diff --git a/requirements/musa.txt b/requirements/musa.txt
index 112f3260465..c100c70cf05 100644
--- a/requirements/musa.txt
+++ b/requirements/musa.txt
@@ -1,4 +1,6 @@
 -r common.txt
 # MUSA platform dependencies
-torchada>=0.1.46
+torchada>=0.1.50
 onnxruntime>=1.23.2
+mate>=0.2.0
+flash_attn_3>=0.1.4
diff --git a/vllm_omni/diffusion/attention/backends/flash_attn.py b/vllm_omni/diffusion/attention/backends/flash_attn.py
index b6ab3a57ad5..d38ea4f6eaa 100644
--- a/vllm_omni/diffusion/attention/backends/flash_attn.py
+++ b/vllm_omni/diffusion/attention/backends/flash_attn.py
@@ -96,7 +96,7 @@ def forward_cuda(
         value: torch.Tensor,
         attn_metadata: AttentionMetadata = None,
     ) -> torch.Tensor:
-        """CUDA/ROCm flash attention implementation."""
+        """CUDA/ROCm/MUSA flash attention implementation."""
         from vllm_omni.diffusion.attention.backends.utils.fa import (
             HAS_FLASH_ATTN,
             flash_attn_func,
@@ -209,13 +209,3 @@ def forward_npu(
             layout="BNSD",
         )
         return output
-
-    def forward_musa(
-        self,
-        query: torch.Tensor,
-        key: torch.Tensor,
-        value: torch.Tensor,
-        attn_metadata: AttentionMetadata = None,
-    ) -> torch.Tensor:
-        # XXX (MUSA): MUSA uses the same implementation as XPU (mate only provides flash_attn_varlen_func)
-        return self.forward_xpu(query, key, value, attn_metadata)
diff --git a/vllm_omni/diffusion/attention/backends/utils/fa.py b/vllm_omni/diffusion/attention/backends/utils/fa.py
index fe6051f8ba7..18886871a22 100644
--- a/vllm_omni/diffusion/attention/backends/utils/fa.py
+++ b/vllm_omni/diffusion/attention/backends/utils/fa.py
@@ -41,7 +41,7 @@
         pass
 elif current_omni_platform.is_musa():
     try:
-        from mate import flash_attn_varlen_func  # noqa: F401
+        from flash_attn_interface import flash_attn_func, flash_attn_varlen_func  # noqa: F401
     except (ImportError, ModuleNotFoundError):
         pass
 else:
@@ -82,8 +82,8 @@
 
 @lru_cache(maxsize=1)
 def is_mate_available() -> bool:
-    """Check if MATE (MUSA Flash Attention) is available."""
-    return current_omni_platform.is_musa() and flash_attn_varlen_func is not None
+    """Check if MATE (MUSA AI Tensor Engine) is available."""
+    return current_omni_platform.is_musa() and flash_attn_func is not None or flash_attn_varlen_func is not None
 
 
 def _index_first_axis(tensor, indices):