diff --git a/cuda_core/cuda/core/experimental/_device.py b/cuda_core/cuda/core/experimental/_device.py
index 6be8077b8..22cf7419e 100644
--- a/cuda_core/cuda/core/experimental/_device.py
+++ b/cuda_core/cuda/core/experimental/_device.py
@@ -957,34 +957,42 @@ def __new__(cls, device_id=None):
 
         # important: creating a Device instance does not initialize the GPU!
         if device_id is None:
-            device_id = handle_return(runtime.cudaGetDevice())
-            assert_type(device_id, int)
+            err, dev = driver.cuCtxGetDevice()
+            if err == 0:
+                device_id = int(dev)
+            else:
+                ctx = handle_return(driver.cuCtxGetCurrent())
+                assert int(ctx) == 0
+                device_id = 0  # cudart behavior
+            assert isinstance(device_id, int), f"{device_id=}"
         else:
-            total = handle_return(runtime.cudaGetDeviceCount())
-            assert_type(device_id, int)
-            if not (0 <= device_id < total):
+            total = handle_return(driver.cuDeviceGetCount())
+            if not isinstance(device_id, int) or not (0 <= device_id < total):
                 raise ValueError(f"device_id must be within [0, {total}), got {device_id}")
 
         # ensure Device is singleton
         if not hasattr(_tls, "devices"):
-            total = handle_return(runtime.cudaGetDeviceCount())
+            total = handle_return(driver.cuDeviceGetCount())
             _tls.devices = []
             for dev_id in range(total):
                 dev = super().__new__(cls)
+
                 dev._id = dev_id
                 # If the device is in TCC mode, or does not support memory pools for some other reason,
                 # use the SynchronousMemoryResource which does not use memory pools.
                 if (
                     handle_return(
-                        runtime.cudaDeviceGetAttribute(runtime.cudaDeviceAttr.cudaDevAttrMemoryPoolsSupported, 0)
+                        driver.cuDeviceGetAttribute(
+                            driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MEMORY_POOLS_SUPPORTED, dev_id
+                        )
                     )
                 ) == 1:
                     dev._mr = _DefaultAsyncMempool(dev_id)
                 else:
                     dev._mr = _SynchronousMemoryResource(dev_id)
-
                 dev._has_inited = False
                 dev._properties = None
+
                 _tls.devices.append(dev)
 
         return _tls.devices[device_id]