diff --git a/mindspore/lite/src/runtime/kernel/arm/fp16/transpose_fp16.cc b/mindspore/lite/src/runtime/kernel/arm/fp16/transpose_fp16.cc
new file mode 100644
index 0000000000..1094446ba6
--- /dev/null
+++ b/mindspore/lite/src/runtime/kernel/arm/fp16/transpose_fp16.cc
@@ -0,0 +1,156 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/runtime/kernel/arm/fp16/transpose_fp16.h"
+#include <vector>
+#include "src/runtime/kernel/arm/nnacl/fp16/transpose_fp16.h"
+#include "schema/model_generated.h"
+#include "src/kernel_registry.h"
+#include "include/errorcode.h"
+#include "src/runtime/runtime_api.h"
+#include "nnacl/fp16/cast_fp16.h"
+
+using mindspore::lite::KernelRegistrar;
+using mindspore::lite::RET_ERROR;
+using mindspore::lite::RET_OK;
+using mindspore::lite::RET_OP_EXECUTE_FAILURE;
+using mindspore::schema::PrimitiveType_Transpose;
+
+namespace mindspore::kernel {
+namespace {
+constexpr int kTransposeInputNum = 1;
+constexpr int kTransposeOutputNum = 1;
+}  // namespace
+int TransposeFp16CPUKernel::Init() {
+  TransposeParameter *param = reinterpret_cast<TransposeParameter *>(this->op_parameter_);
+  num_unit_ = static_cast<int>(in_tensors_[kInputIndex]->shape().at(param->perm_[kNHWC_H]));
+  thread_h_num_ = MSMIN(thread_num_, num_unit_);
+  thread_h_stride_ = UP_DIV(num_unit_, thread_h_num_);
+  if (!InferShapeDone()) {
+    return RET_OK;
+  }
+  return ReSize();
+}
+
+int TransposeFp16CPUKernel::ReSize() {
+  auto &inTensor = in_tensors_.front();
+  auto &outTensor = out_tensors_.front();
+  auto param = reinterpret_cast<TransposeParameter *>(op_parameter_);
+  auto in_shape = inTensor->shape();
+  auto out_shape = outTensor->shape();
+  param->strides_[param->num_axes_ - 1] = 1;
+  param->out_strides_[param->num_axes_ - 1] = 1;
+  param->data_size_ = inTensor->Size();
+  for (int i = param->num_axes_ - 2; i >= 0; i--) {
+    param->strides_[i] = in_shape[i + 1] * param->strides_[i + 1];
+    param->out_strides_[i] = out_shape[i + 1] * param->out_strides_[i + 1];
+  }
+
+  if (fp16_in_data_ != nullptr) {
+    free(fp16_in_data_);
+    fp16_in_data_ = nullptr;
+  }
+  fp16_in_data_ = reinterpret_cast<float16_t *>(malloc(sizeof(float16_t) * inTensor->ElementsNum()));
+  if (fp16_out_data_ != nullptr) {
+    free(fp16_out_data_);
+    fp16_out_data_ = nullptr;
+  }
+  fp16_out_data_ = reinterpret_cast<float16_t *>(malloc(sizeof(float16_t) * outTensor->ElementsNum()));
+  return RET_OK;
+}
+
+int TransposeFp16CPUKernel::TransposeParallel(int task_id) {
+  int num_unit_thread = MSMIN(thread_h_stride_, num_unit_ - task_id * thread_h_stride_);
+  if (num_unit_thread <= 0) {
+    return RET_OK;
+  }
+  int thread_offset = task_id * thread_h_stride_;
+  TransposeParameter *param = reinterpret_cast<TransposeParameter *>(this->op_parameter_);
+  auto ret = DoTranspose(fp16_in_data_, fp16_out_data_, in_shape_, out_shape_, param, thread_offset,
+                         thread_offset + num_unit_thread);
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Transpose error task_id[" << task_id << "] error_code[" << ret << "]";
+    return RET_ERROR;
+  }
+  return RET_OK;
+}
+
+int TransposeRun(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
+  auto g_kernel = reinterpret_cast<TransposeFp16CPUKernel *>(cdata);
+  auto ret = g_kernel->TransposeParallel(task_id);
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "TransposeRun error task_id[" << task_id << "] error_code[" << ret << "]";
+    return RET_OP_EXECUTE_FAILURE;
+  }
+  return RET_OK;
+}
+
+int TransposeFp16CPUKernel::Run() {
+  auto ret = Prepare();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Prepare fail!ret: " << ret;
+    return ret;
+  }
+  MS_ASSERT(in_tensors_.size() == TransposeInputNum);
+  MS_ASSERT(out_tensors_.size() == TransposeOutputNum);
+  auto &in_tensor = in_tensors_.front();
+  auto &out_tensor = out_tensors_.front();
+  if (in_tensor == nullptr || out_tensor == nullptr) {
+    MS_LOG(ERROR) << "null pointer dreferencing.";
+    return RET_ERROR;
+  }
+  in_data_ = reinterpret_cast<float *>(in_tensor->Data());
+  out_data_ = reinterpret_cast<float *>(out_tensor->Data());
+  Float32ToFloat16(in_data_, fp16_in_data_, in_tensor->ElementsNum());
+  in_shape_ = const_cast<int *>(in_tensor->shape().data());
+  out_shape_ = const_cast<int *>(out_tensor->shape().data());
+
+  ret = LiteBackendParallelLaunch(TransposeRun, this, thread_h_num_);
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Tranpose error error_code[" << ret << "]";
+    return ret;
+  }
+  Float16ToFloat32(fp16_out_data_, out_data_, out_tensor->ElementsNum());
+  return ret;
+}  // namespace mindspore::kernel
+
+kernel::LiteKernel *CpuTransposeFp16KernelCreator(const std::vector<lite::tensor::Tensor *> &inputs,
+                                                  const std::vector<lite::tensor::Tensor *> &outputs,
+                                                  OpParameter *opParameter, const lite::Context *ctx,
+                                                  const kernel::KernelKey &desc, const lite::Primitive *primitive) {
+  MS_ASSERT(desc.type == schema::PrimitiveType_Transpose);
+  if (opParameter == nullptr) {
+    MS_LOG(ERROR) << "desc type is not Transpose";
+    return nullptr;
+  }
+  auto *kernel = new (std::nothrow) TransposeFp16CPUKernel(opParameter, inputs, outputs, ctx, primitive);
+  if (kernel == nullptr) {
+    MS_LOG(ERROR) << "New kernel fails.";
+    return nullptr;
+  }
+
+  auto ret = kernel->Init();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init kernel failed, name: " << opParameter->name_ << ", type: "
+                  << schema::EnumNamePrimitiveType(static_cast<schema::PrimitiveType>(opParameter->type_));
+    delete kernel;
+    return nullptr;
+  }
+  return kernel;
+}
+
+REG_KERNEL(kCPU, kNumberTypeFloat16, PrimitiveType_Transpose, CpuTransposeFp16KernelCreator)
+}  // namespace mindspore::kernel
diff --git a/mindspore/lite/src/runtime/kernel/arm/fp16/transpose_fp16.h b/mindspore/lite/src/runtime/kernel/arm/fp16/transpose_fp16.h
new file mode 100644
index 0000000000..4f0d3eb945
--- /dev/null
+++ b/mindspore/lite/src/runtime/kernel/arm/fp16/transpose_fp16.h
@@ -0,0 +1,63 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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 MINDSPORE_CCSRC_KERNEL_CPU_ARM_FP16_TRANSPOSE_FP16_H_
+#define MINDSPORE_CCSRC_KERNEL_CPU_ARM_FP16_TRANSPOSE_FP16_H_
+
+#include <arm_neon.h>
+#include <vector>
+#include "src/lite_kernel.h"
+#include "src/kernel_factory.h"
+
+namespace mindspore::kernel {
+
+class TransposeFp16CPUKernel : public LiteKernel {
+ public:
+  explicit TransposeFp16CPUKernel(OpParameter *param, const std::vector<lite::tensor::Tensor *> &inputs,
+                                  const std::vector<lite::tensor::Tensor *> &outputs, const lite::Context *ctx,
+                                  const lite::Primitive *primitive)
+      : LiteKernel(param, inputs, outputs, ctx, primitive), thread_num_(ctx->thread_num_) {}
+  ~TransposeFp16CPUKernel() {
+    if (fp16_in_data_ != nullptr) {
+      free(fp16_in_data_);
+      fp16_in_data_ = nullptr;
+    }
+    if (fp16_out_data_ != nullptr) {
+      free(fp16_out_data_);
+      fp16_out_data_ = nullptr;
+    }
+  }
+
+  int Init() override;
+  int ReSize() override;
+  int Run() override;
+  int TransposeParallel(int task_id);
+
+ private:
+  int thread_num_;
+  int thread_h_stride_;
+  int thread_h_num_;
+  int num_unit_;
+  float *in_data_;
+  float *out_data_;
+  float16_t *fp16_in_data_ = nullptr;
+  float16_t *fp16_out_data_ = nullptr;
+  int *in_shape_;
+  int *out_shape_;
+};
+}  // namespace mindspore::kernel
+
+#endif  // MINDSPORE_CCSRC_KERNEL_CPU_ARM_FP16_TRANSPOSE_FP16_H_
diff --git a/mindspore/lite/src/runtime/kernel/arm/nnacl/fp16/transpose_fp16.c b/mindspore/lite/src/runtime/kernel/arm/nnacl/fp16/transpose_fp16.c
new file mode 100644
index 0000000000..d43dca1000
--- /dev/null
+++ b/mindspore/lite/src/runtime/kernel/arm/nnacl/fp16/transpose_fp16.c
@@ -0,0 +1,168 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "nnacl/fp16/transpose_fp16.h"
+#include <string.h>
+#include "nnacl/errorcode.h"
+
+void TransposeDim2(float16_t *in_data, float16_t *out_data, int *strides, int *out_strides, int *perm,
+                   int *output_shape, int h_start, int h_end) {
+  const int stride0 = strides[perm[0]];
+  const int stride1 = strides[perm[1]];
+  const int output0 = output_shape[0];
+  const int output1 = output_shape[1];
+  for (int i = 0; i < output0; ++i) {
+    int out_stride0_i = i * output1;
+    int stride0_i = i * 1 * stride0;
+    for (int j = 0; j < output1; ++j) {
+      out_data[out_stride0_i + j] = in_data[stride0_i + j * stride1];
+    }
+  }
+}
+
+void TransposeDim3(float16_t *in_data, float16_t *out_data, int *strides, int *out_strides, int *perm,
+                   int *output_shape, int h_start, int h_end) {
+  const int stride0 = strides[perm[0]];
+  const int stride1 = strides[perm[1]];
+  const int stride2 = strides[perm[2]];
+  const int out_stride0 = out_strides[0];
+  const int out_stride1 = out_strides[1];
+  const int output0 = output_shape[0];
+  const int output1 = output_shape[1];
+  const int output2 = output_shape[2];
+  for (int i = 0; i < output0; ++i) {
+    int out_stride0_i = i * out_stride0;
+    int stride0_i = i * stride0;
+    for (int j = 0; j < output1; ++j) {
+      int out_stride1_j = j * out_stride1;
+      int stride1_j = j * stride1;
+      for (int k = 0; k < output2; ++k) {
+        out_data[out_stride0_i + out_stride1_j + k] = in_data[stride0_i + stride1_j + k * stride2];
+      }
+    }
+  }
+}
+
+void TransposeDim4(float16_t *in_data, float16_t *out_data, int *strides, int *out_strides, int *perm,
+                   int *output_shape, int h_start, int h_end) {
+  const int stride0 = strides[perm[0]];
+  const int stride1 = strides[perm[1]];
+  const int stride2 = strides[perm[2]];
+  const int stride3 = strides[perm[3]];
+  const int out_stride0 = out_strides[0];
+  const int out_stride1 = out_strides[1];
+  const int out_stride2 = out_strides[2];
+  const int output0 = output_shape[0];
+  const int output1 = output_shape[1];
+  const int output2 = output_shape[2];
+  const int output3 = output_shape[3];
+
+  for (int i = 0; i < output0; ++i) {
+    int out_stride0_i = i * out_stride0;
+    int stride0_i = i * stride0;
+    for (int j = 0; j < output1; ++j) {
+      int out_stride1_j = j * out_stride1;
+      int stride1_j = j * stride1;
+      for (int k = 0; k < output2; ++k) {
+        int out_stride2_k = k * out_stride2;
+        int stride2_k = k * stride2;
+        for (int m = 0; m < output3; ++m) {
+          out_data[out_stride0_i + out_stride1_j + out_stride2_k + m] =
+            in_data[stride0_i + stride1_j + stride2_k + m * stride3];
+        }
+      }
+    }
+  }
+}
+
+void TransposeDim5(float16_t *in_data, float16_t *out_data, int *strides, int *out_strides, int *perm,
+                   int *output_shape, int h_start, int h_end) {
+  const int stride0 = strides[perm[0]];
+  const int stride1 = strides[perm[1]];
+  const int stride2 = strides[perm[2]];
+  const int stride3 = strides[perm[3]];
+  const int stride4 = strides[perm[4]];
+  const int out_stride0 = out_strides[0];
+  const int out_stride1 = out_strides[1];
+  const int out_stride2 = out_strides[2];
+  const int out_stride3 = out_strides[3];
+  const int output0 = output_shape[0];
+  const int output1 = output_shape[1];
+  const int output2 = output_shape[2];
+  const int output3 = output_shape[3];
+  const int output4 = output_shape[4];
+
+  for (int i = 0; i < output0; ++i) {
+    int out_stride0_i = i * out_stride0;
+    int stride0_i = i * stride0;
+    for (int j = 0; j < output1; ++j) {
+      int out_stride1_j = j * out_stride1;
+      int stride1_j = j * stride1;
+      for (int k = 0; k < output2; ++k) {
+        int out_stride2_k = k * out_stride2;
+        int stride2_k = k * stride2;
+        for (int m = 0; m < output3; ++m) {
+          int out_stride3_m = m * out_stride3;
+          int stride3_m = m * stride3;
+          for (int n = 0; n < output4; ++n) {
+            out_data[out_stride0_i + out_stride1_j + out_stride2_k + out_stride3_m + n] =
+              in_data[stride0_i + stride1_j + stride2_k + stride3_m + n * stride4];
+          }
+        }
+      }
+    }
+  }
+}
+
+int DoTranspose(float16_t *in_data, float16_t *out_data, int *input_shape, int *output_shape,
+                TransposeParameter *transpose_param, int h_start, int h_end) {
+  if (in_data == NULL || out_data == NULL) {
+    return NNACL_ERR;
+  }
+  int *perm = transpose_param->perm_;
+  int *strides = transpose_param->strides_;
+  int *out_strides = transpose_param->out_strides_;
+  int data_size = transpose_param->data_size_;
+  int num_axes = transpose_param->num_axes_;
+
+  if (num_axes < 2 || num_axes > 5) {
+    return NNACL_ERR;
+  }
+
+  // check if transpose is needed
+  bool needTranspose = false;
+  for (int i = 1; i < num_axes; ++i) {
+    if (perm[i] - perm[i - 1] != 1) {
+      needTranspose = true;
+      break;
+    }
+  }
+
+  if (!needTranspose) {
+    (void)memcpy(out_data, in_data, data_size);
+    return NNACL_OK;
+  }
+  if (num_axes == 2) {
+    TransposeDim2(in_data, out_data, strides, out_strides, perm, output_shape, h_start, h_end);
+  } else if (num_axes == 3) {
+    TransposeDim3(in_data, out_data, strides, out_strides, perm, output_shape, h_start, h_end);
+  } else if (num_axes == 4) {
+    TransposeDim4(in_data, out_data, strides, out_strides, perm, output_shape, h_start, h_end);
+  } else if (num_axes == 5) {
+    TransposeDim5(in_data, out_data, strides, out_strides, perm, output_shape, h_start, h_end);
+  }
+  return NNACL_OK;
+}
diff --git a/mindspore/lite/src/runtime/kernel/arm/nnacl/fp16/transpose_fp16.h b/mindspore/lite/src/runtime/kernel/arm/nnacl/fp16/transpose_fp16.h
new file mode 100644
index 0000000000..6d9793adb5
--- /dev/null
+++ b/mindspore/lite/src/runtime/kernel/arm/nnacl/fp16/transpose_fp16.h
@@ -0,0 +1,52 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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 MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_FP16_TRANSPOSE_FP16_H_
+#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_FP16_TRANSPOSE_FP16_H_
+
+#include "nnacl/op_base.h"
+#ifdef ENABLE_NEON
+#include <arm_neon.h>
+#endif
+
+typedef struct TransposeParameter {
+  OpParameter op_parameter_;
+  int perm_[8];
+  bool conjugate_;
+  int num_axes_;
+  int strides_[8];
+  int out_strides_[8];
+  int data_size_;
+} TransposeParameter;
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+int DoTranspose(float16_t *in_data, float16_t *out_data, int *input_shape, int *output_shape,
+                TransposeParameter *transpose_param, int h_start, int h_end);
+void TransposeDim2(float16_t *in_data, float16_t *out_data, int *strides, int *out_strides, int *perm,
+                   int *output_shape, int h_start, int h_end);
+void TransposeDim3(float16_t *in_data, float16_t *out_data, int *strides, int *out_strides, int *perm,
+                   int *output_shape, int h_start, int h_end);
+void TransposeDim4(float16_t *in_data, float16_t *out_data, int *strides, int *out_strides, int *perm,
+                   int *output_shape, int h_start, int h_end);
+void TransposeDim5(float16_t *in_data, float16_t *out_data, int *strides, int *out_strides, int *perm,
+                   int *output_shape, int h_start, int h_end);
+#ifdef __cplusplus
+}
+#endif
+
+#endif  // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_FP16_TRANSPOSE_FP16_H_