diff --git a/vllm/v1/attention/backends/rocm_aiter_unified_attn.py b/vllm/v1/attention/backends/rocm_aiter_unified_attn.py
index 55ed5c5b3c4..f56b58c43e7 100644
--- a/vllm/v1/attention/backends/rocm_aiter_unified_attn.py
+++ b/vllm/v1/attention/backends/rocm_aiter_unified_attn.py
@@ -200,19 +200,9 @@ class RocmAiterUnifiedAttentionImpl(RocmAttentionImpl):
         key_cache, value_cache = kv_cache.unbind(0)
 
         softmax_scale = self.scale
-        fp8_post_attn_v_rescale = False
         if is_quantized_kv_cache(self.kv_cache_dtype):
             key_cache = key_cache.view(self.fp8_dtype)
             value_cache = value_cache.view(self.fp8_dtype)
-            # When Q is FP8, triton kernel skips K/V dequant (for fp8xfp8 matmul).
-            # Compensate by absorbing q_scale and k_scale into softmax_scale, and
-            # v_scale into output_scale (or post-multiplying if no fusion).
-            if query.dtype == self.fp8_dtype:
-                softmax_scale = self.scale * layer._q_scale_float * layer._k_scale_float
-                if output_scale is not None:
-                    output_scale = output_scale / layer._v_scale_float
-                else:
-                    fp8_post_attn_v_rescale = True
 
         cu_seqlens_q = attn_metadata.query_start_loc
         seqused_k = attn_metadata.seq_lens
@@ -220,11 +210,6 @@ class RocmAiterUnifiedAttentionImpl(RocmAttentionImpl):
         max_seqlen_k = attn_metadata.max_seq_len
         block_table = attn_metadata.block_table
 
-        descale_shape = (
-            cu_seqlens_q.shape[0] - 1,
-            key.shape[1] if key is not None else self.num_kv_heads,
-        )
-
         self.unified_attention(
             q=query[:num_actual_tokens],
             k=key_cache,
@@ -240,16 +225,13 @@ class RocmAiterUnifiedAttentionImpl(RocmAttentionImpl):
             window_size=self.sliding_window,
             block_table=block_table,
             softcap=self.logits_soft_cap,
-            q_descale=None,  # q_scale absorbed into softmax_scale
-            k_descale=layer._k_scale.expand(descale_shape),
-            v_descale=layer._v_scale.expand(descale_shape),
+            q_descale=layer._q_scale if query.dtype == self.fp8_dtype else None,
+            k_descale=layer._k_scale,
+            v_descale=layer._v_scale,
             sinks=self.sinks,
             output_scale=output_scale,
         )
 
-        if fp8_post_attn_v_rescale:
-            output[:num_actual_tokens].mul_(layer._v_scale_float)
-
         return output
 
     def do_kv_cache_update(