diff --git a/csrc/attention/mla/sm100_cutlass_mla_kernel.cu b/csrc/attention/mla/sm100_cutlass_mla_kernel.cu
index c60f1823b8a1..d1874515cc8f 100644
--- a/csrc/attention/mla/sm100_cutlass_mla_kernel.cu
+++ b/csrc/attention/mla/sm100_cutlass_mla_kernel.cu
@@ -43,6 +43,7 @@ void sm100_cutlass_mla_decode(
     torch::Tensor const& seq_lens,
     torch::Tensor const& page_table,
     torch::Tensor const& workspace,
+    double sm_scale,
     int64_t num_kv_splits) {
   TORCH_CHECK(false, "CUDA version must be >= 12.4 for cutlass_mla_decode");
 }
diff --git a/tests/kernels/moe/test_mxfp4_moe.py b/tests/kernels/moe/test_mxfp4_moe.py
index 9fd72ee152b5..a3b8f07638d9 100644
--- a/tests/kernels/moe/test_mxfp4_moe.py
+++ b/tests/kernels/moe/test_mxfp4_moe.py
@@ -771,11 +771,11 @@ def dequant_mxfp4_batches(mat_fp4: torch.Tensor,
     w13_ref = dequant_mxfp4_batches(
         w13_q.view(torch.uint8),
         w13_scale.view(torch.uint8).reshape(-1)).to(torch.float32).reshape(
-            num_experts, 2 * intermediate_size, hidden_size)
+            num_experts, 2 * intermediate_size, hidden_size).to(device)
     w2_ref = dequant_mxfp4_batches(
         w2_q.view(torch.uint8),
         w2_scale.view(torch.uint8).reshape(-1)).to(torch.float32).reshape(
-            num_experts, hidden_size, intermediate_size)
+            num_experts, hidden_size, intermediate_size).to(device)
 
     # Quantize activations for SM100 path and dequantize for reference
     hidden_states_q, hidden_states_sf = mxfp8_quantize(hidden_states, True, 32)