diff --git a/vllm/v1/attention/backends/rocm_aiter_fa.py b/vllm/v1/attention/backends/rocm_aiter_fa.py
index 141d57d908eb..2ea3c346f5a8 100644
--- a/vllm/v1/attention/backends/rocm_aiter_fa.py
+++ b/vllm/v1/attention/backends/rocm_aiter_fa.py
@@ -1114,7 +1114,50 @@ def forward(
                     )
                     return
 
-                if rocm_aiter_ops.is_shuffle_kv_cache_enabled():
+                # The ll4mi kernel in paged_attention_v1 requires
+                # HEAD_SIZE >= 16 * NWARPS (= 64 on ROCm with NWARPS=4).
+                # For smaller head sizes or sliding window attention,
+                # fall back to the unified_attention triton kernel which
+                # handles both correctly.
+                _MIN_HEAD_SIZE_FOR_LL4MI = 64
+                use_unified_attention = self.head_size < _MIN_HEAD_SIZE_FOR_LL4MI
+
+                if use_unified_attention:
+                    assert not rocm_aiter_ops.is_shuffle_kv_cache_enabled(), (
+                        "unified_attention fallback with shuffle layout "
+                        "is not supported yet."
+                    )
+                    from aiter.ops.triton.unified_attention import (
+                        unified_attention,
+                    )
+
+                    decode_cu_seqlens_q = attn_metadata.query_start_loc[
+                        : num_decodes + 1
+                    ]
+                    descale_shape = (
+                        num_decodes,
+                        key_cache.shape[2],
+                    )
+                    unified_attention(
+                        q=query[:num_decode_tokens],
+                        k=key_cache,
+                        v=value_cache,
+                        out=output[:num_decode_tokens],
+                        cu_seqlens_q=decode_cu_seqlens_q,
+                        max_seqlen_q=1,
+                        seqused_k=attn_metadata.seq_lens[:num_decodes],
+                        max_seqlen_k=attn_metadata.max_seq_len,
+                        softmax_scale=self.scale,
+                        causal=True,
+                        alibi_slopes=self.alibi_slopes,
+                        window_size=self.sliding_window,
+                        block_table=attn_metadata.block_table[:num_decodes],
+                        softcap=self.logits_soft_cap,
+                        q_descale=None,
+                        k_descale=layer._k_scale.expand(descale_shape),
+                        v_descale=layer._v_scale.expand(descale_shape),
+                    )
+                elif rocm_aiter_ops.is_shuffle_kv_cache_enabled():
                     num_blocks, block_size, num_kv_heads, head_size = key_cache.shape
                     x = 16 // key_cache.element_size()
                     k_cache_template = torch.empty(