diff --git a/vllm_ascend/ops/mm_encoder_attention.py b/vllm_ascend/ops/mm_encoder_attention.py
index 9d497059..1ffd8679 100644
--- a/vllm_ascend/ops/mm_encoder_attention.py
+++ b/vllm_ascend/ops/mm_encoder_attention.py
@@ -118,19 +118,18 @@ class AscendMMEncoderAttention(MMEncoderAttention):
             k = F.pad(k, (0, pad_len), mode="constant", value=0)
             v = F.pad(v, (0, pad_len), mode="constant", value=0)
 
-        context_layer = torch.empty_like(q)
+        seq_lens_cpu = list(seq_lens_cpu.cumsum(0))
 
-        # operator requires pta version >= 2.5.1
-        torch_npu._npu_flash_attention_unpad(
+        context_layer = torch_npu.npu_fusion_attention(
             query=q,
             key=k,
             value=v,
-            seq_len=seq_lens_cpu,
-            scale_value=self.scale_value,
-            num_heads=self.num_heads,
-            num_kv_heads=self.num_kv_heads,
-            out=context_layer,
-        )
+            actual_seq_qlen=seq_lens_cpu,
+            actual_seq_kvlen=seq_lens_cpu,
+            head_num=self.num_heads,
+            scale=self.scale_value,
+            input_layout="TND",
+        )[0]
 
         if self.enable_pad:
             context_layer = context_layer[..., :origin_shape]
diff --git a/vllm_ascend/ops/rotary_embedding.py b/vllm_ascend/ops/rotary_embedding.py
index 9e81fa3c..3df4cad3 100644
--- a/vllm_ascend/ops/rotary_embedding.py
+++ b/vllm_ascend/ops/rotary_embedding.py
@@ -32,7 +32,7 @@ from vllm.triton_utils import HAS_TRITON
 
 from vllm_ascend.ascend_forward_context import _EXTRA_CTX
 from vllm_ascend.platform import NPUPlatform
-from vllm_ascend.utils import AscendDeviceType, get_ascend_device_type, has_rope, is_vl_model
+from vllm_ascend.utils import has_rope, is_vl_model
 
 if HAS_TRITON:
     from vllm.model_executor.layers.rotary_embedding.mrope import triton_mrope
@@ -519,7 +519,7 @@ class AscendMRotaryEmbedding(MRotaryEmbedding):
             # todo: need cann update in 8.5.0
             return self.forward_triton(positions, query, key)
 
-        if self.mrope_section != [16, 24, 24] or get_ascend_device_type() == AscendDeviceType.A5:
+        if self.mrope_section != [16, 24, 24]:
             return super().forward_oot(positions, query, key)
 
         import torch_npu