diff --git a/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py b/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py
new file mode 100644
index 0000000000..8290e491c6
--- /dev/null
+++ b/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py
@@ -0,0 +1,241 @@
+# Copyright 2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-License-Identifier: LicenseRef-NVIDIA-SOFTWARE-LICENSE
+
+
+# ################################################################################
+#
+# This example demonstrates the core cuda.bindings.nvml functionality by
+# implementing a subset of the NVIDIA System Management Interface (nvidia-smi)
+# command line tool in Python.
+#
+# ################################################################################
+
+
+import sys
+
+from cuda.bindings import nvml
+
+##################################################################################
+# FORMATTING HELPERS
+
+# Utilities to help format the output table. See below for NVML usage.
+
+
+def format_size(bytes_val: int) -> str:
+    """Formats bytes to MiB."""
+    return f"{bytes_val / (1024 * 1024):.0f}MiB"
+
+
+LINES = [[[4, 27, 6], [18, 3], [20]], [[4, 6, 13, 13], [22], [9, 10]]]
+
+
+class TableFormatter:
+    def __init__(self, lines):
+        self.formats, self.sizes, self.counts = zip(*[self._create_line_format(line) for line in lines])
+
+    def _create_line_format(self, descriptor):
+        parts = []
+        sizes = []
+        for section in descriptor:
+            parts.append("| ")
+            sizes.append(1)
+            for i, align in enumerate(section):
+                if i == len(section) - 1:
+                    direct = ">"
+                else:
+                    direct = "<"
+                parts.append(f"{{:{direct}{align}}} ")
+                sizes[-1] += align + 1
+        parts.append("|")
+        return "".join(parts), sizes, sum(len(x) for x in descriptor)
+
+    def print_line(self, char="-"):
+        parts = ["+"]
+        for size in self.sizes[0]:
+            parts.append(char * size)
+            parts.append("+")
+        print("".join(parts))
+
+    def print_values(self, *args):
+        for line_format, count in zip(self.formats, self.counts):
+            print(line_format.format(*args[:count]))
+            args = args[count:]
+
+
+def print_table(metadata, devices):
+    formatter = TableFormatter(LINES)
+
+    print("+-----------------------------------------------------------------------------------------+")
+    print(
+        f"| NVIDIA-MINI-SMI {metadata['driver_version']:<16} Driver Version: {metadata['driver_version']:<15} CUDA Version: {metadata['cuda_version']:<9}|"
+    )
+    formatter.print_line()
+    print("| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |")
+    print("| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |")
+    formatter.print_line("=")
+
+    for device in devices:
+        formatter.print_values(
+            str(device["index"]),
+            device["name"],
+            device["persistence"],
+            device["bus_id"],
+            device["display_active"],
+            device["ecc_mode"],
+            device["fan_speed"],
+            device["temperature"],
+            device["performance_state"],
+            device["power"],
+            device["memory"],
+            device["utilization"],
+            device["compute_mode"],
+        )
+        formatter.print_line()
+
+
+##################################################################################
+# NVML USAGE EXAMPLES
+
+
+def collect_info():
+    metadata = {}
+    metadata["driver_version"] = nvml.system_get_driver_version()
+    cuda_version_int = nvml.system_get_cuda_driver_version()
+    cuda_major = cuda_version_int // 1000
+    cuda_minor = (cuda_version_int % 1000) // 10
+    metadata["cuda_version"] = f"{cuda_major}.{cuda_minor}"
+
+    devices = []
+
+    device_count = nvml.device_get_count_v2()
+
+    for i in range(device_count):
+        device = {}
+        device["index"] = i
+
+        handle = nvml.device_get_handle_by_index_v2(i)
+
+        name = nvml.device_get_name(handle)
+        device["name"] = name
+
+        try:
+            persistence = nvml.device_get_persistence_mode(handle)
+            persistence_str = "On" if persistence == nvml.EnableState.FEATURE_ENABLED else "Off"
+        except nvml.NvmlError:
+            persistence_str = "N/A"
+        device["persistence"] = persistence_str
+
+        try:
+            pci_info = nvml.device_get_pci_info_v3(handle)
+            bus_id = pci_info.bus_id
+        except nvml.NvmlError:
+            bus_id = "N/A"
+        device["bus_id"] = bus_id
+
+        try:
+            display_active = nvml.device_get_display_active(handle)
+            disp_str = "On" if display_active == nvml.EnableState.FEATURE_ENABLED else "Off"
+        except nvml.NvmlError:
+            disp_str = "N/A"
+        device["display_active"] = disp_str
+
+        try:
+            current, _ = nvml.device_get_ecc_mode(handle)
+            ecc_str = "On" if current == nvml.EnableState.FEATURE_ENABLED else "Off"
+        except nvml.NvmlError:
+            ecc_str = "N/A"
+        device["ecc_mode"] = ecc_str
+
+        try:
+            fan = nvml.device_get_fan_speed(handle)
+            fan_str = f"{fan: >3}%"
+        except nvml.NvmlError:
+            fan_str = "N/A"
+        device["fan_speed"] = fan_str
+
+        try:
+            temp = nvml.device_get_temperature_v(handle, nvml.TemperatureSensors.TEMPERATURE_GPU)
+            temp_str = f"{temp}C"
+        except nvml.NvmlError:
+            temp_str = "N/A"
+        device["temperature"] = temp_str
+
+        try:
+            perf_state = nvml.device_get_performance_state(handle)
+            perf_str = f"P{perf_state}"
+        except nvml.NvmlError:
+            perf_str = "N/A"
+        device["performance_state"] = perf_str
+
+        try:
+            power_usage = nvml.device_get_power_usage(handle)  # mW
+            usage_str = f"{power_usage // 1000}W"
+        except nvml.NvmlError:
+            usage_str = "N/A"
+
+        try:
+            power_cap = nvml.device_get_power_management_limit(handle)  # mW
+            cap_str = f"{power_cap // 1000}W"
+        except nvml.NvmlError:
+            cap_str = "N/A"
+
+        pwr_str = f"{usage_str} / {cap_str}"
+        device["power"] = pwr_str
+
+        try:
+            mem_info = nvml.device_get_memory_info_v2(handle)
+        except nvml.NvmlError:
+            mem_str = "N/A"
+        else:
+            mem_used = format_size(mem_info.used)
+            mem_total = format_size(mem_info.total)
+            mem_str = f"{mem_used} / {mem_total}"
+
+        device["memory"] = mem_str
+
+        try:
+            util_rates = nvml.device_get_utilization_rates(handle)
+        except nvml.NvmlError:
+            util_str = "N/A"
+        else:
+            gpu_util = util_rates.gpu
+            util_str = f"{gpu_util: >3}%"
+
+        device["utilization"] = util_str
+
+        try:
+            compute_mode = nvml.device_get_compute_mode(handle)
+        except nvml.NvmlError:
+            comp_str = "N/A"
+        else:
+            if compute_mode == nvml.ComputeMode.COMPUTEMODE_DEFAULT:
+                comp_str = "Default"
+            elif compute_mode == nvml.ComputeMode.COMPUTEMODE_EXCLUSIVE_PROCESS:
+                comp_str = "E. Process"
+            elif compute_mode == nvml.ComputeMode.COMPUTEMODE_PROHIBITED:
+                comp_str = "Prohibited"
+            else:
+                comp_str = "Unknown"
+        device["compute_mode"] = comp_str
+
+        devices.append(device)
+
+    return metadata, devices
+
+
+def main():
+    try:
+        nvml.init_v2()
+    except nvml.NvmlError as e:
+        print(f"Failed to initialize NVML: {e}")
+        sys.exit(1)
+
+    try:
+        metadata, devices = collect_info()
+        print_table(metadata, devices)
+    finally:
+        nvml.shutdown()
+
+
+if __name__ == "__main__":
+    main()