diff --git a/vllm/attention/ops/triton_unified_attention.py b/vllm/attention/ops/triton_unified_attention.py
index ba4299a2772df..56ebed0f52448 100644
--- a/vllm/attention/ops/triton_unified_attention.py
+++ b/vllm/attention/ops/triton_unified_attention.py
@@ -75,6 +75,7 @@ def kernel_unified_attention_2d(
         USE_ALIBI_SLOPES: tl.constexpr,  # bool
         USE_QQ_BIAS: tl.constexpr,  # bool
         USE_SOFTCAP: tl.constexpr,  # bool
+        USE_SINKS: tl.constexpr,  # bool
         SLIDING_WINDOW: tl.constexpr,  # int
         stride_k_cache_0: tl.int64,  # int
         stride_k_cache_1: tl.int64,  # int
@@ -132,7 +133,7 @@ def kernel_unified_attention_2d(
 
     block_table_offset = seq_idx * block_table_stride
 
-    if sink_ptr is None:
+    if not USE_SINKS:
         M = tl.full([BLOCK_M], float("-inf"), dtype=tl.float32)
     else:
         M = tl.load(
@@ -322,6 +323,7 @@ def kernel_unified_attention_3d(
         USE_ALIBI_SLOPES: tl.constexpr,  # bool
         USE_QQ_BIAS: tl.constexpr,  # bool
         USE_SOFTCAP: tl.constexpr,  # bool
+        USE_SINKS: tl.constexpr,  # bool
         SLIDING_WINDOW: tl.constexpr,  # int
         stride_k_cache_0: tl.int64,  # int
         stride_k_cache_1: tl.int64,  # int
@@ -393,14 +395,17 @@ def kernel_unified_attention_3d(
 
     block_table_offset = seq_idx * block_table_stride
 
-    if sink_ptr is None or segm_idx != 0:
-        M = tl.full([BLOCK_M], float("-inf"), dtype=tl.float32)
+    if USE_SINKS:
+        if segm_idx == 0:
+            M = tl.load(
+                sink_ptr + query_offset_1,
+                mask=query_mask_1,
+                other=float("-inf"),
+            ).to(dtype=tl.float32)
+        else:
+            M = tl.full([BLOCK_M], float("-inf"), dtype=tl.float32)
     else:
-        M = tl.load(
-            sink_ptr + query_offset_1,
-            mask=query_mask_1,
-            other=float("-inf"),
-        ).to(dtype=tl.float32)
+        M = tl.full([BLOCK_M], float("-inf"), dtype=tl.float32)
 
     L = tl.full([BLOCK_M], 1.0, dtype=tl.float32)
     acc = tl.zeros([BLOCK_M, HEAD_SIZE_PADDED], dtype=tl.float32)
@@ -716,6 +721,7 @@ def unified_attention(
             USE_ALIBI_SLOPES=use_alibi_slopes,
             USE_QQ_BIAS=use_qq_bias,
             USE_SOFTCAP=(softcap > 0),
+            USE_SINKS=(sinks is not None),
             SLIDING_WINDOW=(1 + window_size[0]),
             stride_k_cache_0=k.stride(0),
             stride_k_cache_1=k.stride(1),
@@ -787,6 +793,7 @@ def unified_attention(
                 USE_ALIBI_SLOPES=use_alibi_slopes,
                 USE_QQ_BIAS=use_qq_bias,
                 USE_SOFTCAP=(softcap > 0),
+                USE_SINKS=(sinks is not None),
                 SLIDING_WINDOW=(1 + window_size[0]),
                 stride_k_cache_0=k.stride(0),
                 stride_k_cache_1=k.stride(1),