diff --git a/monai/networks/blocks/activation_checkpointing.py b/monai/networks/blocks/activation_checkpointing.py
new file mode 100644
index 0000000000..283bcd19e1
--- /dev/null
+++ b/monai/networks/blocks/activation_checkpointing.py
@@ -0,0 +1,41 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from typing import cast
+
+import torch
+import torch.nn as nn
+from torch.utils.checkpoint import checkpoint
+
+
+class ActivationCheckpointWrapper(nn.Module):
+    """Wrapper applying activation checkpointing to a module during training.
+
+    Args:
+        module: The module to wrap with activation checkpointing.
+    """
+
+    def __init__(self, module: nn.Module) -> None:
+        super().__init__()
+        self.module = module
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        """Forward pass with optional activation checkpointing.
+
+        Args:
+            x: Input tensor.
+
+        Returns:
+            Output tensor from the wrapped module.
+        """
+        return cast(torch.Tensor, checkpoint(self.module, x, use_reentrant=False))
diff --git a/monai/networks/nets/unet.py b/monai/networks/nets/unet.py
index eac0ddab39..1fa5cbf7f2 100644
--- a/monai/networks/nets/unet.py
+++ b/monai/networks/nets/unet.py
@@ -17,11 +17,12 @@
 import torch
 import torch.nn as nn
 
+from monai.networks.blocks.activation_checkpointing import ActivationCheckpointWrapper
 from monai.networks.blocks.convolutions import Convolution, ResidualUnit
 from monai.networks.layers.factories import Act, Norm
 from monai.networks.layers.simplelayers import SkipConnection
 
-__all__ = ["UNet", "Unet"]
+__all__ = ["UNet", "Unet", "CheckpointUNet"]
 
 
 class UNet(nn.Module):
@@ -298,4 +299,19 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         return x
 
 
+class CheckpointUNet(UNet):
+    """UNet variant that wraps internal connection blocks with activation checkpointing.
+
+    See `UNet` for constructor arguments. During training with gradients enabled,
+    intermediate activations inside encoder–decoder connections are recomputed in
+    the backward pass to reduce peak memory usage at the cost of extra compute.
+    """
+
+    def _get_connection_block(self, down_path: nn.Module, up_path: nn.Module, subblock: nn.Module) -> nn.Module:
+        subblock = ActivationCheckpointWrapper(subblock)
+        down_path = ActivationCheckpointWrapper(down_path)
+        up_path = ActivationCheckpointWrapper(up_path)
+        return super()._get_connection_block(down_path, up_path, subblock)
+
+
 Unet = UNet