Llama Stack 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.
Not the right match-up?
Llama Stack
Composable API server for building generative AI applications
VS
SGLang
Fast serving framework for LLMs and vision-language models
| Feature | Llama Stack | SGLang |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | MIT | Apache-2.0 |
| Language | Python | Python |
| Setup difficulty | Medium | Hard |
| Min. RAM | 4,096 MB | 16,384 MB |
| Deployment | docker, source | docker, kubernetes, bare-metal |
| GitHub stars | ★ 8,421 | ★ 31,514 |
| First released | 2024 | 2024 |
| Replaces | OpenAI API | OpenAI API |
Why pick each one
Choose Llama Stack if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Mature project with 8.4k GitHub stars
- Written in Python
Choose SGLang if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Kubernetes-ready with Helm charts available
- Mature project with 31.5k GitHub stars
Frequently asked questions
Is Llama Stack or SGLang better?
Neither is universally better. SGLang has the larger community, while Llama Stack is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.
Are Llama Stack and SGLang free and open-source?
Yes. Llama Stack is licensed under MIT and SGLang under Apache-2.0. Both can be self-hosted at no software cost.
Can I run Llama Stack and SGLang with Docker?
Llama Stack: yes. SGLang: yes.