diff --git a/vllm/v1/attention/backends/utils.py b/vllm/v1/attention/backends/utils.py
index b6a06b17bca2..7057023d6684 100644
--- a/vllm/v1/attention/backends/utils.py
+++ b/vllm/v1/attention/backends/utils.py
@@ -59,11 +59,6 @@ class CommonAttentionMetadata:
     block_table_tensor: torch.Tensor
     slot_mapping: torch.Tensor
 
-    def __post_init__(self):
-        # Fill unused with -1. Needed for reshape_and_cache in full cuda graph
-        # mode.
-        self.slot_mapping[self.num_actual_tokens:].fill_(-1)
-
 
 M = TypeVar("M")
 
diff --git a/vllm/v1/worker/gpu_model_runner.py b/vllm/v1/worker/gpu_model_runner.py
index c3eeb6c2e390..0dd2b78e0a9b 100644
--- a/vllm/v1/worker/gpu_model_runner.py
+++ b/vllm/v1/worker/gpu_model_runner.py
@@ -684,7 +684,7 @@ def _prepare_inputs(
         self.seq_lens[:num_reqs].copy_(self.seq_lens_cpu[:num_reqs],
                                        non_blocking=True)
 
-        # Fill unused with -1. Needed for reshape_and_cache
+        # Fill unused with 0 for full cuda graph mode.
         self.seq_lens[num_reqs:].fill_(0)
         # Note: pad query_start_loc to be non-decreasing, as kernels
         # like FlashAttention requires that
@@ -704,6 +704,11 @@ def _prepare_inputs(
             blk_table = self.input_batch.block_table[kv_cache_group_id]
             blk_table_tensor = blk_table.get_device_tensor()[:num_reqs]
             slot_mapping = blk_table.slot_mapping[:total_num_scheduled_tokens]
+
+            # Fill unused with -1. Needed for reshape_and_cache in full cuda
+            # graph mode.
+            blk_table.slot_mapping[total_num_scheduled_tokens:].fill_(-1)
+
             common_attn_metadata = CommonAttentionMetadata(
                 query_start_loc=self.query_start_loc[:num_reqs + 1],
                 query_start_loc_cpu=self.query_start_loc_cpu[:num_reqs + 1],