diff --git a/python/sglang/srt/layers/attention/nsa/nsa_indexer.py b/python/sglang/srt/layers/attention/nsa/nsa_indexer.py
index 02ef4e2440cd..6bfcb3f66852 100644
--- a/python/sglang/srt/layers/attention/nsa/nsa_indexer.py
+++ b/python/sglang/srt/layers/attention/nsa/nsa_indexer.py
@@ -257,13 +257,13 @@ def _weights_proj_bf16_in_fp32_out(self, x: torch.Tensor) -> torch.Tensor:
         weights, _ = self.weights_proj(x)
         return weights.float()
 
-    @torch.compile(dynamic=True) if not _is_hip else lambda f: f
+    @torch.compile(dynamic=True)
     def _project_and_scale_head_gates(self, x: torch.Tensor):
         weights = self._weights_proj_bf16_in_fp32_out(x)
         weights = weights * self.n_heads**-0.5
         return weights
 
-    @torch.compile(dynamic=True) if not _is_hip else lambda f: f
+    @torch.compile(dynamic=True)
     def _get_logits_head_gate(self, x: torch.Tensor, q_scale: torch.Tensor):
         weights = self._weights_proj_bf16_in_fp32_out(x)
         weights = weights * self.n_heads**-0.5
@@ -318,8 +318,8 @@ def _get_q_k_bf16(
 
         q_rope, k_rope = self.rotary_emb(positions, q_rope, k_rope)
 
-        query[..., : self.rope_head_dim] = q_rope.clone()
-        key[..., : self.rope_head_dim] = k_rope.clone()
+        self._update_rope_guarded(query[..., : self.rope_head_dim], q_rope)
+        self._update_rope_guarded(key[..., : self.rope_head_dim], k_rope)
 
         if enable_dual_stream:
             current_stream = torch.cuda.current_stream()
@@ -376,11 +376,19 @@ def _get_k_bf16(
         )
 
         _, k_rope = self.rotary_emb(positions, k_rope, k_rope)
-        key[..., : self.rope_head_dim] = k_rope.clone()
+        self._update_rope_guarded(key[..., : self.rope_head_dim], k_rope)
         key = rotate_activation(key)
 
         return key
 
+    @staticmethod
+    def _update_rope_guarded(dst: torch.Tensor, src: torch.Tensor) -> None:
+        # On AMD with in-place RoPE kernels, self-aliasing can occur;
+        # skip write-back when src/dst tensors point to a single memory.
+        if src.data_ptr() == dst.data_ptr():
+            return
+        dst.copy_(src)
+
     def _get_topk_paged(
         self,
         forward_batch: ForwardBatch,