FastChat 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 | FastChat | vLLM |
|---|---|---|
| Deploy effort | Under-an-hour setup | Under-an-hour setup |
| Health score | 69 · Good | 100 · Excellent |
| Category | Local LLM Runners | Local LLM Runners |
| License | Apache-2.0 | Apache-2.0 |
| Language | Python | Python |
| Setup difficulty | Hard | Hard |
| Min. RAM | 8,192 MB | 16,384 MB |
| Deployment | docker, source | docker, kubernetes, bare-metal |
| GitHub stars | ★ 39,549 | ★ 92,464 |
| First released | 2023 | 2023 |
| Replaces | OpenAI API | OpenAI API |
What are FastChat and vLLM?
FastChat
FastChat is an open platform for training, serving, and evaluating large language model chatbots. It powers the Chatbot Arena and provides an OpenAI-compatible API server for self-hosted models.
- OpenAI-compatible API
- Web UI for model chat
- Distributed serving
- Model evaluation tools
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
FastChat vs vLLM: key differences
Both projects are written in Python. FastChat is the lighter option, starting around 8,192 MB of RAM against 16,384 MB for vLLM. VLLM has the considerably larger community, at 92,464 GitHub stars versus 39,549.
Why pick each one
Choose FastChat if…
- OpenAI-compatible API
- Powers Chatbot Arena
- Multi-model serving
Watch out for
- GPU recommended
- Steep learning curve
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 FastChat or vLLM better?
Neither is universally better. vLLM has the larger community; both share a hard setup difficulty, so the decision comes down to features and licensing.
Are FastChat and vLLM free and open-source?
Yes. FastChat is licensed under Apache-2.0 and vLLM under Apache-2.0. Both can be self-hosted at no software cost.
Can I run FastChat and vLLM with Docker?
FastChat: yes. vLLM: yes.
Which is lighter on resources, FastChat or vLLM?
FastChat 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.