diff --git a/cpp/tensorrt_llm/thop/cublasScaledMM.cpp b/cpp/tensorrt_llm/thop/cublasScaledMM.cpp
index d39b7b693fe..f4b2291e6c1 100644
--- a/cpp/tensorrt_llm/thop/cublasScaledMM.cpp
+++ b/cpp/tensorrt_llm/thop/cublasScaledMM.cpp
@@ -343,11 +343,7 @@ TORCH_LIBRARY_FRAGMENT(trtllm, m)
     m.def(
         "cublas_scaled_mm(Tensor mat_a, Tensor mat_b, Tensor scale_a, Tensor scale_b, Tensor? bias,"
         " ScalarType? out_dtype, bool to_userbuffers=False) -> (Tensor out)");
-    m.def(
-        "cublas_scaled_mm_out(Tensor mat_a, Tensor mat_b, Tensor scale_a, Tensor scale_b, Tensor? bias,"
-        " int userbuffers_id, Tensor! out) -> (Tensor out)");
     m.def("cublas_mm(Tensor mat_a, Tensor mat_b, Tensor? bias, ScalarType? out_dtype) -> (Tensor out)");
-    m.def("cublas_mm_out(Tensor mat_a, Tensor mat_b, Tensor? bias, Tensor! out) -> (Tensor out)");
 }
 
 TORCH_LIBRARY_IMPL(trtllm, CUDA, m)
diff --git a/tests/unittest/_torch/test_custom_ops.py b/tests/unittest/_torch/test_custom_ops.py
new file mode 100644
index 00000000000..9a50468ae30
--- /dev/null
+++ b/tests/unittest/_torch/test_custom_ops.py
@@ -0,0 +1,106 @@
+import pytest
+import torch
+import torch._library.utils as library_utils
+
+import tensorrt_llm  # noqa: F401
+
+
+def discover_namespace_ops(namespace: str, prefix: str = ""):
+    """Discover custom ops in a specific namespace."""
+    # C++ custom ops are lazy loaded, cannot use torch.ops.x to discover all custom ops.
+    # Use schemas to discover instead.
+    ops_schemas = torch._C._jit_get_all_schemas()
+    ops = []
+
+    ns_prefix = f"{namespace}::{prefix}"
+    print("Discovering custom ops:")
+    for schema in ops_schemas:
+        if not schema.name.startswith(ns_prefix):
+            continue
+        op = library_utils.lookup_op(schema.name)
+        ops.append(op)
+        print(f"    {op._name}")
+    return ops
+
+
+def discover_custom_ops(namespaces):
+    """Discover all custom ops in the codebase."""
+    discovered_ops = []
+    for ns in namespaces:
+        ops = discover_namespace_ops(ns)
+        print(f"Total {len(ops)} custom ops in namespace {ns}")
+        discovered_ops.extend(ops)
+    return discovered_ops
+
+
+@pytest.fixture(scope="module", autouse=True)
+def custom_ops():
+    """Discover custom ops in the codebase."""
+    # "auto_deploy" custom ops are not checked here.
+    custom_op_namespaces = ("trtllm", )
+
+    return discover_custom_ops(custom_op_namespaces)
+
+
+# Better to add OpInfo for each custom op, and use opcheck to test the custom ops.
+# Currently OpInfo for custom ops are not available in the codebase.
+# As a trade-off, only fake registration is checked.
+def test_register_fake(custom_ops):
+    """Test custom operator fake impl registration."""
+
+    # Custom ops that are not required to have fake impl.
+    waivers = {
+        "trtllm::record_stream",
+        "trtllm::wait_event",
+        "trtllm::record_event",
+        "trtllm::set_stream",
+    }
+
+    # TODO: add fake impl for these ops in follow-up PRs.
+    to_fix = {
+        "trtllm::lora_grouped_gemm",
+        "trtllm::mtp_relaxed_acceptance_op",
+        "trtllm::mtp_update_hidden_states_op",
+        "trtllm::mtp_prepare_drafter_inputs_op",
+        "trtllm::selective_scan",
+        "trtllm::reducescatter_list",
+        "trtllm::fp8_per_tensor_scale_moe_runner",
+        "trtllm::migrate_to_host_accessible",
+        "trtllm::mnnvl_moe_alltoallv_prepare_without_allgather",
+        "trtllm::mamba_conv1d",
+        "trtllm::llama4_moe_tp8ep1_min_latency",
+        "trtllm::llama4_fp8_fp8_gemm_swiglu",
+        "trtllm::llama4_fp8_bf16_gemm",
+        "trtllm::llama4_bf16_bf16_gemm",
+        "trtllm::fused_topk_softmax",
+        "trtllm::fp8_batched_quantize_1x128_permute102",
+        "trtllm::fp8_block_scaling_moe_gemm",
+        "trtllm::fp8_block_scaling_bmm_out",
+        "trtllm::fp8_block_scaling_bmm",
+        "trtllm::fp4_batched_quantize",
+        "trtllm::fp4_gemm_trtllmgen",
+        "trtllm::fp4_bmm",
+        "trtllm::merge_chunked_attention_for_mla",
+        "trtllm::cuda_scaled_mm",
+        "trtllm::initialize_static_lowprecision_buffers",
+        "trtllm::cutlass_scaled_mm",
+        "trtllm::fp8_per_tensor_scaling_tllmg_gemm",
+        "trtllm::load_chunked_kv_cache_for_mla",
+        "trtllm::load_paged_kv_cache_for_mla",
+        "trtllm::set_paged_kv_cache_for_mla",
+        "trtllm::set_chunked_kv_cache_for_mla",
+        "trtllm::mla_rope_append_paged_kv_assign_q",
+        "trtllm::fused_qk_norm_rope",
+    }
+
+    ops_missing_fake_impl = []
+
+    for op in custom_ops:
+        if op._name in waivers or op._name in to_fix:
+            continue
+        if not library_utils.has_fake_kernel(op):
+            ops_missing_fake_impl.append(op)
+
+    names = ", ".join(op._name for op in ops_missing_fake_impl)
+    assert len(
+        ops_missing_fake_impl) == 0, f"Custom ops missing fake impl: {names}"