diff --git a/mindspore/lite/src/lite_session.cc b/mindspore/lite/src/lite_session.cc
index c526d868a1c..9c6e2f853eb 100644
--- a/mindspore/lite/src/lite_session.cc
+++ b/mindspore/lite/src/lite_session.cc
@@ -347,6 +347,23 @@ void LiteSession::InitGraphInOutTensors(const lite::Model *model) {
   }
 }
 
+void LiteSession::FreePackOpWeight() {
+  for (auto *kernel : kernels_) {
+    MS_ASSERT(kernel != nullptr);
+    if (!IsPackedOp(kernel->Type())) {
+      continue;
+    }
+    auto inputs = kernel->in_tensors();
+    for (auto *tensor : inputs) {
+      MS_ASSERT(tensor != nullptr);
+      if (!tensor->IsConst()) {
+        continue;
+      }
+      tensor->FreeData();
+    }
+  }
+}
+
 int LiteSession::CompileGraph(Model *model) {
   bool expected = false;
   if (!is_running_.compare_exchange_strong(expected, true)) {
@@ -427,7 +444,8 @@ int LiteSession::CompileGraph(Model *model) {
     is_running_.store(false);
     return ret;
   }
-
+  // For reducing runtime RAM, free packop weight because packop will pack weight and will not access to origin weight
+  FreePackOpWeight();
   is_running_.store(false);
   return RET_OK;
 }  // namespace lite
diff --git a/mindspore/lite/src/lite_session.h b/mindspore/lite/src/lite_session.h
index 1e4375a5f18..89672c1dfc2 100644
--- a/mindspore/lite/src/lite_session.h
+++ b/mindspore/lite/src/lite_session.h
@@ -106,6 +106,8 @@ class LiteSession : public session::LiteSession {
 
   static int ReSizeKernels(const std::vector<kernel::LiteKernel *> &kernels);
 
+  void FreePackOpWeight();
+
  private:
   void ResetInputsShape(const std::vector<std::vector<int>> &dims);
 
diff --git a/mindspore/lite/src/scheduler.cc b/mindspore/lite/src/scheduler.cc
index cf16b85eaf6..d08beba9cdb 100644
--- a/mindspore/lite/src/scheduler.cc
+++ b/mindspore/lite/src/scheduler.cc
@@ -217,71 +217,105 @@ int Scheduler::InferSubGraphShape(size_t subgraph_index, bool *infer_shape_inter
 namespace {
 #ifndef SUPPORT_TRAIN
 int CastConstTensorData(Tensor *tensor, std::map<Tensor *, Tensor *> *restored_origin_tensors, TypeId dst_data_type) {
-  MS_ASSERT(restored_origin_tensors != nullptr);
+#if defined(ENABLE_ARM) && defined(ENABLE_FP16)
   MS_ASSERT(tensor != nullptr);
-  if (dst_data_type != kNumberTypeFloat32 && dst_data_type != kNumberTypeFloat16) {
-    MS_LOG(ERROR) << "Only support fp32 or fp16 as dst_data_type.";
-    return RET_PARAM_INVALID;
-  }
-  // tensorlist not support fp16 now
-  if (!tensor->IsConst() || tensor->data_type() == kObjectTypeTensorType) {
+  MS_ASSERT(tensor->IsConst());
+  MS_ASSERT(tensor->data_type() == kNumberTypeFloat32 || tensor->data_type() == kNumberTypeFloat16);
+  MS_ASSERT(dst_data_type == kNumberTypeFloat32 || dst_data_type == kNumberTypeFloat16);
+  if (tensor->data_type() == dst_data_type) {
     return RET_OK;
   }
   auto origin_data = tensor->data_c();
   MS_ASSERT(origin_data != nullptr);
-  if (tensor->data_type() == kNumberTypeFloat32 && dst_data_type == kNumberTypeFloat16) {
-#if defined(ENABLE_ARM) && defined(ENABLE_FP16)
-    auto restore_tensor = Tensor::CopyTensor(*tensor, false);
-    restore_tensor->set_data(origin_data);
-    restore_tensor->set_own_data(tensor->own_data());
-    tensor->set_data(nullptr);
-    tensor->set_data_type(kNumberTypeFloat16);
-    auto ret = tensor->MallocData();
-    if (RET_OK != ret) {
-      MS_LOG(ERROR) << "malloc data failed";
-      return ret;
-    }
-    auto new_tensor_data = tensor->data_c();
-    MS_ASSERT(new_tensor_data != nullptr);
-    Float32ToFloat16_fp16_handler(origin_data, new_tensor_data, tensor->ElementsNum());
-    (*restored_origin_tensors)[tensor] = restore_tensor;
-#else
-    MS_LOG(ERROR) << "Unsupported dst data type: float16";
-    return RET_ERROR;
-#endif
-  } else if (tensor->data_type() == kNumberTypeFloat16 && dst_data_type == kNumberTypeFloat32) {
-#if defined(ENABLE_ARM64) && defined(ENABLE_FP16)
-    auto restore_tensor = Tensor::CopyTensor(*tensor, false);
-    restore_tensor->set_data(origin_data);
-    restore_tensor->set_own_data(tensor->own_data());
-    tensor->set_data(nullptr);
-    tensor->set_data_type(kNumberTypeFloat32);
-    auto ret = tensor->MallocData();
-    if (RET_OK != ret) {
-      MS_LOG(ERROR) << "malloc data failed";
-      return ret;
-    }
-    auto new_tensor_data = tensor->data_c();
-    MS_ASSERT(new_tensor_data != nullptr);
+  auto restore_tensor = Tensor::CopyTensor(*tensor, false);
+  restore_tensor->set_data(origin_data);
+  restore_tensor->set_own_data(tensor->own_data());
+  tensor->set_data(nullptr);
+  tensor->set_data_type(dst_data_type);
+  auto ret = tensor->MallocData();
+  if (RET_OK != ret) {
+    MS_LOG(ERROR) << "malloc data failed";
+    return ret;
+  }
+  auto new_tensor_data = tensor->data_c();
+  MS_ASSERT(new_tensor_data != nullptr);
+  if (dst_data_type == kNumberTypeFloat32) {
     Float16ToFloat32_fp16_handler(origin_data, new_tensor_data, tensor->ElementsNum());
-    (*restored_origin_tensors)[tensor] = restore_tensor;
-#else
-    MS_LOG(ERROR) << "Unsupported dst data type: float16";
+  } else {  // dst_data_type == kNumberTypeFloat16
+    Float32ToFloat16_fp16_handler(origin_data, new_tensor_data, tensor->ElementsNum());
+  }
+  if (restored_origin_tensors->find(tensor) != restored_origin_tensors->end()) {
+    MS_LOG(ERROR) << "Tensor " << tensor->tensor_name() << " is already be stored";
     return RET_ERROR;
+  }
+  (*restored_origin_tensors)[tensor] = restore_tensor;
+  return RET_OK;
+#else
+  return RET_NOT_SUPPORT;
 #endif
-  } else {
+}
+
+int CastConstTensorsData(const std::vector<Tensor *> &tensors, std::map<Tensor *, Tensor *> *restored_origin_tensors,
+                         TypeId dst_data_type) {
+  MS_ASSERT(restored_origin_tensors != nullptr);
+  if (dst_data_type != kNumberTypeFloat32 && dst_data_type != kNumberTypeFloat16) {
+    MS_LOG(ERROR) << "Only support fp32 or fp16 as dst_data_type.";
+    return RET_PARAM_INVALID;
+  }
+  for (auto *tensor : tensors) {
+    MS_ASSERT(tensor != nullptr);
+    // only cast const tensor
+    // tensorlist not support fp16 now
+    if (!tensor->IsConst() || tensor->data_type() == kObjectTypeTensorType) {
+      continue;
+    }
+    // only support fp32->fp16 or fp16->fp32
+    if (tensor->data_type() != kNumberTypeFloat32 && tensor->data_type() != kNumberTypeFloat16) {
+      continue;
+    }
+    if (tensor->data_type() == kNumberTypeFloat32 && dst_data_type == kNumberTypeFloat16) {
+      auto ret = CastConstTensorData(tensor, restored_origin_tensors, kNumberTypeFloat16);
+      if (ret != RET_OK) {
+        MS_LOG(ERROR) << "Cast const tensor from fp32 to fp16 failed, tensor name : " << tensor->tensor_name();
+        return ret;
+      }
+    } else if (tensor->data_type() == kNumberTypeFloat16 && dst_data_type == kNumberTypeFloat32) {
+      auto ret = CastConstTensorData(tensor, restored_origin_tensors, kNumberTypeFloat32);
+      if (ret != RET_OK) {
+        MS_LOG(ERROR) << "Cast const tensor from fp16 to fp32 failed, tensor name : " << tensor->tensor_name();
+        return ret;
+      }
+    } else {
+      MS_LOG(DEBUG) << "No need to cast from " << tensor->data_type() << " to " << dst_data_type;
+    }
+  }
+  return RET_OK;
+}
+
+int CopyConstTensorData(const std::vector<Tensor *> &tensors, int op_type) {
+  // packed kernels such as conv don't need to copy because weight will be packed in kernel
+  if (IsPackedOp(op_type)) {
+    return RET_OK;
+  }
+  for (auto *tensor : tensors) {
+    // only cast const tensor
+    // tensorlist not support fp16 now
+    if (!tensor->IsConst() || tensor->data_type() == kObjectTypeTensorType) {
+      continue;
+    }
     if (tensor->own_data()) {
-      return RET_OK;
+      continue;
     }
-    tensor->set_data(nullptr);
-    auto ret = tensor->MallocData();
-    if (RET_OK != ret) {
-      MS_LOG(ERROR) << "malloc data failed";
-      return ret;
+    auto copy_tensor = Tensor::CopyTensor(*tensor, true);
+    if (copy_tensor == nullptr) {
+      MS_LOG(ERROR) << "Copy tensor failed";
+      return RET_ERROR;
     }
-    auto new_data = tensor->data_c();
-    MS_ASSERT(new_data != nullptr);
-    memcpy(new_data, origin_data, tensor->Size());
+    tensor->FreeData();
+    tensor->set_data(copy_tensor->data_c());
+    tensor->set_own_data(true);
+    copy_tensor->set_data(nullptr);
+    delete (copy_tensor);
   }
   return RET_OK;
 }
@@ -335,12 +369,16 @@ kernel::LiteKernel *Scheduler::FindCpuKernel(const std::vector<Tensor *> &in_ten
   }
   std::map<Tensor *, Tensor *> restored_origin_tensors;
 #ifndef SUPPORT_TRAIN
-  for (auto &tensor : in_tensors) {
-    ret = CastConstTensorData(tensor, &restored_origin_tensors, kernel_data_type);
-    if (ret != RET_OK) {
-      MS_LOG(DEBUG) << "CastConstTensorData failed: " << ret;
-      return nullptr;
-    }
+  ret = CastConstTensorsData(in_tensors, &restored_origin_tensors, kernel_data_type);
+  if (ret != RET_OK) {
+    MS_LOG(DEBUG) << "CastConstTensorsData failed: " << ret;
+    return nullptr;
+  }
+  // we don't need to restore tensor for copy data
+  ret = CopyConstTensorData(in_tensors, op_type);
+  if (ret != RET_OK) {
+    MS_LOG(DEBUG) << "CopyConstTensorsData failed: " << ret;
+    return nullptr;
   }
 #endif
   auto *kernel = KernelRegistry::GetInstance()->GetKernel(in_tensors, out_tensors, context_, cpu_desc, op_parameter);