -6.f, 200.f, 254.f});
+  test.Run();
+}
+
 // 2d inputs
 TEST(DequantizeLinearOpTest, 2D) {
   OpTester test("DequantizeLinear", 10);
@@ -134,7 +144,7 @@ TEST(DequantizeLinearOpTest, Per_Channel_Axis_0) {
 }
 
 // 1d zero & scale with int8 broadcast axis 1
-TEST(DequantizeLinearOpTest, Per_Channel_Axis_1) {
+TEST(DequantizeLinearOpTest, Per_Channel_Axis_1_int8) {
   OpTester test("DequantizeLinear", 13);
   std::vector<int64_t> dims{3, 4};
   test.AddInput<int8_t>("X", dims,
@@ -151,6 +161,24 @@ TEST(DequantizeLinearOpTest, Per_Channel_Axis_1) {
   test.Run();
 }
 
+// 1d zero & scale with int32 broadcast axis 1
+TEST(DequantizeLinearOpTest, Per_Channel_Axis_1_int32) {
+  OpTester test("DequantizeLinear", 13);
+  std::vector<int64_t> dims{3, 4};
+  test.AddInput<int32_t>("X", dims,
+                        {0, 1, 2, 3,
+                         0, 2, 4, 6,
+                         0, 10, 20, 30});
+  test.AddAttribute<int64_t>("axis", 1);
+  test.AddInput<float>("scale", {4}, {1, 2, 4, 8});
+  test.AddInput<int32_t>("zero_point", {4}, {0, 0, 0, 0});
+  test.AddOutput<float>("Y", dims,
+                        {0, 2, 8, 24,
+                         0, 4, 16, 48,
+                         0, 20, 80, 240});
+  test.Run();
+}
+
 // 1d zero & scale with uint8 broadcast axis -2 (-2 resolves to axis 0)
 TEST(DequantizeLinearOpTest, Per_Channel_Neg_2) {
   OpTester test("DequantizeLinear", 13);