ExLlamaV2 vs screenshot-to-code
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?
ExLlamaV2
Fast inference library for quantized LLMs on consumer GPUs
VS
screenshot-to-code
Convert screenshots and designs into working code
| Feature | ExLlamaV2 | screenshot-to-code |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | MIT | MIT |
| Language | Python | Python |
| Setup difficulty | Hard | Easy |
| Min. RAM | 8,192 MB | 1,024 MB |
| Deployment | bare-metal, source | docker, bare-metal |
| GitHub stars | ★ 4,602 | ★ 73,884 |
| First released | 2023 | 2023 |
| Replaces | OpenAI API | Vercel v0 |
Why pick each one
Choose ExLlamaV2 if…
- Released under the MIT license
- Active community (4.6k GitHub stars)
- Written in Python
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
Frequently asked questions
Is ExLlamaV2 or screenshot-to-code better?
screenshot-to-code is the stronger all-round pick: it has both the larger community and the simpler easy setup. Consider ExLlamaV2 if its specific feature set fits your needs better.
Are ExLlamaV2 and screenshot-to-code free and open-source?
Yes. ExLlamaV2 is licensed under MIT and screenshot-to-code under MIT. Both can be self-hosted at no software cost.
Can I run ExLlamaV2 and screenshot-to-code with Docker?
ExLlamaV2: check the project docs for container support. screenshot-to-code: yes.