GPUStack vs SGLang
A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.
| Feature | GPUStack | SGLang |
|---|---|---|
| Deploy effort | Under-an-hour setup | Under-an-hour setup |
| Health score | 90 · Excellent | 99 · Excellent |
| Category | Self-Hosted AI | Self-Hosted AI |
| License | Apache-2.0 | Apache-2.0 |
| Language | Python | Python |
| Setup difficulty | Medium | Hard |
| Min. RAM | 8,192 MB | 16,384 MB |
| Deployment | docker, kubernetes, bare-metal | docker, kubernetes, bare-metal |
| GitHub stars | ★ 5,754 | ★ 36,383 |
| First released | 2024 | 2024 |
| Replaces | OpenAI API | OpenAI API |
What are GPUStack and SGLang?
GPUStack
GPUStack is an open-source platform for running and scaling AI models across heterogeneous GPU clusters. It supports LLMs, embeddings, image, and audio models with an OpenAI-compatible API and a management dashboard.
- Distributed GPU scheduling
- OpenAI-compatible API
- Many model types
- Cluster dashboard
SGLang
SGLang is a high-performance serving framework for large language and vision-language models. It features a fast runtime with RadixAttention and a flexible programming language for complex LLM applications.
- RadixAttention caching
- Structured generation
- OpenAI-compatible server
- Multi-GPU scaling
GPUStack vs SGLang: key differences
Both projects are written in Python. GPUStack is the lighter option, starting around 8,192 MB of RAM against 16,384 MB for SGLang. SGLang has the considerably larger community, at 36,383 GitHub stars versus 5,754.
Why pick each one
Choose GPUStack if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Kubernetes-ready with Helm charts available
- Mature project with 5.8k GitHub stars
Choose SGLang if…
- Very high throughput
- RadixAttention prefix caching
- Vision model support
Watch out for
- Serious GPU required
- Complex tuning options
Frequently asked questions
Is GPUStack or SGLang better?
Neither is universally better. SGLang has the larger community, while GPUStack is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.
Are GPUStack and SGLang free and open-source?
Yes. GPUStack is licensed under Apache-2.0 and SGLang under Apache-2.0. Both can be self-hosted at no software cost.
Can I run GPUStack and SGLang with Docker?
GPUStack: yes. SGLang: yes.
Which is lighter on resources, GPUStack or SGLang?
GPUStack has the smaller minimum footprint at 8,192 MB of RAM, compared to about 16,384 MB for SGLang. Real-world usage depends on library size, user count, and enabled features.