---
id: nvidia-ml-py3
version: "7.352.0"
license: BSD
license_treatment: permissive
maintenance: abandoned
---

# nvidia-ml-py3 — Python Bindings for the NVIDIA Management Library

License: permissive · Maintenance: abandoned · Downloads: 481.4K/mo

## What it is and what it does

nvidia-ml-py3 is a ctypes-based wrapper around NVIDIA's Management Library that exposes GPU monitoring and management functions to Python. It allows you to query device properties, memory usage, driver versions, and other GPU state without calling external commands. The package converts NVML C structs and function signatures into Python classes and methods, handling string buffers and error codes automatically.

The package has been unmaintained since 2017-06-03 and carries no runtime dependencies—it relies entirely on the system's NVML C library being present. While it is marked Production/Stable and carries a permissive BSD license, its age and lack of maintenance mean it may not work reliably with modern Python versions, recent NVIDIA drivers, or current NVML library versions without manual fixes.

Use it for:

- Monitor GPU memory usage and availability on systems running NVIDIA GPUs for resource allocation decisions.
- Query driver version and GPU device names at startup to validate hardware configuration in GPU-accelerated applications.
- Build system administration tools that report GPU health and utilization without spawning external processes.
- Detect the number and type of available GPUs to automatically configure multi-GPU workloads.
- Log GPU state changes during long-running compute jobs for debugging and performance analysis.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides Python bindings to NVIDIA's Management Library (NVML) for querying and monitoring GPU devices, including memory usage, driver version, and device information.

No. The package is abandoned (last release 2017-06-03) with no maintenance signal. While it has no known vulnerabilities and carries a permissive license, the high install friction combined with zero maintenance makes it a poor choice for new projects. Consider maintained alternatives or direct NVML bindings if you need GPU monitoring on modern systems.

## Install

pip install nvidia-ml-py3
uv add nvidia-ml-py3
poetry add nvidia-ml-py3

## Installing nvidia-ml-py3

Before you install: High install friction: the package has been abandoned since its last release on 2017-06-03 with no maintenance activity. Installation requires the NVML C library to be present on the system, and the package itself carries no runtime dependencies to help bridge that gap.

License in practice: BSD license (permissive) places no restrictions on use, modification, or redistribution in proprietary or open-source contexts.

Quickstart:

pip install nvidia-ml-py3

from nvidia_ml_py3 import *
nvmlInit()
deviceCount = nvmlDeviceGetCount()
for i in range(deviceCount):
    handle = nvmlDeviceGetHandleByIndex(i)
    info = nvmlDeviceGetMemoryInfo(handle)
    print(f"Device {i} free memory: {info.free}")
nvmlShutdown()

Requires the NVIDIA Management Library (NVML) C library to be installed on the system; NVIDIA GPU drivers must be present and properly configured.

Verify before relying:

- Whether the package actually works with modern Python versions despite being abandoned since 2017-06-03.
- Current compatibility with recent NVIDIA driver versions and NVML library versions.
- Whether ctypes-based bindings remain functional across different operating systems without maintenance.

## Package facts

- License: BSD (permissive)
- Python support: unspecified
- Install friction: high
- Maintenance: abandoned
- Downloads: 481.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

nvidia gpu monitoring python, nvml python bindings, gpu memory usage query, nvidia device management, cuda gpu info python, nvidia driver version check, gpu status monitoring, gpu-monitoring, nvidia-bindings, abandoned

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