diff --git a/vllm_ascend/attention/sfa_v1.py b/vllm_ascend/attention/sfa_v1.py
index 2e90a7fa..b74efc8d 100644
--- a/vllm_ascend/attention/sfa_v1.py
+++ b/vllm_ascend/attention/sfa_v1.py
@@ -484,14 +484,15 @@ class AscendSFAImpl(MLAAttentionImpl):
                 self._process_weights_for_fused_mlapo(act_dtype)
 
     def _v_up_proj(self, x):
-        if self.W_UV.shape[0] * self.W_UV.shape[1] < 65536:
-            x = x.view(-1, self.local_num_heads, self.kv_lora_rank)
-            x = torch_npu.npu_transpose_batchmatmul(x,
-                                                    self.W_UV,
-                                                    perm_x1=[1, 0, 2],
-                                                    perm_x2=[0, 1, 2],
-                                                    perm_y=[1, 0, 2])
-            x = x.reshape(-1, self.local_num_heads * self.v_head_dim)
+        if x.dtype in [torch.float16, torch.bfloat16] \
+                and hasattr(torch.ops._C_ascend, "batch_matmul_transpose"):
+            x = x.view(-1, self.num_heads, self.kv_lora_rank)
+            b, _, _ = x.shape
+            res = torch.empty((b, self.num_heads, self.v_head_dim),
+                              dtype=x.dtype,
+                              device=x.device)
+            torch.ops._C_ascend.batch_matmul_transpose(x, self.W_UV, res)
+            x = res.reshape(-1, self.num_heads * self.v_head_dim)
         else:
             # Convert from (B, N, L) to (N, B, L)
             x = x.view(-1, self.local_num_heads,