exo 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.
| Feature | exo | LMDeploy |
|---|---|---|
| Deploy effort | Read-the-docs project | Under-an-hour setup |
| Health score | 98 · Excellent | 92 · Excellent |
| Category | Local LLM Runners | Local LLM Runners |
| License | GPL-3.0 | Apache-2.0 |
| Language | Python | Python |
| Setup difficulty | Medium | Hard |
| Min. RAM | 8,192 MB | 16,384 MB |
| Deployment | source | docker, source |
| GitHub stars | ★ 47,624 | ★ 8,097 |
| First released | 2024 | 2023 |
| Replaces | OpenAI API | OpenAI API, Hugging Face Inference Endpoints |
What are exo and LMDeploy?
exo
exo is an open-source project that unifies multiple everyday devices into a single AI compute cluster for running large language models. It splits models across phones, laptops, and desktops and exposes an OpenAI-compatible API.
- Distributes models across devices
- OpenAI-compatible API
- Automatic device discovery
- No master node required
LMDeploy
LMDeploy is an inference and serving toolkit from the OpenMMLab ecosystem for deploying large language models efficiently. It offers quantization, a high-throughput serving engine, and an OpenAI-compatible API.
- High-throughput inference engine
- Weight quantization support
- OpenAI-compatible serving
- Multi-GPU deployment
exo vs LMDeploy: key differences
Both projects are written in Python. Licensing differs — GPL-3.0 for exo versus Apache-2.0 for LMDeploy. Exo is the lighter option, starting around 8,192 MB of RAM against 16,384 MB for LMDeploy. Exo has the considerably larger community, at 47,624 GitHub stars versus 8,097. LMDeploy lists first-class Docker deployment; exo does not.
Why pick each one
Choose exo if…
- Pools everyday devices
- OpenAI-compatible API
- Runs fully offline
Watch out for
- Experimental and evolving
- Network limits performance
Choose LMDeploy if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Mature project with 8.1k GitHub stars
- Written in Python
Frequently asked questions
Is exo or LMDeploy better?
exo is the stronger all-round pick: it has both the larger community and the simpler medium setup. Consider LMDeploy if its specific feature set fits your needs better.
Are exo and LMDeploy free and open-source?
Yes. exo is licensed under GPL-3.0 and LMDeploy under Apache-2.0. Both can be self-hosted at no software cost.
Can I run exo and LMDeploy with Docker?
exo: check the project docs for container support. LMDeploy: yes.
Which is lighter on resources, exo or LMDeploy?
exo has the smaller minimum footprint at 8,192 MB of RAM, compared to about 16,384 MB for LMDeploy. Real-world usage depends on library size, user count, and enabled features.