openedai-speech 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 | openedai-speech | SGLang |
|---|---|---|
| Deploy effort | Under-an-hour setup | Under-an-hour setup |
| Health score | 13 · At risk | 99 · Excellent |
| Status | Archived | Actively maintained |
| Category | Self-Hosted AI | Self-Hosted AI |
| License | AGPL-3.0 | Apache-2.0 |
| Language | Python | Python |
| Setup difficulty | Easy | Hard |
| Min. RAM | 2,048 MB | 16,384 MB |
| Deployment | docker | docker, kubernetes, bare-metal |
| GitHub stars | ★ 857 | ★ 36,383 |
| First released | 2024 | 2024 |
| Replaces | OpenAI API, ElevenLabs | OpenAI API |
What are openedai-speech and SGLang?
openedai-speech
openedai-speech is a self-hosted text-to-speech server that mimics the OpenAI audio speech API. It uses local models such as Piper and Coqui XTTS to generate audio without sending data to the cloud.
- OpenAI speech API compatible
- Piper and XTTS backends
- Custom voice mapping
- Drop-in replacement
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
openedai-speech vs SGLang: key differences
The biggest difference is maintenance: openedai-speech's repository is archived and no longer developed, while SGLang is actively maintained. Both projects are written in Python. Licensing differs — AGPL-3.0 for openedai-speech versus Apache-2.0 for SGLang. Openedai-speech is the lighter option, starting around 2,048 MB of RAM against 16,384 MB for SGLang. SGLang has the considerably larger community, at 36,383 GitHub stars versus 857.
Why pick each one
Choose openedai-speech if…
- Released under the AGPL-3.0 license
- Easy to set up — beginner-friendly
- First-class Docker support for quick deployment
- Written in Python
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 openedai-speech or SGLang better?
Neither is universally better. SGLang has the larger community, while openedai-speech is simpler to set up (easy difficulty). Choose based on the comparison table above and your own setup.
Are openedai-speech and SGLang free and open-source?
Yes. openedai-speech is licensed under AGPL-3.0 and SGLang under Apache-2.0. Both can be self-hosted at no software cost.
Can I run openedai-speech and SGLang with Docker?
openedai-speech: yes. SGLang: yes.
Which is lighter on resources, openedai-speech or SGLang?
openedai-speech has the smaller minimum footprint at 2,048 MB of RAM, compared to about 16,384 MB for SGLang. Real-world usage depends on library size, user count, and enabled features.