AI ERP with agents inside the systems you run
AI phone and voice agents for real calls
LLM.coPrivate, self-hosted LLM deployments
Legal AI infrastructure for firms
AI RFP discovery and response drafting
Automatic.coBusiness process automation
CyberAttack.aiThreat detection and defense
Secure AI virtual data roomsgpustat
gpustat is a lightweight command-line tool that displays GPU status and resource usage for NVIDIA GPUs in a human-readable format, similar to nvidia-smi but simpler. It supports colored output, process monitoring, and JSON export, and can be used both as a CLI utility and as a Python library.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | wookayin/gpustat |
| Owner | wookayin |
| Primary language | Python |
| License | MIT — OSI-approved |
| Stars | 4.4k |
| Forks | 286 |
| Open issues | 29 |
| Latest release | v1.1.1 (2023-08-22) |
| Last updated | 2026-05-30 |
| Source | https://github.com/wookayin/gpustat |
What gpustat is
Python-based CLI utility that queries NVIDIA GPU metrics via the official nvidia-ml-py binding (NVML). Provides real-time GPU utilization, memory usage, temperature, and process-level monitoring with configurable output formats (colored text, JSON, watch mode). Requires NVIDIA Driver >=450.00 and Python >=3.6.
Get the gpustat source
Clone the repository and explore it locally.
git clone https://github.com/wookayin/gpustat.gitcd gpustat# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Ensure nvidia-ml-py (>=12.535.108 for gpustat 1.2+) is installed from official PyPI, not the misleadingly named 'pynvml' package.
- Set CUDA_DEVICE_ORDER=PCI_BUS_ID environment variable if GPU index must match CUDA device numbering in production workloads.
- For fast repeated queries in high-frequency monitoring, run nvidia-smi daemon (requires root) to reduce CPU overhead per query.
- Python 3.6+ required; no Python 2.7 support in current versions (1.1+).
- Output format (color, verbosity, JSON) configurable per-invocation; integrate via shell scripts or Python API for custom workflows.
When to avoid it — and what to weigh
- AMD GPU environments — Tool is NVIDIA-only; contributors are welcome but no AMD support currently implemented.
- Systems with very old NVIDIA drivers — Requires Driver >=450.00; older GPUs may be unsupported unless using legacy gpustat versions.
- Need for enterprise-grade alerting — gpustat is a query tool; complex alerting rules, thresholds, and incident management require external orchestration.
- Heterogeneous GPU fleets — Designed for homogeneous NVIDIA setups; no built-in multi-vendor or multi-architecture abstraction.
License & commercial use
MIT License. Permissive OSI-approved license; allows use in proprietary and commercial software with attribution.
MIT permits commercial use, modification, and distribution. Attribution required; no warranty provided. Suitable for proprietary internal tools and closed-source commercial products without restriction.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Low |
| DEV.co fit | Strong |
| Assessment confidence | High |
No sensitive data exposure from GPU queries themselves. Tool requires read access to NVIDIA driver and process list; running with elevated privileges (nvidia-smi daemon) may expand attack surface. Input validation (GPU IDs, watch intervals) not detailed in README. User/process name display can leak information in multi-tenant environments; mitigate with --no-processes flag.
Alternatives to consider
nvidia-smi
Official NVIDIA CLI. More verbose and feature-rich; gpustat is a simpler, friendlier front-end for common queries.
py-nvml / nvidia-ml-py
Lower-level Python bindings. Requires more boilerplate code; gpustat provides pre-built queries and formatted output.
Prometheus nvidia-gpu-prometheus-exporter
Enterprise monitoring exporter. Heavier weight; gpustat is lighter for ad-hoc queries and simple dashboards.
Build on gpustat with DEV.co software developers
Install gpustat via pip and integrate GPU health checks into your ML ops, cluster management, or development workflow. MIT licensed for commercial use.
Talk to DEV.coRelated open-source tools
Surfaced by semantic similarity across the DEV.co open-source index.
Related on DEV.co
Explore the category and the services that help you build with it.
gpustat FAQ
Can I use this on AMD GPUs?
Does gpustat require root?
How do I integrate gpustat into my monitoring stack?
What Python versions does gpustat 1.1 support?
Software development & web development with DEV.co
From first prototype to production, DEV.co delivers custom software development around tools like gpustat. We staff experienced engineers for integrations, web development, and ongoing support across open-source observability and beyond.
Ready to simplify GPU monitoring?
Install gpustat via pip and integrate GPU health checks into your ML ops, cluster management, or development workflow. MIT licensed for commercial use.