diff --git a/python/sglang/srt/models/deepseek_common/attention_forward_methods/forward_mla.py b/python/sglang/srt/models/deepseek_common/attention_forward_methods/forward_mla.py
index 283049a15..cd41e62bd 100644
--- a/python/sglang/srt/models/deepseek_common/attention_forward_methods/forward_mla.py
+++ b/python/sglang/srt/models/deepseek_common/attention_forward_methods/forward_mla.py
@@ -64,9 +64,39 @@ if _is_cuda:
 
 
 if _use_aiter:
-    from aiter.ops.fused_qk_norm_rope_cache_quant import (
-        fused_qk_rmsnorm as fused_qk_rmsnorm_bf16,
-    )
+    # aiter ROCm/aiter#2958 renamed the public `fused_qk_rmsnorm` in
+    # `aiter.ops.fused_qk_norm_rope_cache_quant` to a private `_fused_qk_rmsnorm`
+    # and introduced a unified entry point in `aiter.ops.fused_qk_rmsnorm_group_quant`
+    # with a different (in-place, kwarg-only, no-return) signature. Probe for the
+    # new symbol first so SGLang works with both pre- and post-#2958 aiter without
+    # requiring the docker pin to be bumped atomically.
+    try:
+        from aiter.ops.enum import QuantType as _AiterQuantType
+        from aiter.ops.fused_qk_rmsnorm_group_quant import (
+            fused_qk_rmsnorm as _aiter_fused_qk_rmsnorm_unified,
+        )
+
+        def fused_qk_rmsnorm_bf16(q, q_weight, q_eps, k, k_weight, k_eps):
+            q_out = torch.empty_like(q)
+            k_out = torch.empty_like(k)
+            _aiter_fused_qk_rmsnorm_unified(
+                q_out_quantized=q_out,
+                k_out=k_out,
+                q=q,
+                q_weight=q_weight,
+                q_epsilon=q_eps,
+                k=k,
+                k_weight=k_weight,
+                k_epsilon=k_eps,
+                quant_type=_AiterQuantType.No,
+            )
+            return q_out, k_out
+
+    except ImportError:
+        from aiter.ops.fused_qk_norm_rope_cache_quant import (
+            fused_qk_rmsnorm as fused_qk_rmsnorm_bf16,
+        )
+
     from aiter.ops.triton.batched_gemm_a8w8_a_per_token_group_prequant_w_per_batched_tensor_quant import (
         batched_gemm_a8w8_a_per_token_group_prequant_w_per_batched_tensor_quant,
     )