diff --git a/python/sglang/srt/layers/rotary_embedding.py b/python/sglang/srt/layers/rotary_embedding.py
index 6ce25651f..cfc626e1d 100644
--- a/python/sglang/srt/layers/rotary_embedding.py
+++ b/python/sglang/srt/layers/rotary_embedding.py
@@ -1280,7 +1280,7 @@ class MRotaryEmbedding(RotaryEmbedding):
             self.cos_sin_cache = self.cos_sin_cache.to(query.device, dtype=query.dtype)
 
     @torch.compile(dynamic=True, backend=get_compiler_backend())
-    def forward_native(
+    def _forward_native(
         self,
         positions: torch.Tensor,
         query: torch.Tensor,
@@ -1340,6 +1340,27 @@ class MRotaryEmbedding(RotaryEmbedding):
         query: torch.Tensor,
         key: torch.Tensor,
         fused_set_kv_buffer_arg: Optional[FusedSetKVBufferArg] = None,
+    ) -> Tuple[torch.Tensor, torch.Tensor]:
+        """Forward pass with optional Triton kernel acceleration.
+        Args:
+            positions:
+                [num_tokens,] (text only) or
+                [3, num_tokens] (T/H/W positions with multimodal inputs)
+            query: [num_tokens, num_heads * head_size]
+            key: [num_tokens, num_kv_heads * head_size]
+        """
+        assert positions.ndim == 1 or positions.ndim == 2
+
+        if positions.ndim == 2 and self.mrope_section and _is_cuda:
+            return self._forward_triton(positions, query, key)
+        else:
+            return self._forward_native(positions, query, key)
+
+    def _forward_triton(
+        self,
+        positions: torch.Tensor,
+        query: torch.Tensor,
+        key: torch.Tensor,
     ) -> Tuple[torch.Tensor, torch.Tensor]:
         assert positions.ndim == 1 or positions.ndim == 2
         assert key is not None