diff --git a/tensorflow/lite/kernels/internal/reference/reverse.h b/tensorflow/lite/kernels/internal/reference/reverse.h
new file mode 100644
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+++ b/tensorflow/lite/kernels/internal/reference/reverse.h
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+/* Copyright 2025 The TensorFlow Authors. 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 TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_REVERSE_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_REVERSE_H_
+
+#include <algorithm>
+#include <array>
+#include <cstdint>
+
+#include "ruy/profiler/instrumentation.h"  // from @ruy
+#include "tensorflow/lite/kernels/internal/runtime_shape.h"
+
+namespace tflite {
+namespace reference_ops {
+
+template <typename Scalar>
+void Reverse(std::array<int32_t, 8>& axes, int num_axes,
+             const RuntimeShape& input_shape, const Scalar* input_data,
+             Scalar* output_data) {
+  ruy::profiler::ScopeLabel label("Reverse");
+  bool is_upper = (axes[num_axes - 1] == input_shape.DimensionsCount() - 1);
+  bool is_lower = (axes[0] == 0);
+  int rank = input_shape.DimensionsCount();
+  if (is_upper && is_lower) {
+    std::reverse_copy(input_data, input_data + input_shape.FlatSize(),
+                      output_data);
+    return;
+  } else {
+    int32_t min_dim = axes[0];
+    int32_t max_dim = axes[num_axes - 1];
+    int upper_size = 1;
+    for (int i = 0; i < min_dim; ++i) {
+      upper_size *= input_shape.Dims(i);
+    }
+    int lower_size = 1;
+    for (int i = max_dim + 1; i < rank; ++i) {
+      lower_size *= input_shape.Dims(i);
+    }
+    int middle_size = 1;
+    for (int i = min_dim; i <= max_dim; ++i) {
+      middle_size *= input_shape.Dims(i);
+    }
+
+    if (lower_size > 1) {
+      for (int i = 0; i < upper_size; ++i) {
+        for (int j = 0; j < middle_size; ++j) {
+          Scalar* src =
+              (Scalar*)input_data + (i * (middle_size) + j) * lower_size;
+          Scalar* dst =
+              (Scalar*)output_data +
+              (i * (middle_size) + (middle_size - j - 1)) * lower_size;
+          memcpy(dst, src, lower_size * sizeof(Scalar));
+        }
+      }
+    } else {
+      for (int i = 0; i < upper_size; ++i) {
+        std::reverse_copy(input_data + i * (middle_size),
+                          input_data + i * middle_size + middle_size,
+                          output_data + i * (middle_size));
+      }
+    }
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_REVERSE_H_