diff --git a/docling/utils/gpu_utils.py b/docling/utils/gpu_utils.py
new file mode 100644
index 00000000..977cc669
--- /dev/null
+++ b/docling/utils/gpu_utils.py
@@ -0,0 +1,52 @@
+"""Add commentMore actions
+Utilities for managing GPU resources.
+"""
+
+import logging
+import importlib.util
+
+_log = logging.getLogger(__name__)
+
+def clear_gpu_memory():
+    """
+    Clear GPU memory cache for supported frameworks.
+    Currently supports PyTorch and TensorFlow.
+    """
+    # Try to clear PyTorch CUDA cache
+    try:
+        if importlib.util.find_spec("torch") is not None:
+            import torch
+            if torch.cuda.is_available():
+                _log.info("Clearing PyTorch CUDA memory cache")
+                torch.cuda.empty_cache()
+                
+            # Handle Apple MPS (Metal Performance Shaders)
+            if hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
+                _log.info("MPS device detected - note that MPS may not support explicit memory clearing")
+                # MPS doesn't have an explicit memory clearing mechanism like CUDA
+                # But we can try to force garbage collection
+                import gc
+                gc.collect()
+    except Exception as e:
+        _log.warning(f"Failed to clear PyTorch GPU memory: {e}")
+    
+    # Try to clear TensorFlow GPU memory
+    try:
+        if importlib.util.find_spec("tensorflow") is not None:
+            import tensorflow as tf
+            if len(tf.config.list_physical_devices('GPU')) > 0:
+                _log.info("Clearing TensorFlow GPU memory")
+                for device in tf.config.list_physical_devices('GPU'):
+                    try:
+                        tf.config.experimental.reset_memory_stats(device)
+                    except Exception as e:
+                        _log.warning(f"Failed to reset memory stats for device {device}: {e}")
+    except Exception as e:
+        _log.warning(f"Failed to clear TensorFlow GPU memory: {e}")
+    
+    # Force Python garbage collection
+    try:
+        import gc
+        gc.collect()
+    except Exception as e:
+        _log.warning(f"Failed to run garbage collection: {e}")