diff --git a/tests/kernels/moe/utils.py b/tests/kernels/moe/utils.py
index 6cf01ac47..ef72b96be 100644
--- a/tests/kernels/moe/utils.py
+++ b/tests/kernels/moe/utils.py
@@ -7,11 +7,6 @@ import vllm._custom_ops as ops
 from tests.kernels.quant_utils import per_block_cast_to_int8
 from tests.kernels.quantization.nvfp4_utils import FLOAT4_E2M1_MAX, FLOAT8_E4M3_MAX
 from vllm.model_executor.layers.activation import SiluAndMul
-from vllm.model_executor.layers.fused_moe import (
-    TritonExperts,
-    fused_experts,
-    fused_topk,
-)
 from vllm.model_executor.layers.fused_moe.activation import MoEActivation
 from vllm.model_executor.layers.fused_moe.config import (
     FusedMoEConfig,
@@ -24,10 +19,15 @@ from vllm.model_executor.layers.fused_moe.fused_batched_moe import (
     BatchedTritonExperts,
     NaiveBatchedExperts,
 )
+from vllm.model_executor.layers.fused_moe.fused_moe import (
+    TritonExperts,
+    fused_experts,
+)
 from vllm.model_executor.layers.fused_moe.modular_kernel import FusedMoEModularKernel
 from vllm.model_executor.layers.fused_moe.prepare_finalize import (
     MoEPrepareAndFinalizeNoEP,
 )
+from vllm.model_executor.layers.fused_moe.router.fused_topk_router import fused_topk
 from vllm.model_executor.layers.fused_moe.utils import moe_kernel_quantize_input
 from vllm.utils.deep_gemm import per_block_cast_to_fp8
 from vllm.utils.math_utils import round_up