Continue vs LMDeploy
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
LMDeploy
Toolkit for compressing and serving large language models
| Feature | Continue | LMDeploy |
|---|---|---|
| Category | Local LLM Runners | Local LLM Runners |
| License | Apache-2.0 | Apache-2.0 |
| Language | TypeScript | Python |
| Setup difficulty | Easy | Hard |
| Min. RAM | 1,024 MB | 16,384 MB |
| Deployment | bare-metal, source | docker, source |
| GitHub stars | ★ 35,374 | ★ 7,998 |
| First released | 2023 | 2023 |
| Replaces | GitHub Copilot, Cursor | OpenAI API, Hugging Face Inference Endpoints |
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 LMDeploy if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Mature project with 8k GitHub stars
- Written in Python
Frequently asked questions
Is Continue or LMDeploy better?
Continue is the stronger all-round pick: it has both the larger community and the simpler easy setup. Consider LMDeploy if its specific feature set fits your needs better.
Are Continue and LMDeploy free and open-source?
Yes. Continue is licensed under Apache-2.0 and LMDeploy under Apache-2.0. Both can be self-hosted at no software cost.
Can I run Continue and LMDeploy with Docker?
Continue: check the project docs for container support. LMDeploy: yes.