Continue vs Harbor LLM Toolkit
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?
Continue
Open-source AI code assistant for VS Code and JetBrains
VS
Harbor LLM Toolkit
Containerized LLM toolkit to run a local AI stack with one CLI
| Feature | Continue | Harbor LLM Toolkit |
|---|---|---|
| Category | Local LLM Runners | Local LLM Runners |
| License | Apache-2.0 | Apache-2.0 |
| Language | TypeScript | Python |
| Setup difficulty | Easy | Easy |
| Min. RAM | 1,024 MB | 8,192 MB |
| Deployment | bare-metal, source | docker |
| GitHub stars | ★ 35,374 | ★ 3,158 |
| First released | 2023 | 2024 |
| Replaces | GitHub Copilot, Cursor | OpenAI Platform |
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 Harbor LLM Toolkit if…
- Released under the Apache-2.0 license
- Easy to set up — beginner-friendly
- First-class Docker support for quick deployment
- Active community (3.2k GitHub stars)
Frequently asked questions
Is Continue or Harbor LLM Toolkit better?
Neither is universally better. Continue has the larger community; both share a easy setup difficulty, so the decision comes down to features and licensing.
Are Continue and Harbor LLM Toolkit free and open-source?
Yes. Continue is licensed under Apache-2.0 and Harbor LLM Toolkit under Apache-2.0. Both can be self-hosted at no software cost.
Can I run Continue and Harbor LLM Toolkit with Docker?
Continue: check the project docs for container support. Harbor LLM Toolkit: yes.