FastChat vs llama.cpp
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
llama.cpp
High-performance LLM inference in plain C/C++
| Feature | FastChat | llama.cpp |
|---|---|---|
| Category | Local LLM Runners | Local LLM Runners |
| License | Apache-2.0 | MIT |
| Language | Python | C++ |
| Setup difficulty | Hard | Hard |
| Min. RAM | 8,192 MB | 8,192 MB |
| Deployment | docker, source | binary, bare-metal, docker |
| GitHub stars | ★ 39,516 | ★ 123,039 |
| First released | 2023 | 2023 |
| 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 llama.cpp if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Mature project with 123k GitHub stars
- Written in C++
Frequently asked questions
Is FastChat or llama.cpp better?
Neither is universally better. llama.cpp has the larger community; both share a hard setup difficulty, so the decision comes down to features and licensing.
Are FastChat and llama.cpp free and open-source?
Yes. FastChat is licensed under Apache-2.0 and llama.cpp under MIT. Both can be self-hosted at no software cost.
Can I run FastChat and llama.cpp with Docker?
FastChat: yes. llama.cpp: yes.