diff --git a/mindspore/ccsrc/backend/optimizer/ascend/ir_fission/bn_split.cc b/mindspore/ccsrc/backend/optimizer/ascend/ir_fission/bn_split.cc
index d03e29b6c4..245186ea47 100644
--- a/mindspore/ccsrc/backend/optimizer/ascend/ir_fission/bn_split.cc
+++ b/mindspore/ccsrc/backend/optimizer/ascend/ir_fission/bn_split.cc
@@ -182,18 +182,34 @@ AnfNodePtr CreateValueNodeOfDeviceNumReciprocal(const FuncGraphPtr &graph, const
   return device_num_reciprocal_value;
 }
 
+AnfNodePtr InsertCast(const FuncGraphPtr &graph, const AnfNodePtr &input, const TypeId dst_type) {
+  if (AnfAlgo::GetOutputInferDataType(input, 0) != dst_type) {
+    AnfNodePtr cast = graph->NewCNode({NewValueNode(std::make_shared<Primitive>(kCastOpName)), input});
+    AnfAlgo::SetOutputInferTypeAndShape({dst_type}, {AnfAlgo::GetOutputInferShape(input, 0)}, cast.get());
+    AnfAlgo::SetNodeAttr(kIsBackendCast, MakeValue(true), cast);
+    cast->set_scope(input->scope());
+    return cast;
+  }
+  return input;
+}
+
 AnfNodePtr CreateAllReduceAndMul(const FuncGraphPtr &graph, const AnfNodePtr &allreduce_input,
                                  const CNodePtr &sync_bn_cnode) {
   MS_EXCEPTION_IF_NULL(graph);
   MS_EXCEPTION_IF_NULL(allreduce_input);
   MS_EXCEPTION_IF_NULL(sync_bn_cnode);
 
+  // Cast input to fp32, this can reduce the number of cast node. Since the input of AllReduce,
+  // BNTrainingReduce/BNTrainingUpdateGrad op only support fp32 output, when inferred output is fp16, it will
+  // insert cast: output_fp32->cast_fp16->allreduce&mul->cast_fp32. Add this cast can eliminate above cast.
+  // Should be removed if BNTrainingReduce/BNTrainingUpdateGrad op support fp16 output.
+  AnfNodePtr input_node = InsertCast(graph, allreduce_input, kNumberTypeFloat32);
+
   // create AllReduce
-  std::vector<AnfNodePtr> allreduce_inputs = {NewValueNode(std::make_shared<Primitive>(kAllReduceOpName)),
-                                              allreduce_input};
+  std::vector<AnfNodePtr> allreduce_inputs = {NewValueNode(std::make_shared<Primitive>(kAllReduceOpName)), input_node};
   auto allreduce = graph->NewCNode(allreduce_inputs);
   MS_EXCEPTION_IF_NULL(allreduce);
-  allreduce->set_abstract(allreduce_input->abstract());
+  allreduce->set_abstract(input_node->abstract());
   allreduce->set_scope(allreduce_input->scope());
   AnfAlgo::SetNodeAttr(kAttrOp, MakeValue(kReduceOpSum), allreduce);
   AnfAlgo::CopyNodeAttr(kAttrGroup, sync_bn_cnode, allreduce);
@@ -216,9 +232,12 @@ AnfNodePtr CreateAllReduceAndMul(const FuncGraphPtr &graph, const AnfNodePtr &al
                                         device_num_reciprocal_vnode};
   auto mul = graph->NewCNode(mul_inputs);
   MS_EXCEPTION_IF_NULL(mul);
-  mul->set_abstract(allreduce_input->abstract());
+  mul->set_abstract(input_node->abstract());
   mul->set_scope(allreduce_input->scope());
-  return mul;
+
+  // Cast output to origin datatype to reduce the number of cast node.
+  // Should be removed if BNTrainingReduce/BNTrainingUpdateGrad op support fp16 output.
+  return InsertCast(graph, mul, AnfAlgo::GetOutputInferDataType(allreduce_input, 0));
 }
 
 const BaseRef BnSplit::DefinePattern() const {