diff --git a/vllm_ascend/ops/fused_moe/token_dispatcher.py b/vllm_ascend/ops/fused_moe/token_dispatcher.py
index 0513307ab74..f5f01a6071d 100644
--- a/vllm_ascend/ops/fused_moe/token_dispatcher.py
+++ b/vllm_ascend/ops/fused_moe/token_dispatcher.py
@@ -32,8 +32,7 @@
 from vllm_ascend.distributed.parallel_state import get_mc2_group
 from vllm_ascend.ops.fused_moe.comm_utils import (
     async_all_to_all, gather_from_sequence_parallel_region)
-from vllm_ascend.utils import (AscendDeviceType, get_ascend_device_type,
-                               is_hierarchical_communication_enabled)
+from vllm_ascend.utils import AscendDeviceType, get_ascend_device_type
 
 
 @dataclass
@@ -117,10 +116,6 @@ def __init__(self, **kwargs):
         self.need_extra_args = (
             get_ascend_device_type() == AscendDeviceType.A3)
 
-        # NOTE: When in A2, setting the environment variables HCCL_INTRA_PCIE_ENABLE=1 and
-        # HCCL_INTRA_ROCE_ENABLE=0 can reduce cross-machine communication traffic and significantly
-        # improve communication performance.
-        self.need_expert_scale = is_hierarchical_communication_enabled()
         self.with_quant = False
 
         # Here we need to calculate the global_bs = max_bs_per_rank * ep_world_size to execute
@@ -158,6 +153,7 @@ def get_dispatch_mc2_kwargs(
         else:
             quant_mode = 0
             moe_expert_num = len(expert_map)
+
         kwargs_mc2 = {
             "x": hidden_states,
             "expert_ids": topk_ids,
@@ -166,8 +162,12 @@ def get_dispatch_mc2_kwargs(
             "moe_expert_num": moe_expert_num,
             "global_bs": self.global_bs,
             "expert_token_nums_type": 0,
+            "expert_scales": topk_weights.to(torch.float32),
         }
 
+        if get_ascend_device_type() == AscendDeviceType.A2:
+            kwargs_mc2["comm_alg"] = "hierarchy"
+
         stage1_kwargs = {
             "scales": None,
             "quant_mode": quant_mode,
@@ -181,11 +181,6 @@ def get_dispatch_mc2_kwargs(
                 "tp_world_size": 1,
                 "tp_rank_id": 0,
             })
-        if self.need_expert_scale:
-            stage1_kwargs.update({
-                "expert_scales":
-                topk_weights.to(torch.float32),
-            })
 
         kwargs_mc2.update(stage1_kwargs)
         return kwargs_mc2
@@ -263,8 +258,12 @@ def get_combine_mc_kwargs(self, hidden_states: torch.Tensor,
             "shared_expert_rank_num": 0,
             "moe_expert_num": moe_expert_num,
             "global_bs": self.global_bs,
+            "expand_scales": expand_scales,
         }
 
+        if get_ascend_device_type() == AscendDeviceType.A2:
+            kwargs_mc2["comm_alg"] = "hierarchy"
+
         if self.with_quant:
             tp_recv_counts = torch.empty(1,
                                          dtype=torch.int32,
@@ -275,7 +274,6 @@ def get_combine_mc_kwargs(self, hidden_states: torch.Tensor,
             "group_ep": self.moe_all_to_all_group_name,
             "ep_world_size": self.ep_world_size,
             "ep_rank_id": self.ep_rank_id,
-            "expand_scales": expand_scales,
         }
 
         if self.enable_dispatch_v2:
diff --git a/vllm_ascend/utils.py b/vllm_ascend/utils.py
index 97f8e2b66cc..51b87cfe37f 100644
--- a/vllm_ascend/utils.py
+++ b/vllm_ascend/utils.py
@@ -958,14 +958,6 @@ def calculate_dp_buffer_size() -> int:
     return max(dp_buffer_size, _MIN_DP_BUFFER_SIZE)
 
 
-# Currently, when in A2, setting the environment variables HCCL_INTRA_PCIE_ENABLE=1
-# and HCCL_INTRA_ROCE_ENABLE=0 can reduce cross-machine communication traffic and
-# significantly improve communication performance of MC2 ops dispatch/combine.
-def is_hierarchical_communication_enabled():
-    return (os.getenv("HCCL_INTRA_ROCE_ENABLE", "") == "0"
-            and os.getenv("HCCL_INTRA_PCIE_ENABLE", "") == "1")
-
-
 def has_layer_idx(model_instance: torch.nn.Module) -> bool:
     if model_instance is None:
         return False