diff --git a/tests/v1/worker/test_gpu_input_batch.py b/tests/v1/worker/test_gpu_input_batch.py
index 5e70cfb53777..53deb70d7675 100644
--- a/tests/v1/worker/test_gpu_input_batch.py
+++ b/tests/v1/worker/test_gpu_input_batch.py
@@ -62,6 +62,7 @@ def _construct_expected_sampling_metadata(
     repetition_penalties = [1.0 for _ in range(num_reqs)]
     top_k = [0 for _ in range(num_reqs)]
     top_p = [0.0 for _ in range(num_reqs)]
+    min_p = [0.0 for _ in range(num_reqs)]
     temperature = [0.0 for _ in range(num_reqs)]
     stop_token_ids: List[Set[int]] = [set() for _ in range(num_reqs)]
     min_tokens = [0 for _ in range(num_reqs)]
@@ -80,12 +81,12 @@ def _construct_expected_sampling_metadata(
             req.sampling_params.repetition_penalty)
         top_k[index_in_input_batch] = req.sampling_params.top_k
         top_p[index_in_input_batch] = req.sampling_params.top_p
+        min_p[index_in_input_batch] = req.sampling_params.min_p
         temperature[index_in_input_batch] = req.sampling_params.temperature
         stop_token_ids[
             index_in_input_batch] = req.sampling_params.all_stop_token_ids
         min_tokens[index_in_input_batch] = req.sampling_params.min_tokens
         logit_bias[index_in_input_batch] = req.sampling_params.logit_bias
-
     return SamplingMetadata(
         temperature=torch.tensor(temperature, dtype=torch.float,
                                  device=device),
@@ -95,6 +96,8 @@ def _construct_expected_sampling_metadata(
         top_k=torch.tensor(top_k, dtype=torch.int, device=device),
         no_top_p=all(x == 1.0 for x in top_p),
         no_top_k=all(x == 0 for x in top_k),
+        min_p=torch.tensor(min_p, dtype=torch.float, device=device),
+        no_min_p=all(x == 0.0 for x in min_p),
         generators={},
         max_num_logprobs=0,
         prompt_token_ids=make_tensor_with_pad(