diff --git a/onnxruntime/contrib_ops/cuda/bert/attention_prepare_qkv.cu b/onnxruntime/contrib_ops/cuda/bert/attention_prepare_qkv.cu
index 7b37a3a4227b6..852f0bcaff5a2 100644
--- a/onnxruntime/contrib_ops/cuda/bert/attention_prepare_qkv.cu
+++ b/onnxruntime/contrib_ops/cuda/bert/attention_prepare_qkv.cu
@@ -258,7 +258,9 @@ Status PrepareQkv_MHA_NoPast(contrib::AttentionParameters& parameters,
   assert(data.past_value == nullptr);
   assert(data.present_key == nullptr);
   assert(data.present_value == nullptr);
-  assert(!parameters.is_unidirectional);
+  // Note: is_unidirectional (causal) is supported by flash attention, memory efficient attention,
+  // cuDNN flash attention, and unfused kernel. TRT fused runner is only used when !is_unidirectional
+  // (enforced in MultiHeadAttention::ComputeInternal).
   assert(data.has_qkv_workspace == !NoQkvWorkspace_MHA_NoPast(data));
 
   if (parameters.qkv_format == AttentionQkvFormat::Q_K_V_BSNH) {
diff --git a/onnxruntime/core/providers/cuda/llm/attention.cc b/onnxruntime/core/providers/cuda/llm/attention.cc
index 99f297bba6444..3b7aebc2d4714 100644
--- a/onnxruntime/core/providers/cuda/llm/attention.cc
+++ b/onnxruntime/core/providers/cuda/llm/attention.cc
@@ -191,7 +191,6 @@ Status Attention<T>::ComputeInternal(OpKernelContext* context) const {
     ORT_THROW("softmax_precision is not supported yet in Attention op (CUDA).");
   }
 
-  // TODO(titaiwang): Continue on these parameters
   // Construct AttentionData to pass to QkvToContext
   typedef typename ToCudaType<T>::MappedType CudaT;
   onnxruntime::contrib::cuda::AttentionData<CudaT> data;
@@ -220,12 +219,12 @@ Status Attention<T>::ComputeInternal(OpKernelContext* context) const {
   }
   data.qkv_format = contribop_parameters.qkv_format;
 
-  // TODO: Determine which kernel to use (Flash Attention, Memory Efficient Attention, etc.)
   // For now, set flags to false and let QkvToContext use the unfused path
   data.use_flash_attention = false;
   data.use_memory_efficient_attention = false;
   data.fused_runner = nullptr;
   data.fused_cross_attention_kernel = nullptr;
+  data.kernel_type = onnxruntime::contrib::AttentionKernelType::AttentionKernel_Unfused;
 
   // Allocate workspace for Q, K, V processing and scratch buffer
   const bool no_qkv_workspace = onnxruntime::contrib::cuda::NoQkvWorkspace(contribop_parameters, data);