diff --git a/vllm/attention/ops/triton_unified_attention.py b/vllm/attention/ops/triton_unified_attention.py
index f61c8e9b89c24..e60af7434d25c 100644
--- a/vllm/attention/ops/triton_unified_attention.py
+++ b/vllm/attention/ops/triton_unified_attention.py
@@ -189,9 +189,14 @@ def kernel_unified_attention_2d(
         + 1
     )
 
-    # adjust for potential padding in the last q_block by considering the
-    # actual sequence length
-    max_seq_prefix_len = tl.minimum(max_seq_prefix_len, seq_len)
+    if USE_MM_PREFIX:
+        # image bidirectional attention ranges require a full range
+        # including q_block padding to make sure doc mask is correct
+        max_seq_prefix_len = tl.maximum(max_seq_prefix_len, seq_len)
+    else:
+        # adjust for potential padding in the last q_block by considering the
+        # actual sequence length
+        max_seq_prefix_len = tl.minimum(max_seq_prefix_len, seq_len)
 
     # calculate the number of tiles that need to be processed to
     # cover the longest sequence prefix (due to causal masking, tiles beyond
@@ -202,7 +207,8 @@ def kernel_unified_attention_2d(
     # Default: keep previous global behavior
     tile_start = 0
     tile_end = num_tiles
-    if SLIDING_WINDOW > 0:
+    # TODO(Isotr0py): sliding window pruning with image bidirectional mask
+    if SLIDING_WINDOW > 0 and not USE_MM_PREFIX:
         # Query rows covered by this Q-block
         qpos_lo = q_block_local_idx * BLOCK_Q
         qpos_hi = tl.minimum(