head to head · open source
vllm vs dingo
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. dingo has 1,705 stars, 263 forks, 8 open issues and last shipped 4 days ago. vllm leads on adoption by 5,540% (96,158 vs 1,705 stars). vllm is written in Python under Apache-2.0; dingo is written in Java under Apache-2.0. vllm has attracted 25% as many forks as stars, dingo 15%. 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 | dingo | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 1.7K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Java |
| Last push | 2026-11-02 | 2026-10-30 |
| Forks | ⑂ 24K | ⑂ 263 |
| 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 dingo if
- You want the dingo feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Java
- You evaluated both and dingo 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 dingo
DingoDB DingoDB is an open source distributed multi modal vector database independently designed and developed by DataCanvas, which integrates real time strong consistency, relational semantics, and vector semantics into a unified platform, DingoDB positioning itself as a distinctive multi modal database solution. With exceptional horizontal scalability and elastic scaling capabilities, it effortlessly meets enterprise grade high availability requirements. Furthermore, DingoDB offers extensive multi language interfaces and seamless compatibility with the MySQL protocol, delivering unparalleled flexibility and…
read the full dingo overview →
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Frequently asked questions
Is vllm or dingo more popular?
vllm has 96,158 GitHub stars and dingo has 1,705. vllm has the larger community by that measure.
Are vllm and dingo free?
Both are open source. vllm is licensed under Apache-2.0 and dingo under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and dingo?
vllm is written in Python and dingo in Java. 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 dingo?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose dingo if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.