head to head · open source
vllm vs burr
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. burr has 2,589 stars, 215 forks, 99 open issues and last shipped yesterday. vllm leads on adoption by 3,614% (96,158 vs 2,589 stars). vllm is written in Python under Apache-2.0; burr is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, burr 8%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| vllm | burr | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 2.6K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 24K | ⑂ 215 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick vllm if
- You weight community size — 96K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick burr if
- You want the burr feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and burr fits your workflow better
About vllm
Easy, fast, and cheap LLM serving for everyone 🔥 We have built a vLLM website to help you get started with vLLM. Please visit vllm.ai to learn more. For events, please visit vllm.ai/events to join us. About vLLM is a fast and easy to use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has grown into one of the most active open source AI projects built and maintained by a diverse community of many dozens of academic institutions and companies from over 2000 contributors. vLLM is fast with: State of the art serving throughput Efficient management of…
About burr
Apache Burr (incubating) Apache Burr (incubating) makes it easy to develop applications that make decisions (chatbots, agents, simulations, etc...) from simple python building blocks. Apache Burr works well for any application that uses LLMs, and can integrate with any of your favorite frameworks. Burr includes a UI that can track/monitor/trace your system in real time, along with pluggable persisters (e.g. for memory) to save & load application state. Link to documentation. Quick ( [!NOTE] In version 0.43.0, the optional CLI included with [start] , [learn] , and [cli] requires Python 3.10+. Core library usage…
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Frequently asked questions
Is vllm or burr more popular?
vllm has 96,158 GitHub stars and burr has 2,589. vllm has the larger community by that measure.
Are vllm and burr free?
Both are open source. vllm is licensed under Apache-2.0 and burr under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and burr?
vllm is written in Python and burr in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, vllm or burr?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose burr if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.