diff --git a/paddle/fluid/memory/allocation/cuda_allocator.cc b/paddle/fluid/memory/allocation/cuda_allocator.cc
index 4ea182cb722cebdc6acb068494267dd029b45a5e..781addd7dba60b214405808d086cd6f246d67e5e 100644
--- a/paddle/fluid/memory/allocation/cuda_allocator.cc
+++ b/paddle/fluid/memory/allocation/cuda_allocator.cc
@@ -70,29 +70,20 @@ phi::Allocation* CUDAAllocator::AllocateImpl(size_t size) {
         limit_size);
   }
 
-  std::string managed_memory_msg;
-  if (platform::IsGPUManagedMemoryOversubscriptionSupported(place_.device)) {
-    managed_memory_msg = string::Sprintf(
-        "If the above ways do not solve the out of memory problem, you can try "
-        "to use CUDA managed memory. The command is `export "
-        "FLAGS_use_cuda_managed_memory=true`.");
-  }
-
   PADDLE_THROW_BAD_ALLOC(platform::errors::ResourceExhausted(
       "\n\nOut of memory error on GPU %d. "
       "Cannot allocate %s memory on GPU %d, %s memory has been allocated and "
       "available memory is only %s.\n\n"
       "Please check whether there is any other process using GPU %d.\n"
       "1. If yes, please stop them, or start PaddlePaddle on another GPU.\n"
-      "2. If no, please decrease the batch size of your model. %s\n%s\n",
+      "2. If no, please decrease the batch size of your model. %s\n",
       place_.device,
       string::HumanReadableSize(size),
       place_.device,
       string::HumanReadableSize(allocated),
       string::HumanReadableSize(avail),
       place_.device,
-      err_msg,
-      managed_memory_msg));
+      err_msg));
 }
 
 }  // namespace allocation