FastChat vs Wllama
A side-by-side comparison of two self-hosted local llm runners options — licensing, setup difficulty, resource needs, and what each one replaces.
Not the right match-up?
FastChat
Platform for serving and evaluating large language models
VS
Wllama
Run LLM inference directly in the browser with WebAssembly
| Feature | FastChat | Wllama |
|---|---|---|
| Category | Local LLM Runners | Local LLM Runners |
| License | Apache-2.0 | MIT |
| Language | Python | TypeScript |
| Setup difficulty | Hard | Medium |
| Min. RAM | 8,192 MB | 512 MB |
| Deployment | docker, source | source |
| GitHub stars | ★ 39,516 | ★ 1,159 |
| First released | 2023 | 2024 |
| Replaces | OpenAI API | OpenAI API |
Why pick each one
Choose FastChat if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Mature project with 39.5k GitHub stars
- Written in Python
Choose Wllama if…
- Released under the MIT license
- Active community (1.2k GitHub stars)
- Written in TypeScript
- Lightweight — runs in 512 MB RAM
Frequently asked questions
Is FastChat or Wllama better?
Neither is universally better. FastChat has the larger community, while Wllama is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.
Are FastChat and Wllama free and open-source?
Yes. FastChat is licensed under Apache-2.0 and Wllama under MIT. Both can be self-hosted at no software cost.
Can I run FastChat and Wllama with Docker?
FastChat: yes. Wllama: check the project docs for container support.