GPU & Compute

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.

  1. 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.

Open the setup guide →
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GPUStack — tracked on AI Navigator

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