GPUStack
Open-source GPU cluster manager for running large language models.
- Status
- Generally available
- Last checked
- Checked · Oct 15, 2026
- License
- Open source
- Pricing
- Free tier · from $0
What it is
GPUStack is an open-source tool designed to manage GPU clusters efficiently, enabling the execution of large language models. It simplifies resource allocation and management for developers working with computationally intensive AI tasks.
GPUStack stands out as a lightweight, open-source alternative for managing GPU clusters, offering flexibility and control without the overhead of cloud-based solutions.
When it fits — and when it doesn’t
A good fit for
Teams needing to manage multiple GPUs for running large language models efficiently.
Projects that require scalable GPU resource management without cloud dependency.
Organizations looking for an open-source solution for GPU cluster management.
Look elsewhere if
Developers who prefer managed cloud services over self-hosted solutions.
Teams with limited technical expertise in setting up and managing their own GPU clusters.
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Performance bottlenecks in high-concurrency scenarios
Known issues with task scheduling under heavy load can lead to suboptimal GPU utilization
What it does well
Efficient GPU resource management for large language models.
Scalable architecture to handle varying workloads.
Open-source with a permissive license.
Pricing
- Free tier
- YesOpen source — free to use
- Paid from
- $0
- Model
- Flat rate
- Enterprise plan
- No
Pricing not independently confirmed — check the vendor’s page.
Performance benchmarks
How Fast Is It?
Set up GPUStack
Setup steps, common gotchas and what to check after 30 days.
Get the badge
A small badge for GPUStack’s README or site: its name, “Tracked on AI Navigator”, and the availability status and check month from this page. It updates as the catalog does.
Markdown
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