Petals 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.
| Feature | Petals | Wllama |
|---|---|---|
| Deploy effort | Under-an-hour setup | Read-the-docs project |
| Health score | 24 · At risk | 84 · Excellent |
| Category | Local LLM Runners | Local LLM Runners |
| License | MIT | MIT |
| Language | Python | TypeScript |
| Setup difficulty | Hard | Medium |
| Min. RAM | 8,192 MB | 512 MB |
| Deployment | source, docker | source |
| GitHub stars | ★ 10,585 | ★ 1,309 |
| First released | 2022 | 2024 |
| Replaces | OpenAI API | OpenAI API |
What are Petals and Wllama?
Petals
Petals lets you run and fine-tune large language models in a distributed, BitTorrent-style network where each participant hosts part of the model. It enables self-hosting models too large for a single machine.
- Distributed model hosting
- Run models larger than one GPU
- Collaborative inference swarm
- Fine-tuning support
Wllama
Wllama is an open-source WebAssembly binding for llama.cpp that allows large language models to run entirely inside the browser. It can be hosted as a static site to provide fully client-side AI inference.
- Browser-based inference
- WebAssembly powered
- No server needed
- Static site deployable
Petals vs Wllama: key differences
Petals is written in Python, while Wllama is built with TypeScript. Wllama is the lighter option, starting around 512 MB of RAM against 8,192 MB for Petals. Petals is the more established project (first released 2022), while Wllama arrived in 2024. Petals has the considerably larger community, at 10,585 GitHub stars versus 1,309. Petals lists first-class Docker deployment; Wllama does not.
Why pick each one
Choose Petals if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Mature project with 10.6k GitHub stars
- Written in Python
Choose Wllama if…
- Released under the MIT license
- Active community (1.3k GitHub stars)
- Written in TypeScript
- Lightweight — runs in 512 MB RAM
Frequently asked questions
Is Petals or Wllama better?
Neither is universally better. Petals 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 Petals and Wllama free and open-source?
Yes. Petals is licensed under MIT and Wllama under MIT. Both can be self-hosted at no software cost.
Can I run Petals and Wllama with Docker?
Petals: yes. Wllama: check the project docs for container support.
Which is lighter on resources, Petals or Wllama?
Wllama has the smaller minimum footprint at 512 MB of RAM, compared to about 8,192 MB for Petals. Real-world usage depends on library size, user count, and enabled features.