diff --git a/vllm/patches/deepseek_v4_attention.py b/vllm/patches/deepseek_v4_attention.py
index 501898d1..53fdcb07 100644
--- a/vllm/patches/deepseek_v4_attention.py
+++ b/vllm/patches/deepseek_v4_attention.py
@@ -372,8 +372,12 @@ class DeepseekV4MultiHeadLatentAttentionWrapper(PluggableLayer):
                 wkv_wgate_weight = compressor.fused_wkv_wgate.weight
                 if wkv_wgate_weight.dtype == torch.uint8:
                     # NVFP4 packed weights — use forward() for dequant+matmul
-                    score, _ = compressor.fused_wkv_wgate(hidden_states)
-                    return score.to(torch.float32)
+                    result = compressor.fused_wkv_wgate(hidden_states)
+                    # MergedColumnParallelLinear may return (output, bias) or
+                    # just output depending on quantization method.
+                    if isinstance(result, tuple):
+                        result = result[0]
+                    return result.to(torch.float32)
                 return torch.mm(
                     hidden_states,
                     wkv_wgate_weight.T,
@@ -393,8 +397,10 @@ class DeepseekV4MultiHeadLatentAttentionWrapper(PluggableLayer):
             def indexer_compressor_kv_score() -> torch.Tensor:
                 wkv_wgate_weight = indexer.compressor.fused_wkv_wgate.weight
                 if wkv_wgate_weight.dtype == torch.uint8:
-                    score, _ = indexer.compressor.fused_wkv_wgate(hidden_states)
-                    return score.to(torch.float32)
+                    result = indexer.compressor.fused_wkv_wgate(hidden_states)
+                    if isinstance(result, tuple):
+                        result = result[0]
+                    return result.to(torch.float32)
                 return torch.mm(
                     hidden_states,
                     wkv_wgate_weight.T,