diff --git a/.github/workflows/install_gpu_driver.ps1 b/.github/workflows/install_gpu_driver.ps1
deleted file mode 100644
index 256c5cf3a9..0000000000
--- a/.github/workflows/install_gpu_driver.ps1
+++ /dev/null
@@ -1,35 +0,0 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# SPDX-License-Identifier: Apache-2.0
-
-# Install the driver
-function Install-Driver {
-
-    # Set the correct URL, filename, and arguments to the installer
-    # This driver is picked to support Windows 11 & CUDA 13.0
-    $url = 'https://us.download.nvidia.com/tesla/580.88/580.88-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe';
-    $file_dir = 'C:\NVIDIA-Driver\580.88-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe';
-    $install_args = '/s /noeula /noreboot';
-
-    # Create the folder for the driver download
-    if (!(Test-Path -Path 'C:\NVIDIA-Driver')) {
-        New-Item -Path 'C:\' -Name 'NVIDIA-Driver' -ItemType 'directory' | Out-Null
-    }
-
-    # Download the file to a specified directory
-    # Disabling progress bar due to https://github.com/GoogleCloudPlatform/compute-gpu-installation/issues/29
-    $ProgressPreference_tmp = $ProgressPreference
-    $ProgressPreference = 'SilentlyContinue'
-    Write-Output 'Downloading the driver installer...'
-    Invoke-WebRequest $url -OutFile $file_dir
-    $ProgressPreference = $ProgressPreference_tmp
-    Write-Output 'Download complete!'
-
-    # Install the file with the specified path from earlier
-    Write-Output 'Running the driver installer...'
-    Start-Process -FilePath $file_dir -ArgumentList $install_args -Wait
-    Write-Output 'Done!'
-}
-
-# Run the functions
-Install-Driver
diff --git a/.github/workflows/test-wheel-linux.yml b/.github/workflows/test-wheel-linux.yml
index f763d65b9d..ebcc47af13 100644
--- a/.github/workflows/test-wheel-linux.yml
+++ b/.github/workflows/test-wheel-linux.yml
@@ -36,8 +36,6 @@ jobs:
     steps:
       - name: Checkout ${{ github.event.repository.name }}
         uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8  # v5.0.0
-        with:
-          fetch-depth: 1
 
       - name: Validate Test Type
         run: |
@@ -76,7 +74,7 @@ jobs:
           echo "MATRIX=${MATRIX}" | tee --append "${GITHUB_OUTPUT}"
 
   test:
-    name: py${{ matrix.PY_VER }}, ${{ matrix.CUDA_VER }}, ${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}, GPU ${{ matrix.GPU }}
+    name: py${{ matrix.PY_VER }}, ${{ matrix.CUDA_VER }}, ${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}, ${{ matrix.GPU }}
     needs: compute-matrix
     strategy:
       fail-fast: false
@@ -97,8 +95,6 @@ jobs:
 
       - name: Checkout ${{ github.event.repository.name }}
         uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8  # v5.0.0
-        with:
-          fetch-depth: 0
 
       - name: Setup proxy cache
         uses: nv-gha-runners/setup-proxy-cache@main
diff --git a/.github/workflows/test-wheel-windows.yml b/.github/workflows/test-wheel-windows.yml
index 93b81ff0a7..6152df55dc 100644
--- a/.github/workflows/test-wheel-windows.yml
+++ b/.github/workflows/test-wheel-windows.yml
@@ -34,8 +34,6 @@ jobs:
     steps:
       - name: Checkout ${{ github.event.repository.name }}
         uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8  # v5.0.0
-        with:
-          fetch-depth: 1
 
       - name: Validate Test Type
         run: |
@@ -65,7 +63,7 @@ jobs:
           echo "MATRIX=${MATRIX}" | tee --append "${GITHUB_OUTPUT}"
 
   test:
-    name: py${{ matrix.PY_VER }}, ${{ matrix.CUDA_VER }}, ${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}, GPU ${{ matrix.GPU }}
+    name: py${{ matrix.PY_VER }}, ${{ matrix.CUDA_VER }}, ${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}, ${{ matrix.GPU }} (${{ matrix.DRIVER_MODE }})
     # The build stage could fail but we want the CI to keep moving.
     needs: compute-matrix
     strategy:
@@ -76,19 +74,29 @@ jobs:
     steps:
       - name: Checkout ${{ github.event.repository.name }}
         uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8  # v5.0.0
-        with:
-          fetch-depth: 0
 
       - name: Setup proxy cache
         uses: nv-gha-runners/setup-proxy-cache@main
         continue-on-error: true
 
       - name: Update driver
+        env:
+          DRIVER_MODE: ${{ matrix.DRIVER_MODE }}
+          GPU_TYPE: ${{ matrix.GPU }}
         run: |
-          .github/workflows/install_gpu_driver.ps1
+          ci/tools/install_gpu_driver.ps1
 
       - name: Ensure GPU is working
-        run: nvidia-smi
+        run: |
+          nvidia-smi
+
+          $mode_output = nvidia-smi | Select-String -Pattern "${{ matrix.DRIVER_MODE }}"
+          Write-Output "Driver mode check: $mode_output"
+          if ("$mode_output" -eq "") {
+            Write-Error "Switching to driver mode ${{ matrix.DRIVER_MODE }} failed!"
+            exit 1
+          }
+          Write-Output "Driver mode verified: ${{ matrix.DRIVER_MODE }}"
 
       - name: Set environment variables
         env:
diff --git a/ci/test-matrix.json b/ci/test-matrix.json
index d1110cfcde..6c5f201acb 100644
--- a/ci/test-matrix.json
+++ b/ci/test-matrix.json
@@ -1,6 +1,6 @@
 {
   "_description": "Test matrix configurations for CUDA Python CI workflows. This file consolidates the test matrices that were previously hardcoded in the workflow files. All GPU and ARCH values are hard-coded for each architecture: l4 GPU for amd64, a100 GPU for arm64.",
-  "_sorted_by": "Please keep matrices sorted in ascending order by [ARCH, PY_VER, CUDA_VER, LOCAL_CTK, GPU, DRIVER]",
+  "_sorted_by": "Please keep matrices sorted in ascending order by [ARCH, PY_VER, CUDA_VER, LOCAL_CTK, GPU, DRIVER]. Windows entries also include DRIVER_MODE.",
   "_notes": "DRIVER: 'earliest' does not work with CUDA 12.9.1 and LOCAL_CTK: 0 does not work with CUDA 12.0.1",
   "linux": {
     "pull-request": [
@@ -25,48 +25,7 @@
       { "ARCH": "arm64", "PY_VER": "3.14", "CUDA_VER": "13.0.2", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
       { "ARCH": "arm64", "PY_VER": "3.14t", "CUDA_VER": "13.0.2", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" }
     ],
-    "nightly": [
-      { "ARCH": "amd64", "PY_VER": "3.10", "CUDA_VER": "11.8.0", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "earliest" },
-      { "ARCH": "amd64", "PY_VER": "3.10", "CUDA_VER": "11.8.0", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.10", "CUDA_VER": "12.0.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.10", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.10", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.11", "CUDA_VER": "11.8.0", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "earliest" },
-      { "ARCH": "amd64", "PY_VER": "3.11", "CUDA_VER": "11.8.0", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.11", "CUDA_VER": "12.0.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.11", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.11", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "11.8.0", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "earliest" },
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "11.8.0", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "12.0.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "11.8.0", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "earliest" },
-      { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "11.8.0", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "12.0.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.10", "CUDA_VER": "11.8.0", "LOCAL_CTK": "0", "GPU": "a100", "DRIVER": "earliest" },
-      { "ARCH": "arm64", "PY_VER": "3.10", "CUDA_VER": "11.8.0", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.10", "CUDA_VER": "12.0.1", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.10", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.10", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.11", "CUDA_VER": "11.8.0", "LOCAL_CTK": "0", "GPU": "a100", "DRIVER": "earliest" },
-      { "ARCH": "arm64", "PY_VER": "3.11", "CUDA_VER": "11.8.0", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.11", "CUDA_VER": "12.0.1", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.11", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.11", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.12", "CUDA_VER": "11.8.0", "LOCAL_CTK": "0", "GPU": "a100", "DRIVER": "earliest" },
-      { "ARCH": "arm64", "PY_VER": "3.12", "CUDA_VER": "11.8.0", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.12", "CUDA_VER": "12.0.1", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.12", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.12", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.13", "CUDA_VER": "11.8.0", "LOCAL_CTK": "0", "GPU": "a100", "DRIVER": "earliest" },
-      { "ARCH": "arm64", "PY_VER": "3.13", "CUDA_VER": "11.8.0", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.13", "CUDA_VER": "12.0.1", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.13", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "a100", "DRIVER": "latest" },
-      { "ARCH": "arm64", "PY_VER": "3.13", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest" }
-    ],
+    "nightly": [],
     "special_runners": {
       "amd64": [
         { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "13.0.2", "LOCAL_CTK": "1", "GPU": "H100", "DRIVER": "latest" }
@@ -75,20 +34,19 @@
   },
   "windows": {
     "pull-request": [
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "t4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "13.0.2", "LOCAL_CTK": "0", "GPU": "t4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "13.0.2", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.14", "CUDA_VER": "13.0.2", "LOCAL_CTK": "0", "GPU": "t4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.14", "CUDA_VER": "13.0.2", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.14t", "CUDA_VER": "13.0.2", "LOCAL_CTK": "0", "GPU": "t4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.14t", "CUDA_VER": "13.0.2", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" }
+      { "ARCH": "amd64", "PY_VER": "3.10", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "rtx2080", "DRIVER": "latest", "DRIVER_MODE": "WDDM" },
+      { "ARCH": "amd64", "PY_VER": "3.10", "CUDA_VER": "13.0.2", "LOCAL_CTK": "1", "GPU": "rtxpro6000", "DRIVER": "latest", "DRIVER_MODE": "TCC" },
+      { "ARCH": "amd64", "PY_VER": "3.11", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "v100", "DRIVER": "latest", "DRIVER_MODE": "MCDM" },
+      { "ARCH": "amd64", "PY_VER": "3.11", "CUDA_VER": "13.0.2", "LOCAL_CTK": "0", "GPU": "rtx4090", "DRIVER": "latest", "DRIVER_MODE": "WDDM" },
+      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "latest", "DRIVER_MODE": "MCDM" },
+      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "13.0.2", "LOCAL_CTK": "1", "GPU": "a100", "DRIVER": "latest", "DRIVER_MODE": "TCC" },
+      { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest", "DRIVER_MODE": "TCC" },
+      { "ARCH": "amd64", "PY_VER": "3.13", "CUDA_VER": "13.0.2", "LOCAL_CTK": "0", "GPU": "rtxpro6000", "DRIVER": "latest", "DRIVER_MODE": "MCDM" },
+      { "ARCH": "amd64", "PY_VER": "3.14", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "v100", "DRIVER": "latest", "DRIVER_MODE": "TCC" },
+      { "ARCH": "amd64", "PY_VER": "3.14", "CUDA_VER": "13.0.2", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest", "DRIVER_MODE": "MCDM" },
+      { "ARCH": "amd64", "PY_VER": "3.14t", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest", "DRIVER_MODE": "TCC" },
+      { "ARCH": "amd64", "PY_VER": "3.14t", "CUDA_VER": "13.0.2", "LOCAL_CTK": "0", "GPU": "a100", "DRIVER": "latest", "DRIVER_MODE": "MCDM" }
     ],
-    "nightly": [
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "11.8.0", "LOCAL_CTK": "0", "GPU": "l4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "11.8.0", "LOCAL_CTK": "1", "GPU": "t4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "12.9.1", "LOCAL_CTK": "0", "GPU": "t4", "DRIVER": "latest" },
-      { "ARCH": "amd64", "PY_VER": "3.12", "CUDA_VER": "12.9.1", "LOCAL_CTK": "1", "GPU": "l4", "DRIVER": "latest" }
-    ]
+    "nightly": []
   }
 }
diff --git a/ci/tools/install_gpu_driver.ps1 b/ci/tools/install_gpu_driver.ps1
new file mode 100644
index 0000000000..5602eeb489
--- /dev/null
+++ b/ci/tools/install_gpu_driver.ps1
@@ -0,0 +1,82 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+# Install the driver
+function Install-Driver {
+
+    # Set the correct URL, filename, and arguments to the installer
+    # This driver is picked to support Windows 11 & CUDA 13.0
+    $version = '581.15'
+
+    # Get GPU type from environment variable
+    $gpu_type = $env:GPU_TYPE
+
+    $data_center_gpus = @('a100', 'h100', 'l4', 't4', 'v100', 'rtxa6000', 'rtx6000ada')
+    $desktop_gpus = @('rtx2080', 'rtx4090', 'rtxpro6000')
+
+    if ($data_center_gpus -contains $gpu_type) {
+        Write-Output "Data center GPU detected: $gpu_type"
+        $filename="$version-data-center-tesla-desktop-winserver-2022-2025-dch-international.exe"
+        $server_path="tesla/$version"
+    } elseif ($desktop_gpus -contains $gpu_type) {
+        Write-Output "Desktop GPU detected: $gpu_type"
+        $filename="$version-desktop-win10-win11-64bit-international-dch-whql.exe"
+        $server_path="Windows/$version"
+    } else {
+        Write-Output "Unknown GPU type: $gpu_type"
+        exit 1
+    }
+
+    $url="https://us.download.nvidia.com/$server_path/$filename"
+    $filepath="C:\NVIDIA-Driver\$filename"
+
+    Write-Output "Installing NVIDIA driver version $version for GPU type $gpu_type"
+    Write-Output "Download URL: $url"
+
+    # Silent install arguments
+    $install_args = '/s /noeula /noreboot';
+
+    # Create the folder for the driver download
+    if (!(Test-Path -Path 'C:\NVIDIA-Driver')) {
+        New-Item -Path 'C:\' -Name 'NVIDIA-Driver' -ItemType 'directory' | Out-Null
+    }
+
+    # Download the file to a specified directory
+    # Disabling progress bar due to https://github.com/GoogleCloudPlatform/compute-gpu-installation/issues/29
+    $ProgressPreference_tmp = $ProgressPreference
+    $ProgressPreference = 'SilentlyContinue'
+    Write-Output 'Downloading the driver installer...'
+    Invoke-WebRequest $url -OutFile $filepath
+    $ProgressPreference = $ProgressPreference_tmp
+    Write-Output 'Download complete!'
+
+    # Install the file with the specified path from earlier
+    Write-Output 'Running the driver installer...'
+    Start-Process -FilePath $filepath -ArgumentList $install_args -Wait
+    Write-Output 'Done!'
+
+    # Handle driver mode configuration
+    # This assumes we have the prior knowledge on which GPU can use which mode.
+    $driver_mode = $env:DRIVER_MODE
+    if ($driver_mode -eq "WDDM") {
+        Write-Output "Setting driver mode to WDDM..."
+        nvidia-smi -fdm 0
+    } elseif ($driver_mode -eq "TCC") {
+        Write-Output "Setting driver mode to TCC..."
+        nvidia-smi -fdm 1
+    } elseif ($driver_mode -eq "MCDM") {
+        Write-Output "Setting driver mode to MCDM..."
+        nvidia-smi -fdm 2
+    } else {
+        Write-Output "Unknown driver mode: $driver_mode"
+        exit 1
+    }
+    pnputil /disable-device /class Display
+    pnputil /enable-device /class Display
+    # Give it a minute to settle:
+    Start-Sleep -Seconds 5
+}
+
+# Run the functions
+Install-Driver
diff --git a/cuda_bindings/cuda/bindings/_internal/cufile_linux.pyx b/cuda_bindings/cuda/bindings/_internal/cufile_linux.pyx
index 33b6384647..2f4580d791 100644
--- a/cuda_bindings/cuda/bindings/_internal/cufile_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/cufile_linux.pyx
@@ -111,12 +111,15 @@ cdef void* load_library() except* with gil:
     return <void*>handle
 
 
-cdef int __check_or_init_cufile() except -1 nogil:
+cdef int _init_cufile() except -1 nogil:
     global __py_cufile_init
 
     cdef void* handle = NULL
 
     with gil, __symbol_lock:
+        # Recheck the flag after obtaining the locks
+        if __py_cufile_init:
+            return 0
         # Load function
         global __cuFileHandleRegister
         __cuFileHandleRegister = dlsym(RTLD_DEFAULT, 'cuFileHandleRegister')
@@ -427,7 +430,7 @@ cdef inline int _check_or_init_cufile() except -1 nogil:
     if __py_cufile_init:
         return 0
 
-    return __check_or_init_cufile()
+    return _init_cufile()
 
 
 cdef dict func_ptrs = None
diff --git a/cuda_bindings/cuda/bindings/_internal/nvjitlink_linux.pyx b/cuda_bindings/cuda/bindings/_internal/nvjitlink_linux.pyx
index a8e2b4e56b..ccc412b0f8 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvjitlink_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvjitlink_linux.pyx
@@ -80,12 +80,16 @@ cdef void* load_library() except* with gil:
     return <void*>handle
 
 
-cdef int __check_or_init_nvjitlink() except -1 nogil:
+cdef int _init_nvjitlink() except -1 nogil:
     global __py_nvjitlink_init
 
     cdef void* handle = NULL
 
     with gil, __symbol_lock:
+        # Recheck the flag after obtaining the locks
+        if __py_nvjitlink_init:
+            return 0
+
         # Load function
         global __nvJitLinkCreate
         __nvJitLinkCreate = dlsym(RTLD_DEFAULT, 'nvJitLinkCreate')
@@ -193,7 +197,7 @@ cdef inline int _check_or_init_nvjitlink() except -1 nogil:
     if __py_nvjitlink_init:
         return 0
 
-    return __check_or_init_nvjitlink()
+    return _init_nvjitlink()
 
 cdef dict func_ptrs = None
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvjitlink_windows.pyx b/cuda_bindings/cuda/bindings/_internal/nvjitlink_windows.pyx
index 5b26cba4aa..1b88b99892 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvjitlink_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvjitlink_windows.pyx
@@ -93,10 +93,14 @@ cdef void* __nvJitLinkGetInfoLog = NULL
 cdef void* __nvJitLinkVersion = NULL
 
 
-cdef int __check_or_init_nvjitlink() except -1 nogil:
+cdef int _init_nvjitlink() except -1 nogil:
     global __py_nvjitlink_init
 
     with gil, __symbol_lock:
+        # Recheck the flag after obtaining the locks
+        if __py_nvjitlink_init:
+            return 0
+
         # Load library
         handle = load_nvidia_dynamic_lib("nvJitLink")._handle_uint
 
@@ -151,7 +155,7 @@ cdef inline int _check_or_init_nvjitlink() except -1 nogil:
     if __py_nvjitlink_init:
         return 0
 
-    return __check_or_init_nvjitlink()
+    return _init_nvjitlink()
 
 
 cdef dict func_ptrs = None
diff --git a/cuda_bindings/cuda/bindings/_internal/nvvm_linux.pyx b/cuda_bindings/cuda/bindings/_internal/nvvm_linux.pyx
index 64d97334b9..e1addcc9ee 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvvm_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvvm_linux.pyx
@@ -79,12 +79,16 @@ cdef void* load_library() except* with gil:
     return <void*>handle
 
 
-cdef int __check_or_init_nvvm() except -1 nogil:
+cdef int _init_nvvm() except -1 nogil:
     global __py_nvvm_init
 
     cdef void* handle = NULL
 
     with gil, __symbol_lock:
+        # Recheck the flag after obtaining the locks
+        if __py_nvvm_init:
+            return 0
+
         # Load function
         global __nvvmGetErrorString
         __nvvmGetErrorString = dlsym(RTLD_DEFAULT, 'nvvmGetErrorString')
@@ -185,7 +189,7 @@ cdef inline int _check_or_init_nvvm() except -1 nogil:
     if __py_nvvm_init:
         return 0
 
-    return __check_or_init_nvvm()
+    return _init_nvvm()
 
 
 cdef dict func_ptrs = None
diff --git a/cuda_bindings/cuda/bindings/_internal/nvvm_windows.pyx b/cuda_bindings/cuda/bindings/_internal/nvvm_windows.pyx
index a1d7dfbd17..de3e789a41 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvvm_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvvm_windows.pyx
@@ -92,10 +92,14 @@ cdef void* __nvvmGetProgramLogSize = NULL
 cdef void* __nvvmGetProgramLog = NULL
 
 
-cdef int __check_or_init_nvvm() except -1 nogil:
+cdef int _init_nvvm() except -1 nogil:
     global __py_nvvm_init
 
     with gil, __symbol_lock:
+        # Recheck the flag after obtaining the locks
+        if __py_nvvm_init:
+            return 0
+
         # Load library
         handle = load_nvidia_dynamic_lib("nvvm")._handle_uint
 
@@ -147,7 +151,7 @@ cdef inline int _check_or_init_nvvm() except -1 nogil:
     if __py_nvvm_init:
         return 0
 
-    return __check_or_init_nvvm()
+    return _init_nvvm()
 
 
 cdef dict func_ptrs = None
diff --git a/cuda_bindings/cuda/bindings/cufile.pyx b/cuda_bindings/cuda/bindings/cufile.pyx
index f8b3e360a2..a4e5c23994 100644
--- a/cuda_bindings/cuda/bindings/cufile.pyx
+++ b/cuda_bindings/cuda/bindings/cufile.pyx
@@ -12,6 +12,7 @@ import numpy as _numpy
 from cpython cimport buffer as _buffer
 from cpython.memoryview cimport PyMemoryView_FromMemory
 from enum import IntEnum as _IntEnum
+cimport cpython
 
 import cython
 
@@ -54,6 +55,10 @@ cdef class _py_anon_pod1:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         return self._data.ctypes.data
 
@@ -157,6 +162,10 @@ cdef class _py_anon_pod3:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         return self._data.ctypes.data
 
@@ -286,6 +295,10 @@ cdef class IOEvents:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         if self._data.size > 1:
             raise TypeError("int() argument must be a bytes-like object of size 1. "
@@ -422,6 +435,10 @@ cdef class OpCounter:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         return self._data.ctypes.data
 
@@ -551,6 +568,10 @@ cdef class PerGpuStats:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         return self._data.ctypes.data
 
@@ -914,6 +935,10 @@ cdef class Descr:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         if self._data.size > 1:
             raise TypeError("int() argument must be a bytes-like object of size 1. "
@@ -1052,6 +1077,10 @@ cdef class _py_anon_pod2:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         return self._data.ctypes.data
 
@@ -1185,6 +1214,10 @@ cdef class StatsLevel1:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         return self._data.ctypes.data
 
@@ -1667,6 +1700,10 @@ cdef class IOParams:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         if self._data.size > 1:
             raise TypeError("int() argument must be a bytes-like object of size 1. "
@@ -1824,6 +1861,10 @@ cdef class StatsLevel2:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         return self._data.ctypes.data
 
@@ -1935,6 +1976,10 @@ cdef class StatsLevel3:
         """Get the pointer address to the data as Python :class:`int`."""
         return self._data.ctypes.data
 
+    cdef intptr_t _get_ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return self._data.ctypes.data
+
     def __int__(self):
         return self._data.ctypes.data
 
@@ -2458,7 +2503,7 @@ cpdef str get_parameter_string(int param, int len):
     with nogil:
         __status__ = cuFileGetParameterString(<_StringConfigParameter>param, desc_str, len)
     check_status(__status__)
-    return _desc_str_.decode()
+    return cpython.PyUnicode_FromString(desc_str)
 
 
 cpdef set_parameter_size_t(int param, size_t value):
diff --git a/cuda_bindings/pixi.lock b/cuda_bindings/pixi.lock
index ade9615770..161960c7fa 100644
--- a/cuda_bindings/pixi.lock
+++ b/cuda_bindings/pixi.lock
@@ -10,9 +10,9 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.14-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/aom-3.9.1-hac33072_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/attr-2.5.2-h39aace5_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.44-h9d8b0ac_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.45-h9d8b0ac_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_8.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.10.5-hbd8a1cb_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.11.12-hbd8a1cb_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cairo-1.18.4-h3394656_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/conda-gcc-specs-15.2.0-h56430cd_7.conda
@@ -32,7 +32,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.3.2-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-profiler-api-13.0.85-h7938cbb_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-13.0-hc7b4dd1_3.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.0-py314h1807b08_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.1-py314h1807b08_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/dbus-1.16.2-h3c4dab8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.3.0-pyhd8ed1ab_0.conda
@@ -63,7 +63,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/intel-media-driver-25.3.4-hecca717_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-4.18.0-he073ed8_8.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/lame-3.100-h166bdaf_1003.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.44-h1aa0949_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45-h1aa0949_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/lerc-4.0.0-h0aef613_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/level-zero-1.26.0-hb700be7_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libabseil-20250512.1-cxx17_hba17884_0.conda
@@ -71,7 +71,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libasprintf-devel-0.25.1-h3f43e3d_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libass-0.17.4-h96ad9f0_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-38_h4a7cf45_openblas.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcap-2.76-h0b2e76d_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcap-2.77-h3ff7636_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-38_h0358290_openblas.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libcufile-1.15.1.6-hbc026e6_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.25-h17f619e_0.conda
@@ -103,7 +103,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libnl-3.11.0-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libnvjitlink-13.0.88-hecca717_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libogg-1.3.5-hd0c01bc_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.30-pthreads_h94d23a6_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.30-pthreads_h94d23a6_4.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libopenvino-2025.2.0-hb617929_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libopenvino-auto-batch-plugin-2025.2.0-hed573e4_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libopenvino-auto-plugin-2025.2.0-hed573e4_1.conda
@@ -128,9 +128,9 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h8f9b012_7.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-64-15.2.0-h73f6952_107.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-15.2.0-h4852527_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libsystemd0-257.10-h085a93f_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libsystemd0-257.10-hd0affe5_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libtiff-4.7.1-h9d88235_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libudev1-257.10-h085a93f_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libudev1-257.10-hd0affe5_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libunwind-1.8.3-h65a8314_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/liburing-2.12-hb700be7_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libusb-1.0.29-h73b1eb8_0.conda
@@ -156,16 +156,15 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pango-1.56.4-hadf4263_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pcre2-10.46-h1321c63_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/pip-25.3-pyh145f28c_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pixman-0.46.4-h54a6638_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pluggy-1.6.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-hb9d3cd8_1002.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pugixml-1.15-h3f63f65_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/pulseaudio-client-17.0-h9a8bead_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/pulseaudio-client-17.0-h9a6aba3_3.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/py-cpuinfo-9.0.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pyglet-2.1.11-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pygments-2.19.2-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.0.0-pyhcf101f3_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.0.1-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-benchmark-5.2.3-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.0-h32b2ec7_102_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
@@ -175,12 +174,12 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/sdl3-3.2.26-h68140b3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-80.9.0-pyhff2d567_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/shaderc-2025.4-h3e344bc_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/snappy-1.2.2-h03e3b7b_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/snappy-1.2.2-h03e3b7b_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/spirv-tools-2025.4-hb700be7_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/svt-av1-3.1.2-hecca717_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-64-2.28-h4ee821c_8.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/tbb-2022.3.0-h8d10470_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_hd72426e_102.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_ha0e22de_103.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025b-h78e105d_0.conda
@@ -192,16 +191,16 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libice-1.1.2-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libsm-1.2.6-he73a12e_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libx11-1.8.12-h4f16b4b_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.12-hb9d3cd8_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.12-hb03c661_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxcursor-1.2.3-hb9d3cd8_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.5-hb9d3cd8_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.5-hb03c661_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxext-1.3.6-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxfixes-6.0.2-hb03c661_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxrandr-1.5.4-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxrender-0.9.12-hb9d3cd8_0.conda
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+  - pulseaudio 17.0 *_3
   license: LGPL-2.1-or-later
   license_family: LGPL
-  size: 767096
-  timestamp: 1757472924483
+  size: 760306
+  timestamp: 1763148231117
 - conda: https://conda.anaconda.org/conda-forge/noarch/py-cpuinfo-9.0.0-pyhd8ed1ab_1.conda
   sha256: 6d8f03c13d085a569fde931892cded813474acbef2e03381a1a87f420c7da035
   md5: 46830ee16925d5ed250850503b5dc3a8
@@ -5194,9 +5173,9 @@ packages:
   license_family: BSD
   size: 889287
   timestamp: 1750615908735
-- conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.0.0-pyhcf101f3_0.conda
-  sha256: afd413cd919bd3cca1d45062b9822be8935e1f61ce6d6b2642364e8c19e2873d
-  md5: 499e8e2df95ad3d263bee8d41cc3d475
+- conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.0.1-pyhcf101f3_0.conda
+  sha256: 7f25f71e4890fb60a4c4cb4563d10acf2d741804fec51e9b85a6fd97cd686f2f
+  md5: fa7f71faa234947d9c520f89b4bda1a2
   depends:
   - pygments >=2.7.2
   - python >=3.10
@@ -5210,8 +5189,9 @@ packages:
   constrains:
   - pytest-faulthandler >=2
   license: MIT
-  size: 298822
-  timestamp: 1762632428892
+  license_family: MIT
+  size: 299017
+  timestamp: 1763049198670
 - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-benchmark-5.2.3-pyhd8ed1ab_0.conda
   sha256: 2f2229415a6e5387c1faaedf442ea8c07471cb2bf5ad1007b9cfb83ea85ca29a
   md5: 0e7294ed4af8b833fcd2c101d647c3da
@@ -5220,6 +5200,7 @@ packages:
   - pytest >=8.1
   - python >=3.10
   license: BSD-2-Clause
+  license_family: BSD
   size: 43976
   timestamp: 1762716480208
 - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.0-h32b2ec7_102_cp314.conda
@@ -5511,28 +5492,29 @@ packages:
   license_family: Apache
   size: 1473258
   timestamp: 1758917199117
-- conda: https://conda.anaconda.org/conda-forge/linux-64/snappy-1.2.2-h03e3b7b_0.conda
-  sha256: 8b8acbde6814d1643da509e11afeb6bb30eb1e3004cf04a7c9ae43e9b097f063
-  md5: 3d8da0248bdae970b4ade636a104b7f5
+- conda: https://conda.anaconda.org/conda-forge/linux-64/snappy-1.2.2-h03e3b7b_1.conda
+  sha256: 48f3f6a76c34b2cfe80de9ce7f2283ecb55d5ed47367ba91e8bb8104e12b8f11
+  md5: 98b6c9dc80eb87b2519b97bcf7e578dd
   depends:
   - libgcc >=14
+  - __glibc >=2.17,<3.0.a0
   - libstdcxx >=14
   - libgcc >=14
-  - __glibc >=2.17,<3.0.a0
   license: BSD-3-Clause
   license_family: BSD
-  size: 45805
-  timestamp: 1753083455352
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/snappy-1.2.2-he774c54_0.conda
-  sha256: 06648e1c2fd7c5426b2611d4e480768aea934b54fe8034a8f7a6378a40b20695
-  md5: b80bb2997c2139b3659edfca69b72dae
+  size: 45829
+  timestamp: 1762948049098
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/snappy-1.2.2-he774c54_1.conda
+  sha256: a8a79c53852fb07286407907402caa5a96b6e22b518c4f010be40647f9ee3726
+  md5: 3dec912091fb88614afa0af2712c1362
   depends:
+  - libgcc >=14
   - libstdcxx >=14
   - libgcc >=14
   license: BSD-3-Clause
   license_family: BSD
-  size: 47059
-  timestamp: 1753083509250
+  size: 47096
+  timestamp: 1762948094646
 - conda: https://conda.anaconda.org/conda-forge/linux-64/spirv-tools-2025.4-hb700be7_0.conda
   sha256: aa0f0fc41646ef5a825d5725a2d06659df1c1084f15155936319e1909ac9cd16
   md5: aace50912e0f7361d0d223e7f7cfa6e5
@@ -5634,6 +5616,7 @@ packages:
   - libhwloc >=2.12.1,<2.12.2.0a0
   - libstdcxx >=14
   license: Apache-2.0
+  license_family: APACHE
   size: 181262
   timestamp: 1762509955687
 - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tbb-2022.3.0-h0eac15c_1.conda
@@ -5644,6 +5627,7 @@ packages:
   - libhwloc >=2.12.1,<2.12.2.0a0
   - libstdcxx >=14
   license: Apache-2.0
+  license_family: APACHE
   size: 144223
   timestamp: 1762511489745
 - conda: https://conda.anaconda.org/conda-forge/win-64/tbb-2022.3.0-hd094cb3_1.conda
@@ -5655,40 +5639,45 @@ packages:
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
   license: Apache-2.0
+  license_family: APACHE
   size: 155714
   timestamp: 1762510341121
-- conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_hd72426e_102.conda
-  sha256: a84ff687119e6d8752346d1d408d5cf360dee0badd487a472aa8ddedfdc219e1
-  md5: a0116df4f4ed05c303811a837d5b39d8
+- conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_ha0e22de_103.conda
+  sha256: 1544760538a40bcd8ace2b1d8ebe3eb5807ac268641f8acdc18c69c5ebfeaf64
+  md5: 86bc20552bf46075e3d92b67f089172d
   depends:
   - __glibc >=2.17,<3.0.a0
   - libgcc >=13
   - libzlib >=1.3.1,<2.0a0
+  constrains:
+  - xorg-libx11 >=1.8.12,<2.0a0
   license: TCL
   license_family: BSD
-  size: 3285204
-  timestamp: 1748387766691
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tk-8.6.13-noxft_h5688188_102.conda
-  sha256: 46e10488e9254092c655257c18fcec0a9864043bdfbe935a9fbf4fb2028b8514
-  md5: 2562c9bfd1de3f9c590f0fe53858d85c
+  size: 3284905
+  timestamp: 1763054914403
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tk-8.6.13-noxft_h561c983_103.conda
+  sha256: 154e73f6269f92ad5257aa2039278b083998fd19d371e150f307483fb93c07ae
+  md5: 631db4799bc2bfe4daccf80bb3cbc433
   depends:
   - libgcc >=13
   - libzlib >=1.3.1,<2.0a0
+  constrains:
+  - xorg-libx11 >=1.8.12,<2.0a0
   license: TCL
   license_family: BSD
-  size: 3342845
-  timestamp: 1748393219221
-- conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h2c6b04d_2.conda
-  sha256: e3614b0eb4abcc70d98eae159db59d9b4059ed743ef402081151a948dce95896
-  md5: ebd0e761de9aa879a51d22cc721bd095
+  size: 3333495
+  timestamp: 1763059192223
+- conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h2c6b04d_3.conda
+  sha256: 4581f4ffb432fefa1ac4f85c5682cc27014bcd66e7beaa0ee330e927a7858790
+  md5: 7cb36e506a7dba4817970f8adb6396f9
   depends:
   - ucrt >=10.0.20348.0
   - vc >=14.2,<15
   - vc14_runtime >=14.29.30139
   license: TCL
   license_family: BSD
-  size: 3466348
-  timestamp: 1748388121356
+  size: 3472313
+  timestamp: 1763055164278
 - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
   sha256: cb77c660b646c00a48ef942a9e1721ee46e90230c7c570cdeb5a893b5cce9bff
   md5: d2732eb636c264dc9aa4cbee404b1a53
@@ -5941,25 +5930,25 @@ packages:
   license_family: MIT
   size: 864850
   timestamp: 1741901264068
-- conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.12-hb9d3cd8_0.conda
-  sha256: ed10c9283974d311855ae08a16dfd7e56241fac632aec3b92e3cfe73cff31038
-  md5: f6ebe2cb3f82ba6c057dde5d9debe4f7
+- conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.12-hb03c661_1.conda
+  sha256: 6bc6ab7a90a5d8ac94c7e300cc10beb0500eeba4b99822768ca2f2ef356f731b
+  md5: b2895afaf55bf96a8c8282a2e47a5de0
   depends:
   - __glibc >=2.17,<3.0.a0
-  - libgcc >=13
+  - libgcc >=14
   license: MIT
   license_family: MIT
-  size: 14780
-  timestamp: 1734229004433
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/xorg-libxau-1.0.12-h86ecc28_0.conda
-  sha256: 7829a0019b99ba462aece7592d2d7f42e12d12ccd3b9614e529de6ddba453685
-  md5: d5397424399a66d33c80b1f2345a36a6
+  size: 15321
+  timestamp: 1762976464266
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/xorg-libxau-1.0.12-he30d5cf_1.conda
+  sha256: e9f6e931feeb2f40e1fdbafe41d3b665f1ab6cb39c5880a1fcf9f79a3f3c84a5
+  md5: 1c246e1105000c3660558459e2fd6d43
   depends:
-  - libgcc >=13
+  - libgcc >=14
   license: MIT
   license_family: MIT
-  size: 15873
-  timestamp: 1734230458294
+  size: 16317
+  timestamp: 1762977521691
 - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxcursor-1.2.3-hb9d3cd8_0.conda
   sha256: 832f538ade441b1eee863c8c91af9e69b356cd3e9e1350fff4fe36cc573fc91a
   md5: 2ccd714aa2242315acaf0a67faea780b
@@ -5985,25 +5974,25 @@ packages:
   license_family: MIT
   size: 34596
   timestamp: 1730908388714
-- conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.5-hb9d3cd8_0.conda
-  sha256: 6b250f3e59db07c2514057944a3ea2044d6a8cdde8a47b6497c254520fade1ee
-  md5: 8035c64cb77ed555e3f150b7b3972480
+- conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.5-hb03c661_1.conda
+  sha256: 25d255fb2eef929d21ff660a0c687d38a6d2ccfbcbf0cc6aa738b12af6e9d142
+  md5: 1dafce8548e38671bea82e3f5c6ce22f
   depends:
   - __glibc >=2.17,<3.0.a0
-  - libgcc >=13
+  - libgcc >=14
   license: MIT
   license_family: MIT
-  size: 19901
-  timestamp: 1727794976192
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/xorg-libxdmcp-1.1.5-h57736b2_0.conda
-  sha256: efcc150da5926cf244f757b8376d96a4db78bc15b8d90ca9f56ac6e75755971f
-  md5: 25a5a7b797fe6e084e04ffe2db02fc62
+  size: 20591
+  timestamp: 1762976546182
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/xorg-libxdmcp-1.1.5-he30d5cf_1.conda
+  sha256: 128d72f36bcc8d2b4cdbec07507542e437c7d67f677b7d77b71ed9eeac7d6df1
+  md5: bff06dcde4a707339d66d45d96ceb2e2
   depends:
-  - libgcc >=13
+  - libgcc >=14
   license: MIT
   license_family: MIT
-  size: 20615
-  timestamp: 1727796660574
+  size: 21039
+  timestamp: 1762979038025
 - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxext-1.3.6-hb9d3cd8_0.conda
   sha256: da5dc921c017c05f38a38bd75245017463104457b63a1ce633ed41f214159c14
   md5: febbab7d15033c913d53c7a2c102309d
diff --git a/cuda_bindings/pixi.toml b/cuda_bindings/pixi.toml
index 9b05302f75..da4748516c 100644
--- a/cuda_bindings/pixi.toml
+++ b/cuda_bindings/pixi.toml
@@ -12,7 +12,6 @@ python = ["3.10.*", "3.11.*", "3.12.*", "3.13.*", "3.14.*"]
 
 [dependencies]
 cuda-bindings = { path = "." }
-pip = "*"  # installed to the workspace for convenience
 
 [feature.test.dependencies]
 pytest = ">=6.2.4"
@@ -21,9 +20,9 @@ pyglet = ">=2.1.9"
 numpy = "*"
 
 [feature.cython-tests.dependencies]
-cython = "*"             # for tests that exercise APIs from cython
-setuptools = "*"         # for distutils
-gxx = "*"                # to compile the generated code
+cython = ">=3.2,<3.3"     # for tests that exercise APIs from cython
+setuptools = "*" # for distutils
+gxx = "*"        # to compile the generated code
 # These are necessary because running the Cython tests requires compiling
 # *after* the package is built, and the Cython tests depend on CUDA headers
 # transitively (through cuda-bindings)
@@ -62,21 +61,24 @@ cu13 = { features = ["cu13", "test", "cython-tests"], solve-group = "cu13" }
 # TODO: check if these can be extracted from pyproject.toml
 [package]
 name = "cuda-bindings"
-version = "13.0.2"
+version = "13.0.3"
 
 [package.build]
 backend = { name = "pixi-build-python", version = "*" }
 
 [package.build.config]
-env = { CUDA_PYTHON_PARSER_CACHING = "1", CUDA_PYTHON_PARALLEL_LEVEL = "$(nproc)" }
-noarch = false
 compilers = ["c", "cxx"]
 
+[package.build.config.env]
+CUDA_PYTHON_PARSER_CACHING = "1"
+
 [package.build.target.linux-64.config.env]
 CUDA_HOME = "$PREFIX/targets/x86_64-linux"
+CUDA_PYTHON_PARALLEL_LEVEL = "$(nproc)"
 
 [package.build.target.linux-aarch64.config.env]
 CUDA_HOME = "$PREFIX/targets/sbsa-linux"
+CUDA_PYTHON_PARALLEL_LEVEL = "$(nproc)"
 
 [package.build.target.win-64.config.env]
 CUDA_HOME = '%PREFIX%\Library'
@@ -87,22 +89,22 @@ CUDA_HOME = '%PREFIX%\Library'
 
 [package.host-dependencies]
 python = "*"
-pip = "*"
 setuptools = ">=77"
-cython = ">=3.1,<3.2"
+cython = ">=3.2,<3.3"
 pyclibrary = ">=0.1.7"
 cuda-cudart-static = "*"
 cuda-nvrtc-dev = "*"
 cuda-profiler-api = "*"
 cuda-nvvm = "*"
 
+[package.target.linux.host-dependencies]
+libcufile-dev = "*"
+
 [package.target.linux-64.host-dependencies]
 cuda-crt-dev_linux-64 = "*"
-libcufile-dev = "*"
 
 [package.target.linux-aarch64.host-dependencies]
 cuda-crt-dev_linux-aarch64 = "*"
-libcufile-dev = "*"
 
 [package.target.win-64.host-dependencies]
 cuda-crt-dev_win-64 = "*"
@@ -110,7 +112,6 @@ cuda-crt-dev_win-64 = "*"
 [package.run-dependencies]
 python = "*"
 cuda-pathfinder = ">=1.1,<2"
-cuda-bindings = { path = "." }
 libnvjitlink = "*"
 cuda-nvrtc = "*"
 cuda-nvvm = "*"
@@ -121,10 +122,23 @@ libcufile = "*"
 [target.linux.tasks.build-cython-tests]
 cmd = ["$PIXI_PROJECT_ROOT/tests/cython/build_tests.sh"]
 
-[target.linux.tasks.run-cython-tests]
-cmd = ["pytest", "$PIXI_PROJECT_ROOT/tests/cython/"]
-depends-on = [{ task = "build-cython-tests" }]
+[target.win-64.tasks.build-cython-tests]
+cmd = ['%PIXI_PROJECT_ROOT%\tests\cython\build_tests.bat']
 
 [target.linux.tasks.test]
-cmd = ["pytest", "$PIXI_PROJECT_ROOT"]
-depends-on = [{ task = "run-cython-tests" }]
+cmd = [
+    "pytest",
+    "$PIXI_PROJECT_ROOT",
+    "--override-ini",
+    "norecursedirs=examples", # include cython tests (ignore by default config)
+]
+depends-on = [{ task = "build-cython-tests" }]
+
+[target.win-64.tasks.test]
+cmd = [
+    "pytest",
+    "%PIXI_PROJECT_ROOT%",
+    "--override-ini",
+    "norecursedirs=examples", # include cython tests (ignore by default config)
+]
+depends-on = [{ task = "build-cython-tests" }]
diff --git a/cuda_bindings/pyproject.toml b/cuda_bindings/pyproject.toml
index ed44269e57..4878879afb 100644
--- a/cuda_bindings/pyproject.toml
+++ b/cuda_bindings/pyproject.toml
@@ -1,7 +1,7 @@
 # SPDX-FileCopyrightText: Copyright (c) 2023-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: LicenseRef-NVIDIA-SOFTWARE-LICENSE
 [build-system]
-requires = ["setuptools>=77.0.0", "cython>=3.1,<3.2", "pyclibrary>=0.1.7"]
+requires = ["setuptools>=77.0.0", "cython>=3.2,<3.3", "pyclibrary>=0.1.7"]
 build-backend = "setuptools.build_meta"
 
 [project]
@@ -35,7 +35,7 @@ all = [
 
 [dependency-groups]
 test = [
-    "cython>=3.1,<3.2",
+    "cython>=3.2,<3.3",
     "setuptools>=77.0.0",
     "numpy>=1.21.1",
     "pytest>=6.2.4",
diff --git a/cuda_bindings/tests/test_cufile.py b/cuda_bindings/tests/test_cufile.py
index 3716e2bec5..8ac12dfc7c 100644
--- a/cuda_bindings/tests/test_cufile.py
+++ b/cuda_bindings/tests/test_cufile.py
@@ -121,20 +121,6 @@ def isSupportedFilesystem():
 pytestmark = pytest.mark.skipif(not cufileLibraryAvailable(), reason="cuFile library not available on this system")
 
 
-def safe_decode_string(raw_value):
-    """Safely decode a string value from ctypes buffer."""
-    # Find null terminator if present
-    null_pos = raw_value.find(b"\x00")
-    if null_pos != -1:
-        raw_value = raw_value[:null_pos]
-    # Decode with error handling
-    try:
-        return raw_value.decode("utf-8", errors="ignore")
-    except UnicodeDecodeError:
-        # If UTF-8 fails, try to decode as bytes
-        return str(raw_value)
-
-
 def test_cufile_success_defined():
     """Check if CUFILE_SUCCESS is defined in OpError enum."""
     assert hasattr(cufile.OpError, "SUCCESS")
@@ -1774,8 +1760,6 @@ def test_set_get_parameter_string(tmp_path):
 
     def test_param(param, val, default_val):
         orig_val = cufile.get_parameter_string(param, 256)
-        # Use safe_decode_string to handle null terminators and padding
-        orig_val = safe_decode_string(orig_val.encode("utf-8"))
 
         val_b = val.encode("utf-8")
         val_buf = ctypes.create_string_buffer(val_b)
@@ -1787,7 +1771,6 @@ def test_param(param, val, default_val):
         # Round-trip test
         cufile.set_parameter_string(param, int(ctypes.addressof(val_buf)))
         retrieved_val = cufile.get_parameter_string(param, 256)
-        retrieved_val = safe_decode_string(retrieved_val.encode("utf-8"))
         assert retrieved_val == val
 
         # Restore
diff --git a/cuda_core/cuda/core/_version.py b/cuda_core/cuda/core/_version.py
index 0fefe49f48..dc33772c41 100644
--- a/cuda_core/cuda/core/_version.py
+++ b/cuda_core/cuda/core/_version.py
@@ -2,4 +2,4 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-__version__ = "0.4.1"
+__version__ = "0.4.2"
diff --git a/cuda_core/cuda/core/experimental/__init__.py b/cuda_core/cuda/core/experimental/__init__.py
index 8a60c031c5..816b0d570b 100644
--- a/cuda_core/cuda/core/experimental/__init__.py
+++ b/cuda_core/cuda/core/experimental/__init__.py
@@ -3,11 +3,11 @@
 # SPDX-License-Identifier: Apache-2.0
 
 try:
-    import cuda.bindings
+    from cuda import bindings
 except ImportError:
     raise ImportError("cuda.bindings 12.x or 13.x must be installed") from None
 else:
-    cuda_major, cuda_minor = cuda.bindings.__version__.split(".")[:2]
+    cuda_major, cuda_minor = bindings.__version__.split(".")[:2]
     if cuda_major not in ("12", "13"):
         raise ImportError("cuda.bindings 12.x or 13.x must be installed")
 
@@ -24,7 +24,7 @@
 else:
     del versioned_mod
 finally:
-    del cuda.bindings, importlib, subdir, cuda_major, cuda_minor
+    del bindings, importlib, subdir, cuda_major, cuda_minor
 
 from cuda.core.experimental import utils  # noqa: E402
 from cuda.core.experimental._device import Device  # noqa: E402
diff --git a/cuda_core/cuda/core/experimental/_device.pyx b/cuda_core/cuda/core/experimental/_device.pyx
index bc6167793a..6c3c0c6db7 100644
--- a/cuda_core/cuda/core/experimental/_device.pyx
+++ b/cuda_core/cuda/core/experimental/_device.pyx
@@ -948,9 +948,16 @@ class Device:
         Default value of `None` return the currently used device.
 
     """
-    __slots__ = ("_id", "_mr", "_has_inited", "_properties", "_uuid")
+    __slots__ = ("_id", "_memory_resource", "_has_inited", "_properties", "_uuid")
 
-    def __new__(cls, device_id: int | None = None):
+    def __new__(cls, device_id: Device | int | None = None):
+        # Handle device_id argument.
+        if isinstance(device_id, Device):
+            return device_id
+        else:
+            device_id = getattr(device_id, 'device_id', device_id)
+
+        # Initialize CUDA.
         global _is_cuInit
         if _is_cuInit is False:
             with _lock, nogil:
@@ -976,7 +983,7 @@ class Device:
             raise ValueError(f"device_id must be >= 0, got {device_id}")
 
         # ensure Device is singleton
-        cdef int total, attr
+        cdef int total
         try:
             devices = _tls.devices
         except AttributeError:
@@ -986,21 +993,7 @@ class Device:
             for dev_id in range(total):
                 device = super().__new__(cls)
                 device._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.
-                with nogil:
-                    HANDLE_RETURN(
-                        cydriver.cuDeviceGetAttribute(
-                            &attr, cydriver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MEMORY_POOLS_SUPPORTED, dev_id
-                        )
-                    )
-                if attr == 1:
-                    from cuda.core.experimental._memory import DeviceMemoryResource
-                    device._mr = DeviceMemoryResource(dev_id)
-                else:
-                    from cuda.core.experimental._memory import _SynchronousMemoryResource
-                    device._mr = _SynchronousMemoryResource(dev_id)
-
+                device._memory_resource = None
                 device._has_inited = False
                 device._properties = None
                 device._uuid = None
@@ -1128,13 +1121,31 @@ class Device:
     @property
     def memory_resource(self) -> MemoryResource:
         """Return :obj:`~_memory.MemoryResource` associated with this device."""
-        return self._mr
+        cdef int attr, device_id
+        if self._memory_resource is None:
+            # 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.
+            device_id = self._id
+            with nogil:
+                HANDLE_RETURN(
+                    cydriver.cuDeviceGetAttribute(
+                        &attr, cydriver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MEMORY_POOLS_SUPPORTED, device_id
+                    )
+                )
+            if attr == 1:
+                from cuda.core.experimental._memory import DeviceMemoryResource
+                self._memory_resource = DeviceMemoryResource(self._id)
+            else:
+                from cuda.core.experimental._memory import _SynchronousMemoryResource
+                self._memory_resource = _SynchronousMemoryResource(self._id)
+
+        return self._memory_resource
 
     @memory_resource.setter
     def memory_resource(self, mr):
         from cuda.core.experimental._memory import MemoryResource
         assert_type(mr, MemoryResource)
-        self._mr = mr
+        self._memory_resource = mr
 
     @property
     def default_stream(self) -> Stream:
@@ -1324,7 +1335,7 @@ class Device:
         self._check_context_initialized()
         if stream is None:
             stream = default_stream()
-        return self._mr.allocate(size, stream)
+        return self.memory_resource.allocate(size, stream)
 
     def sync(self):
         """Synchronize the device.
diff --git a/cuda_core/cuda/core/experimental/_event.pyx b/cuda_core/cuda/core/experimental/_event.pyx
index 92899f9673..98a45d0043 100644
--- a/cuda_core/cuda/core/experimental/_event.pyx
+++ b/cuda_core/cuda/core/experimental/_event.pyx
@@ -25,7 +25,6 @@ from cuda.core.experimental._utils.cuda_utils import (
 )
 if TYPE_CHECKING:
     import cuda.bindings
-    from cuda.core.experimental._device import Device
 
 
 @dataclass
diff --git a/cuda_core/cuda/core/experimental/_memory/_device_memory_resource.pyx b/cuda_core/cuda/core/experimental/_memory/_device_memory_resource.pyx
index 47b6fd114e..03e9941fb4 100644
--- a/cuda_core/cuda/core/experimental/_memory/_device_memory_resource.pyx
+++ b/cuda_core/cuda/core/experimental/_memory/_device_memory_resource.pyx
@@ -18,9 +18,9 @@ from cuda.core.experimental._utils.cuda_utils cimport (
     HANDLE_RETURN,
 )
 
-import cython
 from dataclasses import dataclass
 from typing import Optional, TYPE_CHECKING
+import cython
 import platform  # no-cython-lint
 import uuid
 import weakref
@@ -131,7 +131,7 @@ cdef class DeviceMemoryResource(MemoryResource):
 
     Parameters
     ----------
-    device_id : int | Device
+    device_id : Device | int
         Device or Device ordinal for which a memory resource is constructed.
 
     options : DeviceMemoryResourceOptions
@@ -211,8 +211,9 @@ cdef class DeviceMemoryResource(MemoryResource):
         self._ipc_data = None
         self._attributes = None
 
-    def __init__(self, device_id: int | Device, options=None):
-        cdef int dev_id = getattr(device_id, 'device_id', device_id)
+    def __init__(self, device_id: Device | int, options=None):
+        from .._device import Device
+        cdef int dev_id = Device(device_id).device_id
         opts = check_or_create_options(
             DeviceMemoryResourceOptions, options, "DeviceMemoryResource options",
             keep_none=True
@@ -261,7 +262,7 @@ cdef class DeviceMemoryResource(MemoryResource):
 
     @classmethod
     def from_allocation_handle(
-        cls, device_id: int | Device, alloc_handle: int | IPCAllocationHandle
+        cls, device_id: Device | int, alloc_handle: int | IPCAllocationHandle
     ) -> DeviceMemoryResource:
         """Create a device memory resource from an allocation handle.
 
diff --git a/cuda_core/cuda/core/experimental/_memory/_ipc.pyx b/cuda_core/cuda/core/experimental/_memory/_ipc.pyx
index 5aa13af8fb..d9384bf2b8 100644
--- a/cuda_core/cuda/core/experimental/_memory/_ipc.pyx
+++ b/cuda_core/cuda/core/experimental/_memory/_ipc.pyx
@@ -197,7 +197,8 @@ cdef DeviceMemoryResource DMR_from_allocation_handle(cls, device_id, alloc_handl
 
     # Construct a new DMR.
     cdef DeviceMemoryResource self = DeviceMemoryResource.__new__(cls)
-    self._dev_id = getattr(device_id, 'device_id', device_id)
+    from .._device import Device
+    self._dev_id = Device(device_id).device_id
     self._mempool_owned = True
     self._ipc_data = IPCData(alloc_handle, mapped=True)
 
diff --git a/cuda_core/cuda/core/experimental/_memory/_legacy.py b/cuda_core/cuda/core/experimental/_memory/_legacy.py
index 523835a79d..9bddf697a4 100644
--- a/cuda_core/cuda/core/experimental/_memory/_legacy.py
+++ b/cuda_core/cuda/core/experimental/_memory/_legacy.py
@@ -86,7 +86,9 @@ class _SynchronousMemoryResource(MemoryResource):
     __slots__ = ("_dev_id",)
 
     def __init__(self, device_id):
-        self._dev_id = getattr(device_id, "device_id", device_id)
+        from .._device import Device
+
+        self._dev_id = Device(device_id).device_id
 
     def allocate(self, size, stream=None) -> Buffer:
         if stream is None:
diff --git a/cuda_core/cuda/core/experimental/_memory/_virtual_memory_resource.py b/cuda_core/cuda/core/experimental/_memory/_virtual_memory_resource.py
index 5379f0b8f1..1ebc9dfd48 100644
--- a/cuda_core/cuda/core/experimental/_memory/_virtual_memory_resource.py
+++ b/cuda_core/cuda/core/experimental/_memory/_virtual_memory_resource.py
@@ -5,6 +5,7 @@
 from dataclasses import dataclass, field
 from typing import Iterable, Literal, Union
 
+from cuda.core.experimental._device import Device
 from cuda.core.experimental._memory._buffer import Buffer, MemoryResource
 from cuda.core.experimental._stream import Stream
 from cuda.core.experimental._utils.cuda_utils import (
@@ -69,6 +70,7 @@ class VirtualMemoryResourceOptions:
     peers: Iterable[int] = field(default_factory=tuple)
     self_access: VirtualMemoryAccessTypeT = "rw"
     peer_access: VirtualMemoryAccessTypeT = "rw"
+    win32_handle_metadata: int | None = 0
 
     _a = driver.CUmemAccess_flags
     _access_flags = {"rw": _a.CU_MEM_ACCESS_FLAGS_PROT_READWRITE, "r": _a.CU_MEM_ACCESS_FLAGS_PROT_READ, None: 0}
@@ -140,15 +142,15 @@ class VirtualMemoryResource(MemoryResource):
 
     Parameters
     ----------
-    device_id : int
-        Device ordinal for which a memory resource is constructed.
+    device_id : Device | int
+        Device for which a memory resource is constructed.
 
     config : VirtualMemoryResourceOptions
         A configuration object for the VirtualMemoryResource
     """
 
-    def __init__(self, device, config: VirtualMemoryResourceOptions = None):
-        self.device = device
+    def __init__(self, device_id: Device | int, config: VirtualMemoryResourceOptions = None):
+        self.device = Device(device_id)
         self.config = check_or_create_options(
             VirtualMemoryResourceOptions, config, "VirtualMemoryResource options", keep_none=False
         )
@@ -211,6 +213,7 @@ def modify_allocation(self, buf: Buffer, new_size: int, config: VirtualMemoryRes
         prop.location.id = self.device.device_id
         prop.allocFlags.gpuDirectRDMACapable = 1 if self.config.gpu_direct_rdma else 0
         prop.requestedHandleTypes = VirtualMemoryResourceOptions._handle_type_to_driver(self.config.handle_type)
+        prop.win32HandleMetaData = self.config.win32_handle_metadata if self.config.win32_handle_metadata else 0
 
         # Query granularity
         gran_flag = VirtualMemoryResourceOptions._granularity_to_driver(self.config.granularity)
@@ -494,11 +497,11 @@ def allocate(self, size: int, stream: Stream = None) -> Buffer:
         # ---- Build allocation properties ----
         prop = driver.CUmemAllocationProp()
         prop.type = VirtualMemoryResourceOptions._allocation_type_to_driver(config.allocation_type)
-
         prop.location.type = VirtualMemoryResourceOptions._location_type_to_driver(config.location_type)
         prop.location.id = self.device.device_id if config.location_type == "device" else -1
         prop.allocFlags.gpuDirectRDMACapable = 1 if config.gpu_direct_rdma else 0
         prop.requestedHandleTypes = VirtualMemoryResourceOptions._handle_type_to_driver(config.handle_type)
+        prop.win32HandleMetaData = self.config.win32_handle_metadata if self.config.win32_handle_metadata else 0
 
         # ---- Query and apply granularity ----
         # Choose min vs recommended granularity per config
diff --git a/cuda_core/cuda/core/experimental/_module.py b/cuda_core/cuda/core/experimental/_module.py
index f8ce8f95d0..9af722465b 100644
--- a/cuda_core/cuda/core/experimental/_module.py
+++ b/cuda_core/cuda/core/experimental/_module.py
@@ -7,6 +7,7 @@
 from typing import Union
 from warnings import warn
 
+from cuda.core.experimental._device import Device
 from cuda.core.experimental._launch_config import LaunchConfig, _to_native_launch_config
 from cuda.core.experimental._stream import Stream
 from cuda.core.experimental._utils.clear_error_support import (
@@ -73,8 +74,9 @@ def _init(cls, kernel):
         self._loader = _backend[self._backend_version]
         return self
 
-    def _get_cached_attribute(self, device_id: int, attribute: driver.CUfunction_attribute) -> int:
+    def _get_cached_attribute(self, device_id: Device | int, attribute: driver.CUfunction_attribute) -> int:
         """Helper function to get a cached attribute or fetch and cache it if not present."""
+        device_id = Device(device_id).device_id
         cache_key = device_id, attribute
         result = self._cache.get(cache_key, cache_key)
         if result is not cache_key:
@@ -94,62 +96,62 @@ def _get_cached_attribute(self, device_id: int, attribute: driver.CUfunction_att
         self._cache[cache_key] = result
         return result
 
-    def max_threads_per_block(self, device_id: int = None) -> int:
+    def max_threads_per_block(self, device_id: Device | int = None) -> int:
         """int : The maximum number of threads per block.
         This attribute is read-only."""
         return self._get_cached_attribute(
             device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK
         )
 
-    def shared_size_bytes(self, device_id: int = None) -> int:
+    def shared_size_bytes(self, device_id: Device | int = None) -> int:
         """int : The size in bytes of statically-allocated shared memory required by this function.
         This attribute is read-only."""
         return self._get_cached_attribute(device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES)
 
-    def const_size_bytes(self, device_id: int = None) -> int:
+    def const_size_bytes(self, device_id: Device | int = None) -> int:
         """int : The size in bytes of user-allocated constant memory required by this function.
         This attribute is read-only."""
         return self._get_cached_attribute(device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_CONST_SIZE_BYTES)
 
-    def local_size_bytes(self, device_id: int = None) -> int:
+    def local_size_bytes(self, device_id: Device | int = None) -> int:
         """int : The size in bytes of local memory used by each thread of this function.
         This attribute is read-only."""
         return self._get_cached_attribute(device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_LOCAL_SIZE_BYTES)
 
-    def num_regs(self, device_id: int = None) -> int:
+    def num_regs(self, device_id: Device | int = None) -> int:
         """int : The number of registers used by each thread of this function.
         This attribute is read-only."""
         return self._get_cached_attribute(device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_NUM_REGS)
 
-    def ptx_version(self, device_id: int = None) -> int:
+    def ptx_version(self, device_id: Device | int = None) -> int:
         """int : The PTX virtual architecture version for which the function was compiled.
         This attribute is read-only."""
         return self._get_cached_attribute(device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_PTX_VERSION)
 
-    def binary_version(self, device_id: int = None) -> int:
+    def binary_version(self, device_id: Device | int = None) -> int:
         """int : The binary architecture version for which the function was compiled.
         This attribute is read-only."""
         return self._get_cached_attribute(device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_BINARY_VERSION)
 
-    def cache_mode_ca(self, device_id: int = None) -> bool:
+    def cache_mode_ca(self, device_id: Device | int = None) -> bool:
         """bool : Whether the function has been compiled with user specified option "-Xptxas --dlcm=ca" set.
         This attribute is read-only."""
         return bool(self._get_cached_attribute(device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_CACHE_MODE_CA))
 
-    def max_dynamic_shared_size_bytes(self, device_id: int = None) -> int:
+    def max_dynamic_shared_size_bytes(self, device_id: Device | int = None) -> int:
         """int : The maximum size in bytes of dynamically-allocated shared memory that can be used
         by this function."""
         return self._get_cached_attribute(
             device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES
         )
 
-    def preferred_shared_memory_carveout(self, device_id: int = None) -> int:
+    def preferred_shared_memory_carveout(self, device_id: Device | int = None) -> int:
         """int : The shared memory carveout preference, in percent of the total shared memory."""
         return self._get_cached_attribute(
             device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT
         )
 
-    def cluster_size_must_be_set(self, device_id: int = None) -> bool:
+    def cluster_size_must_be_set(self, device_id: Device | int = None) -> bool:
         """bool : The kernel must launch with a valid cluster size specified.
         This attribute is read-only."""
         return bool(
@@ -158,25 +160,25 @@ def cluster_size_must_be_set(self, device_id: int = None) -> bool:
             )
         )
 
-    def required_cluster_width(self, device_id: int = None) -> int:
+    def required_cluster_width(self, device_id: Device | int = None) -> int:
         """int : The required cluster width in blocks."""
         return self._get_cached_attribute(
             device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_WIDTH
         )
 
-    def required_cluster_height(self, device_id: int = None) -> int:
+    def required_cluster_height(self, device_id: Device | int = None) -> int:
         """int : The required cluster height in blocks."""
         return self._get_cached_attribute(
             device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_HEIGHT
         )
 
-    def required_cluster_depth(self, device_id: int = None) -> int:
+    def required_cluster_depth(self, device_id: Device | int = None) -> int:
         """int : The required cluster depth in blocks."""
         return self._get_cached_attribute(
             device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_DEPTH
         )
 
-    def non_portable_cluster_size_allowed(self, device_id: int = None) -> bool:
+    def non_portable_cluster_size_allowed(self, device_id: Device | int = None) -> bool:
         """bool : Whether the function can be launched with non-portable cluster size."""
         return bool(
             self._get_cached_attribute(
@@ -184,7 +186,7 @@ def non_portable_cluster_size_allowed(self, device_id: int = None) -> bool:
             )
         )
 
-    def cluster_scheduling_policy_preference(self, device_id: int = None) -> int:
+    def cluster_scheduling_policy_preference(self, device_id: Device | int = None) -> int:
         """int : The block scheduling policy of a function."""
         return self._get_cached_attribute(
             device_id, driver.CUfunction_attribute.CU_FUNC_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE
diff --git a/cuda_core/docs/nv-versions.json b/cuda_core/docs/nv-versions.json
index b9754c06bd..1d6285df3b 100644
--- a/cuda_core/docs/nv-versions.json
+++ b/cuda_core/docs/nv-versions.json
@@ -3,6 +3,10 @@
         "version": "latest",
         "url": "https://nvidia.github.io/cuda-python/cuda-core/latest/"
     },
+    {
+        "version": "0.4.2",
+        "url": "https://nvidia.github.io/cuda-python/cuda-core/0.4.2/"
+    },
     {
         "version": "0.4.1",
         "url": "https://nvidia.github.io/cuda-python/cuda-core/0.4.1/"
diff --git a/cuda_core/docs/source/release/0.4.X-notes.rst b/cuda_core/docs/source/release/0.4.2-notes.rst
similarity index 66%
rename from cuda_core/docs/source/release/0.4.X-notes.rst
rename to cuda_core/docs/source/release/0.4.2-notes.rst
index 621ac250be..04a89cf098 100644
--- a/cuda_core/docs/source/release/0.4.X-notes.rst
+++ b/cuda_core/docs/source/release/0.4.2-notes.rst
@@ -3,27 +3,36 @@
 
 .. currentmodule:: cuda.core.experimental
 
-``cuda.core`` 0.4.X Release Notes
+``cuda.core`` 0.4.2 Release Notes
 =================================
 
 
 Highlights
 ----------
 
+None.
+
 
 Breaking Changes
 ----------------
 
+None.
+
 
 New features
 ------------
 
+None.
+
 
 New examples
 ------------
 
+None.
+
 
 Fixes and enhancements
 ----------------------
 
-- Fixed a segmentation fault when accessing :class:`StridedMemoryView` ``shape`` and ``strides`` members.
+- Fixed references to the ``cuda.bindings`` module mistakenly purged globally.
+- Restored compatibility with ``cuda-python`` 12.6.
diff --git a/cuda_core/pixi.lock b/cuda_core/pixi.lock
index 64074649fa..d442d10902 100644
--- a/cuda_core/pixi.lock
+++ b/cuda_core/pixi.lock
@@ -8,29 +8,33 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/linux-64/attr-2.5.2-h39aace5_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.44-h9d8b0ac_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.45-h9d8b0ac_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_8.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.10.5-hbd8a1cb_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.11.12-hbd8a1cb_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/conda-gcc-specs-14.3.0-hb991d5c_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-bindings-12.9.4-py314h421e08d_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_linux-64-12.9.27-ha770c72_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_linux-64-12.9.86-ha770c72_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-crt-tools-12.9.86-ha770c72_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-12.9.79-h5888daf_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-dev-12.9.79-h5888daf_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-dev_linux-64-12.9.79-h3f2d84a_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-static-12.9.79-h5888daf_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-static_linux-64-12.9.79-h3f2d84a_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-64-12.9.79-h3f2d84a_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvcc-dev_linux-64-12.9.86-he91c749_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvcc-impl-12.9.86-h85509e4_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvcc-tools-12.9.86-he02047a_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-12.9.86-hecca717_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-dev-12.9.86-hecca717_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-12.9.86-h69a702a_4.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvvm-dev_linux-64-12.9.86-ha770c72_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-impl-12.9.86-h4bc722e_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-tools-12.9.86-h4bc722e_2.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.3.2-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-profiler-api-12.9.79-h7938cbb_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-12.9-h4f385c5_3.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.0-py314h1807b08_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.1-py314h1807b08_0.conda
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@@ -2978,11 +3098,11 @@ packages:
   - openblas >=0.3.30,<0.3.31.0a0
   license: BSD-3-Clause
   license_family: BSD
-  size: 5918287
-  timestamp: 1761748180250
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libopenblas-0.3.30-pthreads_h9d3fd7e_3.conda
-  sha256: 30d394f472905a01a0c1a5b1bbca1760d0d6c05f1da6e323d4ada3f631a0bea8
-  md5: 1613b69c1908764ea3243d0cfd69c055
+  size: 5927939
+  timestamp: 1763114673331
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libopenblas-0.3.30-pthreads_h9d3fd7e_4.conda
+  sha256: 794a7270ea049ec931537874cd8d2de0ef4b3cef71c055cfd8b4be6d2f4228b0
+  md5: 11d7d57b7bdd01da745bbf2b67020b2e
   depends:
   - libgcc >=14
   - libgfortran
@@ -2991,8 +3111,8 @@ packages:
   - openblas >=0.3.30,<0.3.31.0a0
   license: BSD-3-Clause
   license_family: BSD
-  size: 4960633
-  timestamp: 1761747757063
+  size: 4959359
+  timestamp: 1763114173544
 - conda: https://conda.anaconda.org/conda-forge/linux-64/libsanitizer-14.3.0-hd08acf3_7.conda
   sha256: 73eb65f58ed086cf73fb9af3be4a9b288f630e9c2e1caacc75aff5f265d2dda2
   md5: 716f4c96e07207d74e635c915b8b3f8b
@@ -3154,44 +3274,44 @@ packages:
   license_family: GPL
   size: 29343
   timestamp: 1759968157195
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libsystemd0-257.10-h085a93f_1.conda
-  sha256: a57cdd2eec34c49fe748412c1f3cf26f54dc9f346cd1f6f691b90d592ae25660
-  md5: fbe2f90c5e1a2c3affbda77807883dca
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libsystemd0-257.10-hd0affe5_2.conda
+  sha256: b30c06f60f03c2cf101afeb3452f48f12a2553b4cb631c9460c8a8ccf0813ae5
+  md5: b04e0a2163a72588a40cde1afd6f2d18
   depends:
   - __glibc >=2.17,<3.0.a0
-  - libcap >=2.76,<2.77.0a0
+  - libcap >=2.77,<2.78.0a0
   - libgcc >=14
   license: LGPL-2.1-or-later
-  size: 491334
-  timestamp: 1762460699434
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsystemd0-257.10-hf39d17c_1.conda
-  sha256: 659efaa1a096413c3066df5a8595b61829e5ed4ada7d1a3b0bd201ca373656b8
-  md5: 048e729e2e881663d7d90bad8fe56a39
+  size: 491211
+  timestamp: 1763011323224
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsystemd0-257.10-hf9559e3_2.conda
+  sha256: 22e5bc2b72eb4a104927d34d06954573dbbdef1981fd7f73520f2ca82f0b7101
+  md5: e7a86e3cdea9c37bf12005778d490148
   depends:
-  - libcap >=2.76,<2.77.0a0
+  - libcap >=2.77,<2.78.0a0
   - libgcc >=14
   license: LGPL-2.1-or-later
-  size: 513934
-  timestamp: 1762460681330
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libudev1-257.10-h085a93f_1.conda
-  sha256: 135f043ced014c8a94b62f111726addc3b14f52525f4e1d6daafd97372c1b772
-  md5: 553d592cb7712ac732f58e781a2dc7b6
+  size: 517490
+  timestamp: 1763011526609
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libudev1-257.10-hd0affe5_2.conda
+  sha256: 751cf346f0f56cc9bfa43f7b5c9c30df2fcec8d84d164ac0cd74a27a3af79f30
+  md5: 2f6b30acaa0d6e231d01166549108e2c
   depends:
   - __glibc >=2.17,<3.0.a0
-  - libcap >=2.76,<2.77.0a0
+  - libcap >=2.77,<2.78.0a0
   - libgcc >=14
   license: LGPL-2.1-or-later
-  size: 145067
-  timestamp: 1762460712193
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libudev1-257.10-hf39d17c_1.conda
-  sha256: 6a32cec220b1a408ddc944b8b476a7928cb7f869d03bd4eb25140a530b47134c
-  md5: af3657abc2fdbcfc1ca56ef46ab31ff8
+  size: 144395
+  timestamp: 1763011330153
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libudev1-257.10-hf9559e3_2.conda
+  sha256: dd1ec27fef9f74ebdd0211ad875ba037f924931c81be164e7ff756b5d86ffc72
+  md5: 4fc935d5bebd8e6e070a861544a71a34
   depends:
-  - libcap >=2.76,<2.77.0a0
+  - libcap >=2.77,<2.78.0a0
   - libgcc >=14
   license: LGPL-2.1-or-later
-  size: 155831
-  timestamp: 1762460690276
+  size: 156835
+  timestamp: 1763011535779
 - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.2-he9a06e4_0.conda
   sha256: e5ec6d2ad7eef538ddcb9ea62ad4346fde70a4736342c4ad87bd713641eb9808
   md5: 80c07c68d2f6870250959dcc95b209d1
@@ -3292,20 +3412,20 @@ packages:
   license_family: Other
   size: 55476
   timestamp: 1727963768015
-- conda: https://conda.anaconda.org/conda-forge/win-64/llvm-openmp-21.1.5-hfa2b4ca_0.conda
-  sha256: 8c5106720e5414f48344fd28eae4db4f1a382336d8a0f30f71d41d8ae730fbb6
-  md5: 3bd3154b24a1b9489d4ab04d62ffcc86
+- conda: https://conda.anaconda.org/conda-forge/win-64/llvm-openmp-21.1.5-h4fa8253_2.conda
+  sha256: 5c2fe1adaad8981c1d97ccea9c13213ccbc215d763bf8fb9c8480a89df9162c0
+  md5: b245791c45b8fdae490f089dda1652c9
   depends:
   - ucrt >=10.0.20348.0
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
   constrains:
-  - openmp 21.1.5|21.1.5.*
   - intel-openmp <0.0a0
+  - openmp 21.1.5|21.1.5.*
   license: Apache-2.0 WITH LLVM-exception
   license_family: APACHE
-  size: 347688
-  timestamp: 1762315988146
+  size: 347291
+  timestamp: 1763095868575
 - conda: https://conda.anaconda.org/conda-forge/win-64/m2-conda-epoch-20250515-0_x86_64.conda
   build_number: 0
   sha256: 51e9214548f177db9c3fe70424e3774c95bf19cd69e0e56e83abe2e393228ba1
@@ -3460,30 +3580,30 @@ packages:
   license_family: BSD
   size: 7526912
   timestamp: 1761161584209
-- conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.5.4-h26f9b46_0.conda
-  sha256: e807f3bad09bdf4075dbb4168619e14b0c0360bacb2e12ef18641a834c8c5549
-  md5: 14edad12b59ccbfa3910d42c72adc2a0
+- conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.0-h26f9b46_0.conda
+  sha256: a47271202f4518a484956968335b2521409c8173e123ab381e775c358c67fe6d
+  md5: 9ee58d5c534af06558933af3c845a780
   depends:
   - __glibc >=2.17,<3.0.a0
   - ca-certificates
   - libgcc >=14
   license: Apache-2.0
   license_family: Apache
-  size: 3119624
-  timestamp: 1759324353651
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/openssl-3.5.4-h8e36d6e_0.conda
-  sha256: a24b318733c98903e2689adc7ef73448e27cbb10806852032c023f0ea4446fc5
-  md5: 9303e8887afe539f78517951ce25cd13
+  size: 3165399
+  timestamp: 1762839186699
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/openssl-3.6.0-h8e36d6e_0.conda
+  sha256: 8dd3b4c31fe176a3e51c5729b2c7f4c836a2ce3bd5c82082dc2a503ba9ee0af3
+  md5: 7624c6e01aecba942e9115e0f5a2af9d
   depends:
   - ca-certificates
   - libgcc >=14
   license: Apache-2.0
   license_family: Apache
-  size: 3644584
-  timestamp: 1759326000128
-- conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.5.4-h725018a_0.conda
-  sha256: 5ddc1e39e2a8b72db2431620ad1124016f3df135f87ebde450d235c212a61994
-  md5: f28ffa510fe055ab518cbd9d6ddfea23
+  size: 3705625
+  timestamp: 1762841024958
+- conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.0-h725018a_0.conda
+  sha256: 6d72d6f766293d4f2aa60c28c244c8efed6946c430814175f959ffe8cab899b3
+  md5: 84f8fb4afd1157f59098f618cd2437e4
   depends:
   - ca-certificates
   - ucrt >=10.0.20348.0
@@ -3491,8 +3611,8 @@ packages:
   - vc14_runtime >=14.44.35208
   license: Apache-2.0
   license_family: Apache
-  size: 9218823
-  timestamp: 1759326176247
+  size: 9440812
+  timestamp: 1762841722179
 - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
   sha256: 289861ed0c13a15d7bbb408796af4de72c2fe67e2bcb0de98f4c3fce259d7991
   md5: 58335b26c38bf4a20f399384c33cbcf9
@@ -3503,15 +3623,6 @@ packages:
   license_family: APACHE
   size: 62477
   timestamp: 1745345660407
-- conda: https://conda.anaconda.org/conda-forge/noarch/pip-25.3-pyh145f28c_0.conda
-  sha256: 4d5e2faca810459724f11f78d19a0feee27a7be2b3fc5f7abbbec4c9fdcae93d
-  md5: bf47878473e5ab9fdb4115735230e191
-  depends:
-  - python >=3.13.0a0
-  license: MIT
-  license_family: MIT
-  size: 1177084
-  timestamp: 1762776338614
 - conda: https://conda.anaconda.org/conda-forge/noarch/pluggy-1.6.0-pyhd8ed1ab_0.conda
   sha256: a8eb555eef5063bbb7ba06a379fa7ea714f57d9741fe0efdb9442dbbc2cccbcc
   md5: 7da7ccd349dbf6487a7778579d2bb971
@@ -3539,9 +3650,9 @@ packages:
   license_family: BSD
   size: 889287
   timestamp: 1750615908735
-- conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.0.0-pyhcf101f3_0.conda
-  sha256: afd413cd919bd3cca1d45062b9822be8935e1f61ce6d6b2642364e8c19e2873d
-  md5: 499e8e2df95ad3d263bee8d41cc3d475
+- conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.0.1-pyhcf101f3_0.conda
+  sha256: 7f25f71e4890fb60a4c4cb4563d10acf2d741804fec51e9b85a6fd97cd686f2f
+  md5: fa7f71faa234947d9c520f89b4bda1a2
   depends:
   - pygments >=2.7.2
   - python >=3.10
@@ -3555,8 +3666,9 @@ packages:
   constrains:
   - pytest-faulthandler >=2
   license: MIT
-  size: 298822
-  timestamp: 1762632428892
+  license_family: MIT
+  size: 299017
+  timestamp: 1763049198670
 - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-benchmark-5.2.3-pyhd8ed1ab_0.conda
   sha256: 2f2229415a6e5387c1faaedf442ea8c07471cb2bf5ad1007b9cfb83ea85ca29a
   md5: 0e7294ed4af8b833fcd2c101d647c3da
@@ -3565,6 +3677,7 @@ packages:
   - pytest >=8.1
   - python >=3.10
   license: BSD-2-Clause
+  license_family: BSD
   size: 43976
   timestamp: 1762716480208
 - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.0-h32b2ec7_102_cp314.conda
@@ -3741,40 +3854,45 @@ packages:
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
   license: Apache-2.0
+  license_family: APACHE
   size: 155714
   timestamp: 1762510341121
-- conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_hd72426e_102.conda
-  sha256: a84ff687119e6d8752346d1d408d5cf360dee0badd487a472aa8ddedfdc219e1
-  md5: a0116df4f4ed05c303811a837d5b39d8
+- conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_ha0e22de_103.conda
+  sha256: 1544760538a40bcd8ace2b1d8ebe3eb5807ac268641f8acdc18c69c5ebfeaf64
+  md5: 86bc20552bf46075e3d92b67f089172d
   depends:
   - __glibc >=2.17,<3.0.a0
   - libgcc >=13
   - libzlib >=1.3.1,<2.0a0
+  constrains:
+  - xorg-libx11 >=1.8.12,<2.0a0
   license: TCL
   license_family: BSD
-  size: 3285204
-  timestamp: 1748387766691
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tk-8.6.13-noxft_h5688188_102.conda
-  sha256: 46e10488e9254092c655257c18fcec0a9864043bdfbe935a9fbf4fb2028b8514
-  md5: 2562c9bfd1de3f9c590f0fe53858d85c
+  size: 3284905
+  timestamp: 1763054914403
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tk-8.6.13-noxft_h561c983_103.conda
+  sha256: 154e73f6269f92ad5257aa2039278b083998fd19d371e150f307483fb93c07ae
+  md5: 631db4799bc2bfe4daccf80bb3cbc433
   depends:
   - libgcc >=13
   - libzlib >=1.3.1,<2.0a0
+  constrains:
+  - xorg-libx11 >=1.8.12,<2.0a0
   license: TCL
   license_family: BSD
-  size: 3342845
-  timestamp: 1748393219221
-- conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h2c6b04d_2.conda
-  sha256: e3614b0eb4abcc70d98eae159db59d9b4059ed743ef402081151a948dce95896
-  md5: ebd0e761de9aa879a51d22cc721bd095
+  size: 3333495
+  timestamp: 1763059192223
+- conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h2c6b04d_3.conda
+  sha256: 4581f4ffb432fefa1ac4f85c5682cc27014bcd66e7beaa0ee330e927a7858790
+  md5: 7cb36e506a7dba4817970f8adb6396f9
   depends:
   - ucrt >=10.0.20348.0
   - vc >=14.2,<15
   - vc14_runtime >=14.29.30139
   license: TCL
   license_family: BSD
-  size: 3466348
-  timestamp: 1748388121356
+  size: 3472313
+  timestamp: 1763055164278
 - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
   sha256: cb77c660b646c00a48ef942a9e1721ee46e90230c7c570cdeb5a893b5cce9bff
   md5: d2732eb636c264dc9aa4cbee404b1a53
diff --git a/cuda_core/pixi.toml b/cuda_core/pixi.toml
index c2a1aa6363..e60e6be644 100644
--- a/cuda_core/pixi.toml
+++ b/cuda_core/pixi.toml
@@ -12,16 +12,15 @@ python = ["3.10.*", "3.11.*", "3.12.*", "3.13.*", "3.14.*"]
 
 [dependencies]
 cuda-core = { path = "." }
-pip = "*"  # installed to the workspace for convenience
 
 [feature.test.dependencies]
 pytest = "*"
 pytest-benchmark = "*"
 
 [feature.cython-tests.dependencies]
-cython = "*"             # for tests that exercise APIs from cython
-setuptools = "*"         # for distutils
-gxx = "*"                # to compile the generated code
+cython = ">=3.2,<3.3"     # for tests that exercise APIs from cython
+setuptools = "*" # for distutils
+gxx = "*"        # to compile the generated code
 # These are necessary because running the Cython tests requires compiling
 # *after* the package is built, and the Cython tests depend on CUDA headers
 # transitively (through cuda-bindings)
@@ -74,15 +73,15 @@ version = "0.4.1"
 backend = { name = "pixi-build-python", version = "*" }
 
 [package.build.config]
-env = { CUDA_PYTHON_PARALLEL_LEVEL = "$(nproc)" }
-noarch = false
 compilers = ["c", "cxx"]
 
 [package.build.target.linux-64.config.env]
 CUDA_HOME = "$PREFIX/targets/x86_64-linux"
+CUDA_PYTHON_PARALLEL_LEVEL = "$(nproc)"
 
 [package.build.target.linux-aarch64.config.env]
 CUDA_HOME = "$PREFIX/targets/sbsa-linux"
+CUDA_PYTHON_PARALLEL_LEVEL = "$(nproc)"
 
 [package.build.target.win-64.config.env]
 CUDA_HOME = '%PREFIX%\Library'
@@ -93,12 +92,14 @@ CUDA_HOME = '%PREFIX%\Library'
 
 [package.host-dependencies]
 python = "*"
-pip = "*"
 setuptools = ">=77"
-cython = ">=3.1"
+cython = ">=3.2,<3.3"
 cuda-cudart-dev = "*"
 cuda-profiler-api = "*"
-cuda-bindings = { path = "../cuda_bindings" }
+# this doesn't work because Cython cannot find editable-installed build-time
+# dependencies https://github.com/cython/cython/issues/7326
+# cuda-bindings = { path = "../cuda_bindings" }
+cuda-bindings = "*"
 
 [package.target.linux-64.host-dependencies]
 cuda-crt-dev_linux-64 = "*"
@@ -112,16 +113,33 @@ cuda-crt-dev_win-64 = "*"
 [package.run-dependencies]
 python = "*"
 numpy = "*"
-cuda-bindings = { path = "../cuda_bindings" }
+# this doesn't work because Cython cannot find editable-installed build-time
+# dependencies https://github.com/cython/cython/issues/7326
+# cuda-bindings = { path = "../cuda_bindings" }
+cuda-bindings = "*"
 
 [target.linux.tasks.build-cython-tests]
 cmd = ["$PIXI_PROJECT_ROOT/tests/cython/build_tests.sh"]
 
-[target.linux.tasks.run-cython-tests]
-cmd = ["pytest", "$PIXI_PROJECT_ROOT/tests/cython/"]
-depends-on = [{ task = "build-cython-tests" }]
+[target.win-64.tasks.build-cython-tests]
+cmd = ['%PIXI_PROJECT_ROOT%\tests\cython\build_tests.bat']
 
 [target.linux.tasks.test]
-cmd = ["pytest", "$PIXI_PROJECT_ROOT/tests"]
-#env = { PYTHONPATH = "$PIXI_PROJECT_ROOT/../cuda_python_test_helpers" }
-depends-on = [{ task = "run-cython-tests" }]
+cmd = [
+    "pytest",
+    "$PIXI_PROJECT_ROOT",
+    "--override-ini",
+    "norecursedirs=\"\"", # include cython tests (ignore by default config)
+]
+env = { PYTHONPATH = "$PIXI_PROJECT_ROOT/../cuda_python_test_helpers" }
+depends-on = [{ task = "build-cython-tests" }]
+
+[target.win-64.tasks.test]
+cmd = [
+    "pytest",
+    "%PIXI_PROJECT_ROOT%",
+    "--override-ini",
+    "norecursedirs=\"\"",  # include cython tests (ignore by default config)
+]
+env = { PYTHONPATH = '%PIXI_PROJECT_ROOT%\..\cuda_python_test_helpers' }
+depends-on = [{ task = "build-cython-tests" }]
diff --git a/cuda_core/pyproject.toml b/cuda_core/pyproject.toml
index 31ceb5b1a5..a920005f21 100644
--- a/cuda_core/pyproject.toml
+++ b/cuda_core/pyproject.toml
@@ -3,7 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 [build-system]
-requires = ["setuptools>=77.0.0", "Cython>=3.1"]
+requires = ["setuptools>=77.0.0", "Cython>=3.2,<3.3"]
 build-backend = "build_hooks"
 backend-path = ["."]
 
@@ -51,11 +51,12 @@ cu12 = ["cuda-bindings[all]==12.*"]
 cu13 = ["cuda-bindings[all]==13.*"]
 
 [dependency-groups]
-test = ["cython>=3.1", "setuptools", "pytest>=6.2.4"]
+test = ["cython>=3.2,<3.3", "setuptools", "pytest>=6.2.4"]
 test-cu12 = ["cuda-core[test]", "cupy-cuda12x; python_version < '3.14'", "cuda-toolkit[cudart]==12.*"]  # runtime headers needed by CuPy
 test-cu13 = ["cuda-core[test]", "cupy-cuda13x; python_version < '3.14'", "cuda-toolkit[cudart]==13.*"]  # runtime headers needed by CuPy
 # free threaded build, cupy doesn't support free-threaded builds yet, so avoid installing it for now
 # TODO: cupy should support free threaded builds
+test-cu12-ft = ["cuda-core[test]", "cuda-toolkit[cudart]==12.*"]
 test-cu13-ft = ["cuda-core[test]", "cuda-toolkit[cudart]==13.*"]
 
 [project.urls]
diff --git a/cuda_core/tests/pytest.ini b/cuda_core/pytest.ini
similarity index 100%
rename from cuda_core/tests/pytest.ini
rename to cuda_core/pytest.ini
diff --git a/cuda_core/tests/test_memory.py b/cuda_core/tests/test_memory.py
index a261ec7a3d..21dee23280 100644
--- a/cuda_core/tests/test_memory.py
+++ b/cuda_core/tests/test_memory.py
@@ -1,7 +1,9 @@
 # SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
+import ctypes
 import sys
+from ctypes import wintypes
 
 try:
     from cuda.bindings import driver
@@ -11,7 +13,6 @@
     import numpy as np
 except ImportError:
     np = None
-import ctypes
 import platform
 
 import pytest
@@ -28,6 +29,7 @@
 from cuda.core.experimental._memory import IPCBufferDescriptor
 from cuda.core.experimental._utils.cuda_utils import handle_return
 from cuda.core.experimental.utils import StridedMemoryView
+from helpers import IS_WINDOWS
 from helpers.buffers import DummyUnifiedMemoryResource
 
 from cuda_python_test_helpers import supports_ipc_mempool
@@ -312,7 +314,31 @@ def test_device_memory_resource_initialization(mempool_device, use_device_object
     buffer.close()
 
 
-def test_vmm_allocator_basic_allocation():
+def get_handle_type():
+    def get_sa():
+        class SECURITY_ATTRIBUTES(ctypes.Structure):
+            _fields_ = [
+                ("nLength", wintypes.DWORD),
+                ("lpSecurityDescriptor", wintypes.LPVOID),
+                ("bInheritHandle", wintypes.BOOL),
+            ]
+
+        sa = SECURITY_ATTRIBUTES()
+        sa.nLength = ctypes.sizeof(sa)
+        sa.lpSecurityDescriptor = None
+        sa.bInheritHandle = False  # TODO: why?
+
+        return sa
+
+    if IS_WINDOWS:
+        return (("win32", get_sa()), ("win32_kmt", None))
+    else:
+        return (("posix_fd", None),)
+
+
+@pytest.mark.parametrize("use_device_object", [True, False])
+@pytest.mark.parametrize("handle_type", get_handle_type())
+def test_vmm_allocator_basic_allocation(use_device_object, handle_type):
     """Test basic VMM allocation functionality.
 
     This test verifies that VirtualMemoryResource can allocate memory
@@ -325,9 +351,15 @@ def test_vmm_allocator_basic_allocation():
     if not device.properties.virtual_memory_management_supported:
         pytest.skip("Virtual memory management is not supported on this device")
 
-    options = VirtualMemoryResourceOptions()
+    handle_type, security_attribute = handle_type  # unpack
+    win32_handle_metadata = ctypes.addressof(security_attribute) if security_attribute else 0
+    options = VirtualMemoryResourceOptions(
+        handle_type=handle_type,
+        win32_handle_metadata=win32_handle_metadata,
+    )
     # Create VMM allocator with default config
-    vmm_mr = VirtualMemoryResource(device, config=options)
+    device_arg = device if use_device_object else device.device_id
+    vmm_mr = VirtualMemoryResource(device_arg, config=options)
 
     # Test basic allocation
     buffer = vmm_mr.allocate(4096)
@@ -374,7 +406,7 @@ def test_vmm_allocator_policy_configuration():
         location_type="device",
         granularity="minimum",
         gpu_direct_rdma=True,
-        handle_type="posix_fd" if platform.system() != "Windows" else "win32",
+        handle_type="posix_fd" if not IS_WINDOWS else "win32_kmt",
         peers=(),
         self_access="rw",
         peer_access="rw",
@@ -398,7 +430,7 @@ def test_vmm_allocator_policy_configuration():
         location_type="device",
         granularity="recommended",
         gpu_direct_rdma=False,
-        handle_type="posix_fd",
+        handle_type="posix_fd" if not IS_WINDOWS else "win32_kmt",
         peers=(),
         self_access="r",  # Read-only access
         peer_access="r",
@@ -414,7 +446,8 @@ def test_vmm_allocator_policy_configuration():
     modified_buffer.close()
 
 
-def test_vmm_allocator_grow_allocation():
+@pytest.mark.parametrize("handle_type", get_handle_type())
+def test_vmm_allocator_grow_allocation(handle_type):
     """Test VMM allocator's ability to grow existing allocations.
 
     This test verifies that VirtualMemoryResource can grow existing
@@ -427,7 +460,12 @@ def test_vmm_allocator_grow_allocation():
     if not device.properties.virtual_memory_management_supported:
         pytest.skip("Virtual memory management is not supported on this device")
 
-    options = VirtualMemoryResourceOptions()
+    handle_type, security_attribute = handle_type  # unpack
+    win32_handle_metadata = ctypes.addressof(security_attribute) if security_attribute else 0
+    options = VirtualMemoryResourceOptions(
+        handle_type=handle_type,
+        win32_handle_metadata=win32_handle_metadata,
+    )
 
     vmm_mr = VirtualMemoryResource(device, config=options)
 
diff --git a/cuda_core/tests/test_module.py b/cuda_core/tests/test_module.py
index 49df966c08..901a57f7a4 100644
--- a/cuda_core/tests/test_module.py
+++ b/cuda_core/tests/test_module.py
@@ -134,8 +134,9 @@ def test_read_only_kernel_attributes(get_saxpy_kernel_cubin, attr, expected_type
     value = method()
     assert value is not None
 
-    # get the value for each device on the system
+    # get the value for each device on the system, using either the device object or ordinal
     for device in system.devices:
+        value = method(device)
         value = method(device.device_id)
     assert isinstance(value, expected_type), f"Expected {attr} to be of type {expected_type}, but got {type(value)}"
 
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_nvidia_dynamic_lib.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_nvidia_dynamic_lib.py
index fe553a4344..3431c2f86b 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_nvidia_dynamic_lib.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_nvidia_dynamic_lib.py
@@ -25,8 +25,6 @@
 
 def _load_lib_no_cache(libname: str) -> LoadedDL:
     finder = _FindNvidiaDynamicLib(libname)
-    abs_path = finder.try_site_packages()
-
     abs_path = finder.try_site_packages()
     if abs_path is not None:
         found_via = "site-packages"