exo vs vLLM
A side-by-side comparison of two self-hosted local llm runners options — licensing, setup difficulty, resource needs, and what each one replaces.
vLLM
High-throughput LLM serving engine with PagedAttention
| Feature | exo | vLLM |
|---|---|---|
| Deploy effort | Read-the-docs project | Under-an-hour setup |
| Health score | 98 · Excellent | 100 · 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, kubernetes, bare-metal |
| GitHub stars | ★ 47,611 | ★ 92,464 |
| First released | 2024 | 2023 |
| Replaces | OpenAI API | OpenAI API |
What are exo and vLLM?
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
vLLM
vLLM is a fast and memory-efficient inference and serving engine for large language models. Its PagedAttention algorithm delivers high throughput batching, and it exposes an OpenAI-compatible server for production deployments.
- PagedAttention memory management
- Continuous batching
- OpenAI-compatible server
- Tensor parallelism
exo vs vLLM: key differences
Both projects are written in Python. Licensing differs — GPL-3.0 for exo versus Apache-2.0 for vLLM. Exo is the lighter option, starting around 8,192 MB of RAM against 16,384 MB for vLLM. VLLM 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 vLLM if…
- Excellent serving throughput
- OpenAI-compatible API
- Efficient GPU memory use
Watch out for
- GPU practically required
- Complex tuning options
Frequently asked questions
Is exo or vLLM better?
Neither is universally better. vLLM has the larger community, while exo is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.
Are exo and vLLM free and open-source?
Yes. exo is licensed under GPL-3.0 and vLLM under Apache-2.0. Both can be self-hosted at no software cost.
Can I run exo and vLLM with Docker?
exo: check the project docs for container support. vLLM: yes.
Which is lighter on resources, exo or vLLM?
exo has the smaller minimum footprint at 8,192 MB of RAM, compared to about 16,384 MB for vLLM. Real-world usage depends on library size, user count, and enabled features.