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diff --git a/compiler/mir-interpreter/src/ops/ReduceMean.cpp b/compiler/mir-interpreter/src/ops/ReduceMean.cpp
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+++ b/compiler/mir-interpreter/src/ops/ReduceMean.cpp
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+/*
+ * Copyright (c) 2020 Samsung Electronics Co., Ltd. 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 _NNC_CORE_BACKEND_INTERPRETER_REDUCE_MEAN_
+#define _NNC_CORE_BACKEND_INTERPRETER_REDUCE_MEAN_
+
+#include "ReduceMean.h"
+#include "Common.h"
+
+#include "mir/ops/ReduceMeanOp.h"
+#include "mir/Tensor.h"
+#include "mir/ShapeRange.h"
+
+namespace mir_interpreter
+{
+
+template <typename T> struct ReduceMeanImpl
+{
+  static void run(const mir::TensorVariant &inputv, const mir::ops::ReduceMeanOp &op,
+                  mir::TensorVariant &output);
+};
+
+template <typename T>
+void ReduceMeanImpl<T>::run(const mir::TensorVariant &inputv, const mir::ops::ReduceMeanOp &op,
+                            mir::TensorVariant &output)
+{
+  const auto &input_shape = op.getInputShape(0);
+  const auto &output_shape = op.getOutputShape(0);
+  const auto &reduction_dims = op.getReductionDims();
+  const bool keep_dims = op.getKeepDims();
+
+  const auto reductor = [](T result, T x) { return result + x; };
+
+  mir::Tensor<T> input(inputv);
+  mir::Tensor<T> res_accessor(output);
+
+  erase<T>(output);
+
+  // This mask contains 'true' for dimensions that should be reduced. For example, if we want
+  // to reduce dimensions 1 and 3 with total number of dimensions of 4, the mask will be
+  // [false, true, false, true].
+  std::vector<bool> reduction_dims_mask(input_shape.rank(), false);
+  for (const int dim : reduction_dims)
+  {
+    reduction_dims_mask[dim] = true;
+  }
+
+  mir::Index out_index(output_shape.rank());
+  for (const mir::Index &in_index : mir::ShapeRange(input_shape))
+  {
+    int out_index_dim = 0;
+    for (int dim = 0; dim < input_shape.rank(); ++dim)
+    {
+      if (keep_dims)
+      {
+        out_index.at(out_index_dim++) = reduction_dims_mask[dim] ? 0 : in_index.at(dim);
+      }
+      else
+      {
+        if (!reduction_dims_mask[dim])
+        {
+          out_index.at(out_index_dim++) = in_index.at(dim);
+        }
+      }
+    }
+    res_accessor.at(out_index) = reductor(res_accessor.at(out_index), input.at(in_index));
+  }
+
+  const std::int32_t reduction_factor = input_shape.numElements() / output_shape.numElements();
+
+  for (const auto &index : mir::ShapeRange(output_shape))
+  {
+    res_accessor.at(index) /= reduction_factor;
+  }
+}
+
+void ReduceMean(const mir::TensorVariant &input, const mir::ops::ReduceMeanOp &op,
+                mir::TensorVariant &output)
+{
+  dispatch<ReduceMeanImpl>(input.getElementType(), input, op, output);
+};
+
+} // namespace mir_interpreter
+
+#endif //_NNC_CORE_BACKEND_INTERPRETER_REDUCE_MEAN_