diff --git a/src/cunumpy/_cuda_kernel.py b/src/cunumpy/_cuda_kernel.py
index fafd890..e072149 100644
--- a/src/cunumpy/_cuda_kernel.py
+++ b/src/cunumpy/_cuda_kernel.py
@@ -2421,6 +2421,10 @@ def __call__(
         if shared_mem < 0:
             raise ValueError(f"shared_mem must be non-negative, got {shared_mem}")
         values = self.prepare_args(*args)
+        # RawKernel accepts size-one NumPy arrays for structs passed by value,
+        # but not structured NumPy scalars (np.void). Keep their packed bytes
+        # and alignment intact, including array-view pointers and strides.
+        values = tuple(np.asarray(v) if isinstance(v, np.void) else v for v in values)
         if 0 in grid_shape:
             return
 
diff --git a/tests/unit/test_cuda_kernel.py b/tests/unit/test_cuda_kernel.py
index 0ef8c8c..b268f36 100644
--- a/tests/unit/test_cuda_kernel.py
+++ b/tests/unit/test_cuda_kernel.py
@@ -2306,6 +2306,7 @@ def __init__(self):
 
     def __call__(self, grid, block, args, shared_mem=0):
         self.launches.append((grid, block, shared_mem))
+        self.args = args
 
 
 @pytest.fixture
@@ -2333,6 +2334,28 @@ def recorded(monkeypatch):
     return kernel, raw
 
 
+def test_launch_passes_structs_as_size_one_numpy_arrays(recorded, monkeypatch):
+    kernel, raw = recorded
+    packed = np.zeros((), dtype=[("data", np.uintp), ("shape", np.int64, (1,))])
+    packed["data"] = 0x1000
+    packed["shape"] = (7,)
+    scalar = np.float64(2.0)
+    device_array = FakeDeviceArray(np.float64, shape=(7,))
+    monkeypatch.setattr(
+        kernel, "prepare_args", lambda *args: (packed[()], scalar, device_array)
+    )
+
+    kernel(n_threads=1)
+
+    struct_arg, scalar_arg, pointer_arg = raw.args
+    assert isinstance(struct_arg, np.ndarray)
+    assert struct_arg.size == 1
+    assert struct_arg.dtype == packed.dtype
+    assert struct_arg.tobytes() == packed.tobytes()
+    assert scalar_arg is scalar
+    assert pointer_arg is device_array
+
+
 def test_n_threads_from_first_array(recorded):
     kernel, raw = recorded
     kernel.n_threads_from = "first_array"