Continue 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.
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Continue
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llama.cpp
High-performance LLM inference in plain C/C++
| Feature | Continue | llama.cpp |
|---|---|---|
| Category | Local LLM Runners | Local LLM Runners |
| License | Apache-2.0 | MIT |
| Language | TypeScript | C++ |
| Setup difficulty | Easy | Hard |
| Min. RAM | 1,024 MB | 8,192 MB |
| Deployment | bare-metal, source | binary, bare-metal, docker |
| GitHub stars | ★ 35,374 | ★ 123,039 |
| First released | 2023 | 2023 |
| Replaces | GitHub Copilot, Cursor | OpenAI API |
Why pick each one
Choose Continue if…
- Released under the Apache-2.0 license
- Easy to set up — beginner-friendly
- Mature project with 35.4k GitHub stars
- Written in TypeScript
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 Continue or llama.cpp better?
Neither is universally better. llama.cpp has the larger community, while Continue is simpler to set up (easy difficulty). Choose based on the comparison table above and your own setup.
Are Continue and llama.cpp free and open-source?
Yes. Continue is licensed under Apache-2.0 and llama.cpp under MIT. Both can be self-hosted at no software cost.
Can I run Continue and llama.cpp with Docker?
Continue: check the project docs for container support. llama.cpp: yes.