Enchanted vs vLLM
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?
Enchanted
Native Ollama client for iOS and macOS
VS
vLLM
High-throughput LLM serving engine with PagedAttention
| Feature | Enchanted | vLLM |
|---|---|---|
| Category | Local LLM Runners | Local LLM Runners |
| License | Apache-2.0 | Apache-2.0 |
| Language | Swift | Python |
| Setup difficulty | Easy | Hard |
| Min. RAM | 256 MB | 16,384 MB |
| Deployment | binary | docker, kubernetes, bare-metal |
| GitHub stars | ★ 5,983 | ★ 88,482 |
| First released | 2024 | 2023 |
| Replaces | ChatGPT | OpenAI API |
Why pick each one
Choose Enchanted if…
- Released under the Apache-2.0 license
- Easy to set up — beginner-friendly
- Mature project with 6k GitHub stars
- Written in Swift
Choose vLLM if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Kubernetes-ready with Helm charts available
- Mature project with 88.5k GitHub stars
Frequently asked questions
Is Enchanted or vLLM better?
Neither is universally better. vLLM has the larger community, while Enchanted is simpler to set up (easy difficulty). Choose based on the comparison table above and your own setup.
Are Enchanted and vLLM free and open-source?
Yes. Enchanted is licensed under Apache-2.0 and vLLM under Apache-2.0. Both can be self-hosted at no software cost.
Can I run Enchanted and vLLM with Docker?
Enchanted: check the project docs for container support. vLLM: yes.