diff --git a/vllm_spyre/v1/worker/spyre_worker.py b/vllm_spyre/v1/worker/spyre_worker.py
index fbf6a3f17..313cce320 100644
--- a/vllm_spyre/v1/worker/spyre_worker.py
+++ b/vllm_spyre/v1/worker/spyre_worker.py
@@ -363,8 +363,7 @@ def _warmup_spyre_dynamic_size(self, special_token_ids):
         with _maybe_warmup_context():
             self._dynamic_warmup(dummy_requests=dummy_requests,
                                  prompt_len=prompt_len,
-                                 batch_size=batch_size,
-                                 valid_token_ids_tensor=valid_token_ids_tensor)
+                                 batch_size=batch_size)
 
         # warmup_mode completes the graph compilation, but we need to do
         # one additional prefill to deploy the compiled program to the device,
@@ -466,22 +465,17 @@ def _warmup_spyre_fixed_size(self, prompt_len, num_decode_tokens,
 
         # Set up dummy cached_requests for decode steps
         req_ids = []
-        new_token_ids = []
         new_block_ids = []
         num_computed_tokens = []
         for req in dummy_requests:
             req_ids.append(req.req_id)
-            new_token_ids.append([
-                valid_token_ids_tensor[torch.randint(
-                    0, len(valid_token_ids_tensor), (1, )).item()]
-            ])  # placeholder token
             new_block_ids.append([req.block_ids])
             num_computed_tokens.append(req.num_computed_tokens)
 
         cached_request_data = CachedRequestData(
             req_ids=req_ids,
             resumed_from_preemption=False,
-            new_token_ids=new_token_ids,
+            new_token_ids=[[] for _ in range(len(dummy_requests))],
             new_block_ids=new_block_ids,
             num_computed_tokens=num_computed_tokens,
         )
@@ -542,7 +536,6 @@ def _dynamic_warmup(
         dummy_requests: list[NewRequestData],
         prompt_len: int,
         batch_size: int,
-        valid_token_ids_tensor: torch.Tensor,
     ) -> None:
 
         assert (
@@ -569,21 +562,16 @@ def _dynamic_warmup(
 
         # one decode iteration across all sequences
         req_ids = []
-        new_token_ids = []
         new_block_ids = []
         num_computed_tokens = []
         for req in dummy_requests:
             req_ids.append(req.req_id)
-            new_token_ids.append([
-                valid_token_ids_tensor[torch.randint(
-                    0, len(valid_token_ids_tensor), (1, )).item()]
-            ])  # placeholder token
             new_block_ids.append([req.block_ids])
             num_computed_tokens.append(prompt_len)
         cached_request_data = CachedRequestData(
             req_ids=req_ids,
             resumed_from_preemption=False,
-            new_token_ids=new_token_ids,
+            new_token_ids=[[] for _ in range(len(dummy_requests))],
             new_block_ids=new_block_ids,
             num_computed_tokens=num_computed_tokens,
         )