diff --git a/vllm/model_executor/models/qwen3_omni_moe_thinker.py b/vllm/model_executor/models/qwen3_omni_moe_thinker.py
index 5ca6b3d852ac3..07c5499d0b194 100755
--- a/vllm/model_executor/models/qwen3_omni_moe_thinker.py
+++ b/vllm/model_executor/models/qwen3_omni_moe_thinker.py
@@ -118,7 +118,7 @@ def _get_feat_extract_output_lengths(input_lengths: torch.Tensor):
     output_lengths = (
         ((feat_lengths - 1) // 2 + 1 - 1) // 2 + 1 + (input_lengths // 100) * 13
     )
-    return feat_lengths, output_lengths
+    return output_lengths
 
 
 class Qwen3_VisionPatchEmbed(nn.Module):
@@ -921,13 +921,11 @@ class Qwen3OmniMoeThinkerMultiModalProcessor(
         if audio_feature_lengths is None and feature_attention_mask is None:
             audio_output_lengths = []
         elif audio_feature_lengths is not None:
-            _, audio_output_lens = _get_feat_extract_output_lengths(
-                audio_feature_lengths
-            )
+            audio_output_lens = _get_feat_extract_output_lengths(audio_feature_lengths)
             audio_output_lengths = audio_output_lens.tolist()
         elif feature_attention_mask is not None:
             assert isinstance(feature_attention_mask, torch.Tensor)
-            _, audio_output_lens = _get_feat_extract_output_lengths(
+            audio_output_lens = _get_feat_extract_output_lengths(
                 feature_attention_mask.sum(-1)
             )
             audio_output_lengths = audio_output_lens.tolist()
@@ -1111,18 +1109,16 @@ class Qwen3OmniMoeConditionalGenerationMixin(Qwen2_5OmniConditionalGenerationMix
         audio_input: Qwen2_5OmniAudioFeatureInputs,
         audio_hashes: list[str] | None = None,
         cached_audio_features: torch.Tensor | None = None,
-    ) -> torch.Tensor:
+    ) -> tuple[torch.Tensor, ...]:
         input_features = audio_input["input_features"]
         audio_feature_lengths = audio_input["audio_feature_lengths"]
 
-        audio_feat_lengths, audio_output_lengths = _get_feat_extract_output_lengths(
-            audio_feature_lengths
-        )
+        audio_output_lengths = _get_feat_extract_output_lengths(audio_feature_lengths)
 
         audio_outputs = self.audio_tower(
             input_features.to(self.audio_tower.dtype),
             feature_lens=audio_feature_lengths,
-            aftercnn_lens=audio_feat_lengths,
+            aftercnn_lens=audio_output_lengths,
         )
         audio_features = audio_outputs.last_hidden_state
         return audio_features.split(audio_output_lengths.tolist())
@@ -1579,7 +1575,7 @@ class Qwen3OmniMoeThinkerForConditionalGeneration(
                     + st_idx
                 )
                 st_idx = llm_pos_ids_list[-1].max() + 1 if llm_pos_ids_list else 0
-                _, audio_len = _get_feat_extract_output_lengths(
+                audio_len = _get_feat_extract_output_lengths(
                     audio_feature_lengths[audio_idx]
                 )
                 llm_pos_ids = (
@@ -1700,7 +1696,7 @@ class Qwen3OmniMoeThinkerForConditionalGeneration(
                 llm_pos_ids_list.append(bos_block)
                 llm_pos_ids_list.append(bos_block)
                 st_idx = llm_pos_ids_list[-1].max() + 1 if llm_pos_ids_list else 0
-                _, audio_len = _get_feat_extract_output_lengths(
+                audio_len = _get_feat_extract_output_lengths(
                     audio_feature_lengths[audio_idx]
                 )
                 audio_llm_pos_ids = (