diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5e790c38cfcd6..becf55676c73d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -153,6 +153,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed truncated backprop through time enablement when set as a property on the LightningModule and not the Trainer ([#8804](https://github.com/PyTorchLightning/pytorch-lightning/pull/8804/))
 
 
+- Fixed an issues with export to ONNX format when a model has multiple inputs ([#8800](https://github.com/PyTorchLightning/pytorch-lightning/pull/8800))
+
+
 ## [1.4.0] - 2021-07-27
 
 ### Added
diff --git a/pytorch_lightning/core/lightning.py b/pytorch_lightning/core/lightning.py
index b4a50bf10a577..a2f238c0836d8 100644
--- a/pytorch_lightning/core/lightning.py
+++ b/pytorch_lightning/core/lightning.py
@@ -1891,7 +1891,10 @@ def to_onnx(self, file_path: Union[str, Path], input_sample: Optional[Any] = Non
 
         if "example_outputs" not in kwargs:
             self.eval()
-            kwargs["example_outputs"] = self(input_sample)
+            if isinstance(input_sample, Tuple):
+                kwargs["example_outputs"] = self(*input_sample)
+            else:
+                kwargs["example_outputs"] = self(input_sample)
 
         torch.onnx.export(self, input_sample, file_path, **kwargs)
         self.train(mode)
diff --git a/tests/models/test_onnx.py b/tests/models/test_onnx.py
index cec01e828d1ed..7cd1d2776f43c 100644
--- a/tests/models/test_onnx.py
+++ b/tests/models/test_onnx.py
@@ -23,6 +23,7 @@
 from pytorch_lightning import Trainer
 from tests.helpers import BoringModel
 from tests.helpers.runif import RunIf
+from tests.utilities.test_model_summary import UnorderedModel
 
 
 def test_model_saves_with_input_sample(tmpdir):
@@ -66,10 +67,17 @@ def test_model_saves_with_example_output(tmpdir):
     assert os.path.exists(file_path) is True
 
 
-def test_model_saves_with_example_input_array(tmpdir):
-    """Test that ONNX model saves with_example_input_array and size is greater than 3 MB"""
-    model = BoringModel()
-    model.example_input_array = torch.randn(5, 32)
+@pytest.mark.parametrize(
+    ["modelclass", "input_sample"],
+    [
+        (BoringModel, torch.randn(1, 32)),
+        (UnorderedModel, (torch.rand(2, 3), torch.rand(2, 10))),
+    ],
+)
+def test_model_saves_with_example_input_array(tmpdir, modelclass, input_sample):
+    """Test that ONNX model saves with example_input_array and size is greater than 3 MB"""
+    model = modelclass()
+    model.example_input_array = input_sample
 
     file_path = os.path.join(tmpdir, "model.onnx")
     model.to_onnx(file_path)