diff --git a/python/sglang/srt/layers/moe/topk.py b/python/sglang/srt/layers/moe/topk.py
index b372858f7..c346e12f7 100644
--- a/python/sglang/srt/layers/moe/topk.py
+++ b/python/sglang/srt/layers/moe/topk.py
@@ -183,15 +183,13 @@ class TopK(CustomOp):
         *,
         num_token_non_padded: Optional[torch.Tensor] = None,
         expert_location_dispatch_info: Optional[ExpertLocationDispatchInfo] = None,
-        sm_first: bool = False,  # only used for triton kernels topk
     ) -> TopKOutput:
         if self.use_triton_kernels:
-            return triton_kernels_topk(
-                router_logits=router_logits,
-                topk=self.top_k,
-                renormalize=self.renormalize,
-                sm_first=sm_first,
+            # renormalize=True is equivalent to sm_first=False
+            routing_data, gather_idx, scatter_idx = routing(
+                router_logits, self.top_k, sm_first=not self.renormalize
             )
+            return TritonKernelTopKOutput(routing_data, gather_idx, scatter_idx)
         else:
             torch_native = False
             return select_experts(
@@ -647,22 +645,6 @@ def biased_grouped_topk_cpu(
     )
 
 
-def triton_kernels_topk(
-    router_logits: torch.Tensor,
-    topk: int,
-    renormalize: bool = False,
-    sm_first: bool = False,
-) -> TritonKernelTopKOutput:
-    """Top-K routing for Triton kernels MoE."""
-    assert not renormalize, "Triton kernels topk doesn't support renormalize"
-    routing_data, gather_idx, scatter_idx = routing(
-        logits=router_logits,
-        n_expts_act=topk,
-        sm_first=sm_first,
-    )
-    return TritonKernelTopKOutput(routing_data, gather_idx, scatter_idx)
-
-
 if _is_cpu and _is_cpu_amx_available:
     biased_grouped_topk = biased_grouped_topk_cpu
     grouped_topk = grouped_topk_cpu