diff --git a/monai/networks/nets/autoencoder.py b/monai/networks/nets/autoencoder.py
index c2239450f2..8d0aadafd6 100644
--- a/monai/networks/nets/autoencoder.py
+++ b/monai/networks/nets/autoencoder.py
@@ -53,6 +53,10 @@ def __init__(
         self.inter_channels = inter_channels if inter_channels is not None else list()
         self.inter_dilations = list(inter_dilations or [1] * len(self.inter_channels))
 
+        # The number of channels and strides should match
+        if len(channels) != len(strides):
+            raise ValueError("Autoencoder expects matching number of channels and strides")
+
         self.encoded_channels = in_channels
         decode_channel_list = list(channels[-2::-1]) + [out_channels]
 
diff --git a/tests/test_autoencoder.py b/tests/test_autoencoder.py
index a7749d7f3a..86b31e0361 100644
--- a/tests/test_autoencoder.py
+++ b/tests/test_autoencoder.py
@@ -62,6 +62,15 @@
 CASES = [TEST_CASE_0, TEST_CASE_1, TEST_CASE_2, TEST_CASE_3]
 
 
+TEST_CASE_FAIL = {  # 2-channel 2D, should fail because of stride/channel mismatch.
+    "dimensions": 2,
+    "in_channels": 2,
+    "out_channels": 2,
+    "channels": (4, 8, 16),
+    "strides": (2, 2),
+}
+
+
 class TestAutoEncoder(unittest.TestCase):
     @parameterized.expand(CASES)
     def test_shape(self, input_param, input_shape, expected_shape):
@@ -76,6 +85,10 @@ def test_script(self):
         test_data = torch.randn(2, 1, 32, 32)
         test_script_save(net, test_data)
 
+    def test_channel_stride_difference(self):
+        with self.assertRaises(ValueError):
+            net = AutoEncoder(**TEST_CASE_FAIL)
+
 
 if __name__ == "__main__":
     unittest.main()