diff --git a/lite/kernels/mlu/bridges/graph.h b/lite/kernels/mlu/bridges/graph.h
index 140900a2dde004281945e50fb1c72d09b58befa1..bc4da057bfd39e120a48aa7b0525710c2282358b 100644
--- a/lite/kernels/mlu/bridges/graph.h
+++ b/lite/kernels/mlu/bridges/graph.h
@@ -35,6 +35,7 @@ class Graph {
   Graph() { CNML_CALL(cnmlCreateFusionOp(&fusion_op_)); }
 
   ~Graph() {
+    FreeConstData();
     CNML_CALL(cnmlDestroyFusionOp(&fusion_op_));
     for (auto op : ops_) {
       CNML_CALL(cnmlDestroyBaseOp(&op));
@@ -99,6 +100,49 @@ class Graph {
     CNRT_CALL(cnrtSyncQueue(que));
   }
 
+  template <typename T>
+  void* RegisterConstData(size_t len) {
+    void* addr = malloc(len * sizeof(T));
+    const_data_storage_.push_back(addr);
+    return addr;
+  }
+
+  void FreeConstData() {
+    for (auto& addr : const_data_storage_) {
+      free(addr);
+    }
+  }
+
+  void BindConstRawData(std::string tensor_name,
+                        const float* data,
+                        size_t len,
+                        bool alloc = true) {
+    void* alloc_data;
+    if (fp_type_ == CNML_DATA_FLOAT32) {
+      if (alloc) {
+        alloc_data = RegisterConstData<float>(len);
+        memcpy(alloc_data, data, len * sizeof(float));
+      } else {
+        alloc_data = const_cast<void*>(static_cast<const void*>(data));
+      }
+      CNML_CALL(cnmlBindConstData_V2(
+          nodes_[tensor_name]->mlu_tensor(), alloc_data, false));
+    } else if (fp_type_ == CNML_DATA_FLOAT16) {
+      void* data_fp16 = RegisterConstData<::paddle::lite::fluid::float16>(len);
+      CNRT_CALL(
+          cnrtCastDataType(const_cast<void*>(static_cast<const void*>(data)),
+                           CNRT_FLOAT32,
+                           data_fp16,
+                           CNRT_FLOAT16,
+                           len,
+                           nullptr));
+      CNML_CALL(cnmlBindConstData_V2(
+          nodes_[tensor_name]->mlu_tensor(), data_fp16, false));
+    } else {
+      CHECK(0);
+    }
+  }
+
   void BindConstData(std::string tensor_name, ::paddle::lite::Tensor* tensor) {
     const float* data = tensor->data<float>();
     size_t len = tensor->data_size();
@@ -158,6 +202,7 @@ class Graph {
   std::vector<std::shared_ptr<MLUTensor>> output_tensors_;
   std::vector<cnmlBaseOp_t> ops_;
   cnmlFusionOp_t fusion_op_;
+  std::vector<void*> const_data_storage_;
 };
 
 }  // namespace mlu