diff --git a/build-tools/code_generator/function_types.yaml b/build-tools/code_generator/function_types.yaml
index c8c325353..cc33f9d7b 100644
--- a/build-tools/code_generator/function_types.yaml
+++ b/build-tools/code_generator/function_types.yaml
@@ -417,6 +417,9 @@ FixedPointQuantize:
 Pow2Quantize:
   float: [float]
   half: [Half]
+MinMaxQuantize:
+  float: [float]
+  half: [Half]
 TopNError:
   float: [float, int]
   half: [Half, int]
diff --git a/include/nbla/cuda/function/min_max_quantize.hpp b/include/nbla/cuda/function/min_max_quantize.hpp
new file mode 100644
index 000000000..b19694d40
--- /dev/null
+++ b/include/nbla/cuda/function/min_max_quantize.hpp
@@ -0,0 +1,48 @@
+// Copyright (c) 2017 Sony Corporation. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef NBLA_CUDA_FUNCTION_MIN_MAX_QUANTIZE_HPP
+#define NBLA_CUDA_FUNCTION_MIN_MAX_QUANTIZE_HPP
+
+#include <nbla/cuda/cuda.hpp>
+#include <nbla/function/min_max_quantize.hpp>
+
+namespace nbla {
+
+template <typename T> class MinMaxQuantizeCuda : public MinMaxQuantize<T> {
+public:
+  typedef typename CudaType<T>::type Tcu;
+
+  explicit MinMaxQuantizeCuda(const Context &ctx, float decay, bool train,
+                              bool ema, bool ste_fine_grained, float eps)
+      : MinMaxQuantize<T>(ctx, decay, train, ema, ste_fine_grained, eps),
+        device_(std::stoi(ctx.device_id)) {}
+  virtual ~MinMaxQuantizeCuda() {}
+  virtual string name() { return "MinMaxQuantizeCuda"; }
+  virtual vector<string> allowed_array_classes() {
+    return SingletonManager::get<Cuda>()->array_classes();
+  }
+
+protected:
+  int device_;
+  virtual void setup_impl(const Variables &inputs, const Variables &outputs);
+  NBLA_API virtual void nudge_range(Variable *qr_min, Variable *qr_max);
+  NBLA_API virtual void nudge_qr_min_max(Variable *qr_min, Variable *qr_max,
+                                         Variable *ql_min, Variable *ql_max,
+                                         Variable *scale,
+                                         Variable *qr_min_nudged,
+                                         Variable *qr_max_nudged);
+};
+}
+#endif
diff --git a/src/nbla/cuda/function/generic/min_max_quantize.cu b/src/nbla/cuda/function/generic/min_max_quantize.cu
new file mode 100644
index 000000000..fa3782f83
--- /dev/null
+++ b/src/nbla/cuda/function/generic/min_max_quantize.cu
@@ -0,0 +1,91 @@
+// Copyright (c) 2017 Sony Corporation. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <nbla/array.hpp>
+#include <nbla/cuda/common.hpp>
+#include <nbla/cuda/function/min_max_quantize.hpp>
+#include <nbla/variable.hpp>
+
+namespace nbla {
+
+template <typename T>
+void MinMaxQuantizeCuda<T>::setup_impl(const Variables &inputs,
+                                       const Variables &outputs) {
+  MinMaxQuantize<T>::setup_impl(inputs, outputs);
+  cuda_set_device(this->device_);
+}
+
+template <typename T>
+__global__ void kernel_nudge_range(const int size, float eps,
+                                   const T *qr_min_data, T *qr_max_data) {
+  NBLA_CUDA_KERNEL_LOOP(idx, size) {
+    if (qr_max_data[idx] - qr_min_data[idx] < eps) {
+      qr_max_data[idx] = qr_min_data[idx] + eps;
+    }
+  }
+}
+
+template <typename T>
+__global__ void
+kernel_nudge_qr_min_max(const int size, const T *qr_min_data,
+                        const T *qr_max_data, const T *ql_min_data,
+                        const T *ql_max_data, const T *scale_data,
+                        T *qr_min_nudged_data, T *qr_max_nudged_data) {
+  T zero_point_nudged = T(0.0);
+  T zero_point_from_min = T(0.0);
+  NBLA_CUDA_KERNEL_LOOP(idx, size) {
+    zero_point_from_min = ql_min_data[idx] - qr_min_data[idx] / scale_data[idx];
+    if (zero_point_from_min <= ql_min_data[idx]) {
+      zero_point_nudged = ql_min_data[idx];
+    } else if (zero_point_from_min >= ql_max_data[idx]) {
+      zero_point_nudged = ql_max_data[idx];
+    } else {
+      zero_point_nudged = round(zero_point_from_min);
+    }
+    qr_min_nudged_data[idx] =
+        (ql_min_data[idx] - zero_point_nudged) * scale_data[idx];
+    qr_max_nudged_data[idx] =
+        (ql_max_data[idx] - zero_point_nudged) * scale_data[idx];
+  }
+}
+
+template <typename T>
+void MinMaxQuantizeCuda<T>::nudge_range(Variable *qr_min, Variable *qr_max) {
+  const Tcu *qr_min_data = qr_min->get_data_pointer<Tcu>(this->ctx_);
+  Tcu *qr_max_data = qr_max->cast_data_and_get_pointer<Tcu>(this->ctx_);
+  NBLA_CUDA_LAUNCH_KERNEL_SIMPLE(kernel_nudge_range<Tcu>, qr_min->size(),
+                                 this->eps_, qr_min_data, qr_max_data);
+}
+
+template <typename T>
+void MinMaxQuantizeCuda<T>::nudge_qr_min_max(Variable *qr_min, Variable *qr_max,
+                                             Variable *ql_min, Variable *ql_max,
+                                             Variable *scale,
+                                             Variable *qr_min_nudged,
+                                             Variable *qr_max_nudged) {
+  const Tcu *qr_min_data = qr_min->get_data_pointer<Tcu>(this->ctx_);
+  const Tcu *qr_max_data = qr_max->get_data_pointer<Tcu>(this->ctx_);
+  const Tcu *ql_min_data = ql_min->get_data_pointer<Tcu>(this->ctx_);
+  const Tcu *ql_max_data = ql_max->get_data_pointer<Tcu>(this->ctx_);
+  const Tcu *scale_data = scale->get_data_pointer<Tcu>(this->ctx_);
+  Tcu *qr_min_nudged_data =
+      qr_min_nudged->cast_data_and_get_pointer<Tcu>(this->ctx_);
+  Tcu *qr_max_nudged_data =
+      qr_max_nudged->cast_data_and_get_pointer<Tcu>(this->ctx_);
+  NBLA_CUDA_LAUNCH_KERNEL_SIMPLE(kernel_nudge_qr_min_max<Tcu>, qr_min->size(),
+                                 qr_min_data, qr_max_data, ql_min_data,
+                                 ql_max_data, scale_data, qr_min_nudged_data,
+                                 qr_max_nudged_data);
+}
+}