diff --git a/c10/core/TensorImpl.cpp b/c10/core/TensorImpl.cpp
index 47af1d91793f8f..c6244bc81ed57b 100644
--- a/c10/core/TensorImpl.cpp
+++ b/c10/core/TensorImpl.cpp
@@ -923,10 +923,13 @@ void TensorImpl::empty_tensor_restride_symint(MemoryFormat memory_format) {
       sym_shape_meta.strides_.resize(dim_);
       if (dim_ > 0) {
         const auto last_idx = dim_ - 1;
+        auto accum = c10::SymInt(1);
         sym_shape_meta.strides_[last_idx] = c10::SymInt(1);
         for (auto i = last_idx - 1; i >= 0; --i) {
-          sym_shape_meta.strides_[i] = sym_shape_meta.strides_[i + 1] *
-              sym_shape_meta.sizes_[i + 1].max(1);
+          if (TORCH_GUARD_OR_TRUE(sym_shape_meta.sizes_[i + 1].sym_gt(1))) {
+            accum *= sym_shape_meta.sizes_[i + 1];
+          }
+          sym_shape_meta.strides_[i] = accum;
         }
       }
       break;
diff --git a/test/export/test_export.py b/test/export/test_export.py
index 5e7d9a436e3d71..844be1e0ffccf9 100755
--- a/test/export/test_export.py
+++ b/test/export/test_export.py
@@ -4406,6 +4406,19 @@ def forward(self, xs, y):
                 strict=strict,
             )
 
+    def test_contiguous_unbacked_strides(self):
+        class Foo(torch.nn.Module):
+            def forward(self, xs):
+                u0, u1, u2 = xs.tolist()
+                return torch.empty(u0, u1, u2).contiguous()
+
+        ep = export(Foo(), (torch.tensor([2, 3, 4]),))
+        node = [node for node in ep.graph.nodes][-2]
+        val = node.meta["val"]
+        u0, u1, u2 = val.shape
+        self.assertEqual(val.stride(0), u1 * u2)
+        self.assertEqual(val.stride(1), u2)
+
     def test_tolist(self):
         class M(torch.nn.Module):
             def forward(self, x):
diff --git a/test/test_dynamic_shapes.py b/test/test_dynamic_shapes.py
index a3458efbe65b2b..c023ca91ae74ae 100644
--- a/test/test_dynamic_shapes.py
+++ b/test/test_dynamic_shapes.py
@@ -885,7 +885,7 @@ def test_non_overlapping_and_dense_unbacked(self):
             cf(
                 torch.empty_strided(
                     (2, 3, 1, u0),
-                    (3 * Max(1, u0), Max(1, u0), Max(1, u0), 1),
+                    (3 * u0, u0, u0, 1),
                     device="meta",
                 )
             )
diff --git a/torch/_prims_common/__init__.py b/torch/_prims_common/__init__.py
index e8339b789f5442..cc4c94e7df447b 100644
--- a/torch/_prims_common/__init__.py
+++ b/torch/_prims_common/__init__.py
@@ -1638,15 +1638,14 @@ def make_contiguous_strides_for(
     if not shape:
         return ()
 
-    from torch.fx.experimental.symbolic_shapes import is_nested_int
+    from torch.fx.experimental.symbolic_shapes import guard_or_true, is_nested_int
 
     multiplier: Union[_IntLikeT, int] = 1
     strides = []
     for l in reversed(shape):
         strides.append(multiplier)
-        multiplier *= (
-            l if is_nested_int(l) else sym_max(l, 1)
-        )  # type:ignore[assignment]
+        if is_nested_int(l) or guard_or_true(l >= 1):
+            multiplier *= l  # type:ignore[assignment]
 
     result = tuple(reversed(strides))