diff --git a/atom/plugin/attention_mla.py b/atom/plugin/attention_mla.py
index 84dedf069..d4d0e596c 100644
--- a/atom/plugin/attention_mla.py
+++ b/atom/plugin/attention_mla.py
@@ -714,26 +714,20 @@ def forward_impl_plugin_mode(
 
         decode_only = has_decode and not has_prefill
 
-        if not decode_only:
-            if not hasattr(self, "_has_fused_rope_cache"):
-                self._has_fused_rope_cache = hasattr(
-                    ops, "concat_and_cache_mla_rope_fused"
-                )
-            if kv_cache.numel() > 0 and self._has_fused_rope_cache:
-                ops.concat_and_cache_mla_rope_fused(
-                    positions,
-                    q[..., self.qk_nope_head_dim :],
-                    k_pe.squeeze(1),
-                    k_c_normed,
-                    self.rotary_emb_cos_sin_cache,
-                    self.rotary_emb.is_neox_style,
-                    attn_metadata.plugin_metadata.slot_mapping,
-                    kv_cache,
-                    self.kv_cache_dtype,
-                    layer._k_scale,
-                )
-            else:
-                self.rotary_emb(positions, q[..., self.qk_nope_head_dim :], k_pe)
+        # NoPE-only MLA models (e.g., Kimi-Linear) construct ``MLAModules``
+        # with ``rotary_emb=None`` upstream because no rope is applied. Detect
+        # that case once here and route around every ``self.rotary_emb`` /
+        # ``rotary_emb_cos_sin_cache`` access below; the kv_cache write and
+        # decode_q construction otherwise follow the same code paths as the
+        # rope case, just without the rope step.
+        nope_only_mla = self.rotary_emb is None
+
+        if not decode_only or nope_only_mla:
+            if nope_only_mla:
+                # No rope to apply; write kv_cache plainly. ``k_pe`` may have
+                # zero size along the last dim for fully NoPE-only models, in
+                # which case ``aiter.concat_and_cache_mla`` still writes the
+                # ``k_c_normed`` (kv_lora) portion correctly.
                 if kv_cache.numel() > 0:
                     aiter.concat_and_cache_mla(
                         k_c_normed,
@@ -743,6 +737,35 @@ def forward_impl_plugin_mode(
                         kv_cache_dtype=self.kv_cache_dtype,
                         scale=layer._k_scale,
                     )
+            else:
+                if not hasattr(self, "_has_fused_rope_cache"):
+                    self._has_fused_rope_cache = hasattr(
+                        ops, "concat_and_cache_mla_rope_fused"
+                    )
+                if kv_cache.numel() > 0 and self._has_fused_rope_cache:
+                    ops.concat_and_cache_mla_rope_fused(
+                        positions,
+                        q[..., self.qk_nope_head_dim :],
+                        k_pe.squeeze(1),
+                        k_c_normed,
+                        self.rotary_emb_cos_sin_cache,
+                        self.rotary_emb.is_neox_style,
+                        attn_metadata.plugin_metadata.slot_mapping,
+                        kv_cache,
+                        self.kv_cache_dtype,
+                        layer._k_scale,
+                    )
+                else:
+                    self.rotary_emb(positions, q[..., self.qk_nope_head_dim :], k_pe)
+                    if kv_cache.numel() > 0:
+                        aiter.concat_and_cache_mla(
+                            k_c_normed,
+                            k_pe.squeeze(1),
+                            kv_cache,
+                            attn_metadata.plugin_metadata.slot_mapping.flatten(),
+                            kv_cache_dtype=self.kv_cache_dtype,
+                            scale=layer._k_scale,
+                        )
 
         if fp8_attention:
             kv_cache = kv_cache.view(current_platform.fp8_dtype())
@@ -795,7 +818,7 @@ def forward_impl_plugin_mode(
                     transpose_bm=True,
                 )
 
-            if decode_only:
+            if decode_only and not nope_only_mla:
                 decode_q = torch.empty(
                     (
                         decode_ql_nope.shape[0],
@@ -828,6 +851,11 @@ def forward_impl_plugin_mode(
                     is_nope_first=True,
                 )
             else:
+                # Either mixed prefill+decode batch (kv_cache already written
+                # above) OR NoPE-only decode-only batch (kv_cache also written
+                # above via the ``nope_only_mla`` branch). In both cases we
+                # only need to construct ``decode_q`` here; rope was either
+                # applied above or not needed at all.
                 if fp8_attention:
                     assert decode_ql_nope.shape[0] == decode_q_pe.shape[0]
                     assert decode_ql_nope.shape[1] == decode_q_pe.shape[1]