diff --git a/tests/models/test_deepseek_v4_mega_moe.py b/tests/models/test_deepseek_v4_mega_moe.py
index 58d5239285..d3d9ccabad 100644
--- a/tests/models/test_deepseek_v4_mega_moe.py
+++ b/tests/models/test_deepseek_v4_mega_moe.py
@@ -18,10 +18,7 @@ from vllm.models.deepseek_v4.nvidia.model import (
 )
 from vllm.models.deepseek_v4.nvidia.mtp import DeepSeekV4MTP
 from vllm.models.deepseek_v4.nvidia.ops.prepare_megamoe import prepare_megamoe_inputs
-from vllm.models.deepseek_v4_1.common.mm_preprocess import (
-    IMAGE_PAD_ID,
-    IMAGE_SENTINEL_BASE_ID,
-)
+from vllm.models.deepseek_v4_1.common.mm_preprocess import IMAGE_SENTINEL_BASE_ID
 from vllm.models.deepseek_v4_1.nvidia.model import DeepseekV4MoE as DeepseekV41MoE
 from vllm.platforms import current_platform
 from vllm.transformers_utils.configs.deepseek_v41 import DeepseekV41Config
@@ -78,7 +75,7 @@ def test_deepseek_v41_moe_routes_without_hash_table(
         moe = DeepseekV41MoE(v41_moe_config, prefix=f"model.layers.{layer_id}.ffn")
         hidden_states = torch.randn(4, config.hidden_size)
         input_ids = (
-            torch.tensor([42, IMAGE_SENTINEL_BASE_ID, IMAGE_PAD_ID, 129257])
+            torch.tensor([42, IMAGE_SENTINEL_BASE_ID, IMAGE_SENTINEL_BASE_ID, 129257])
             if vision
             else None
         )
@@ -100,7 +97,7 @@ def test_deepseek_v41_moe_routes_without_hash_table(
     ).sqrt()
     bias = moe.gate.e_score_correction_bias
     if vision:
-        image_mask = (input_ids == IMAGE_SENTINEL_BASE_ID) | (input_ids == IMAGE_PAD_ID)
+        image_mask = input_ids == IMAGE_SENTINEL_BASE_ID
         bias = torch.where(image_mask[:, None], moe.gate.bias_vl, bias)
     expected_ids = (scores + bias).topk(top_k, dim=-1).indices
     expected_weights = scores.gather(1, expected_ids)