diff --git a/tests/test_swin_unetr.py b/tests/test_swin_unetr.py
index 9f6b1e7c0a..e34e5a3c8e 100644
--- a/tests/test_swin_unetr.py
+++ b/tests/test_swin_unetr.py
@@ -24,13 +24,21 @@
 from monai.networks.nets.swin_unetr import PatchMerging, PatchMergingV2, SwinUNETR, filter_swinunetr
 from monai.networks.utils import copy_model_state
 from monai.utils import optional_import
-from tests.utils import assert_allclose, skip_if_downloading_fails, skip_if_no_cuda, skip_if_quick, testing_data_config
+from tests.utils import (
+    assert_allclose,
+    pytorch_after,
+    skip_if_downloading_fails,
+    skip_if_no_cuda,
+    skip_if_quick,
+    testing_data_config,
+)
 
 einops, has_einops = optional_import("einops")
 
 TEST_CASE_SWIN_UNETR = []
 case_idx = 0
 test_merging_mode = ["mergingv2", "merging", PatchMerging, PatchMergingV2]
+checkpoint_vals = [True, False] if pytorch_after(1, 11) else [False]
 for attn_drop_rate in [0.4]:
     for in_channels in [1]:
         for depth in [[2, 1, 1, 1], [1, 2, 1, 1]]:
@@ -38,23 +46,25 @@
                 for img_size in ((64, 32, 192), (96, 32)):
                     for feature_size in [12]:
                         for norm_name in ["instance"]:
-                            test_case = [
-                                {
-                                    "spatial_dims": len(img_size),
-                                    "in_channels": in_channels,
-                                    "out_channels": out_channels,
-                                    "img_size": img_size,
-                                    "feature_size": feature_size,
-                                    "depths": depth,
-                                    "norm_name": norm_name,
-                                    "attn_drop_rate": attn_drop_rate,
-                                    "downsample": test_merging_mode[case_idx % 4],
-                                },
-                                (2, in_channels, *img_size),
-                                (2, out_channels, *img_size),
-                            ]
-                            case_idx += 1
-                            TEST_CASE_SWIN_UNETR.append(test_case)
+                            for use_checkpoint in checkpoint_vals:
+                                test_case = [
+                                    {
+                                        "spatial_dims": len(img_size),
+                                        "in_channels": in_channels,
+                                        "out_channels": out_channels,
+                                        "img_size": img_size,
+                                        "feature_size": feature_size,
+                                        "depths": depth,
+                                        "norm_name": norm_name,
+                                        "attn_drop_rate": attn_drop_rate,
+                                        "downsample": test_merging_mode[case_idx % 4],
+                                        "use_checkpoint": use_checkpoint,
+                                    },
+                                    (2, in_channels, *img_size),
+                                    (2, out_channels, *img_size),
+                                ]
+                                case_idx += 1
+                                TEST_CASE_SWIN_UNETR.append(test_case)
 
 TEST_CASE_FILTER = [
     [