diff --git a/test/_inductor/test_cat.py b/test/_inductor/test_cat.py
index 26d89caaa8dd679975d020621fdeafbb79f78c0a..54d43501ad3be2f8373997a6ebf9a736f4c13976 100644
--- a/test/_inductor/test_cat.py
+++ b/test/_inductor/test_cat.py
@@ -20,6 +20,48 @@ class TestCat(TestUtils):
         inductor_cat = compiled_op_calc(input_element, dim)
         self.assertEqual(std_cat, inductor_cat, atol=1e-1, rtol=1e-1, equal_nan=True)
 
+    def op_calc_non_contiguous(self, input_element, dim):
+        return torch.cat([input_element, input_element], dim)
+
+    @parametrize('shape', [(8, 16, 32, 64)])
+    @parametrize('dim', [1])
+    @parametrize('dtype', ['bfloat16'])
+    def test_cat_non_contiguous(self, shape, dim, dtype):
+        input_element = self._generate_tensor(shape, dtype)
+        input_element = input_element.transpose(-1, -2)
+        std_cat = self.op_calc_non_contiguous(input_element, dim)
+        compiled_op_calc = torch.compile(self.op_calc_non_contiguous, backend="inductor")
+        inductor_cat = compiled_op_calc(input_element, dim)
+        self.assertEqual(std_cat, inductor_cat, atol=1e-1, rtol=1e-1, equal_nan=True)
+
+    class PatternModel(torch.nn.Module):
+        def __init__(self, dim):
+            super().__init__()
+            self.dim = dim
+
+        def forward(self, *xs):
+            slices = [x[..., :sz] for x, sz in zip(xs, (128, 32, 48, 48, 48, 48, 48))]
+            output_tensor = torch.cat(slices, self.dim)
+
+            return output_tensor
+    
+    @parametrize('shape', [(128, 50, 128)])
+    @parametrize('dim', [2])
+    @parametrize('dtype', ['float32', 'bfloat16'])
+    def test_model_input_is_concat(self, shape, dim, dtype):
+        inputs = [self._generate_tensor(shape, dtype) for _ in range(7)]
+
+        model = self.PatternModel(dim).to(dtype=getattr(torch, dtype))
+        model.eval()
+        with torch.no_grad():
+            eager_out = model(*inputs)
+
+        compiled_model = torch.compile(model, backend="inductor")
+        with torch.no_grad():
+            inductor_out = compiled_model(*inputs)
+
+        self.assertEqual(eager_out, inductor_out,
+                        atol=1e-2, rtol=1e-2, equal_nan=True)
 
 instantiate_parametrized_tests(TestCat)