screenshot-to-code 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?
screenshot-to-code
Convert screenshots and designs into working code
VS
SGLang
Fast serving framework for LLMs and vision-language models
| Feature | screenshot-to-code | SGLang |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | MIT | Apache-2.0 |
| Language | Python | Python |
| Setup difficulty | Easy | Hard |
| Min. RAM | 1,024 MB | 16,384 MB |
| Deployment | docker, bare-metal | docker, kubernetes, bare-metal |
| GitHub stars | ★ 73,884 | ★ 31,514 |
| First released | 2023 | 2024 |
| Replaces | Vercel v0 | OpenAI API |
Why pick each one
Choose screenshot-to-code if…
- Released under the MIT license
- Easy to set up — beginner-friendly
- First-class Docker support for quick deployment
- Mature project with 73.9k GitHub stars
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 screenshot-to-code or SGLang better?
screenshot-to-code is the stronger all-round pick: it has both the larger community and the simpler easy setup. Consider SGLang if its specific feature set fits your needs better.
Are screenshot-to-code and SGLang free and open-source?
Yes. screenshot-to-code is licensed under MIT and SGLang under Apache-2.0. Both can be self-hosted at no software cost.
Can I run screenshot-to-code and SGLang with Docker?
screenshot-to-code: yes. SGLang: yes.