head to head · open source
vllm vs vearch
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. vearch has 2,333 stars, 366 forks, 170 open issues and last shipped 3 months ago. vllm leads on adoption by 4,022% (96,158 vs 2,333 stars). vllm is written in Python under Apache-2.0; vearch is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, vearch 16%. 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 | vearch | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 2.3K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-07-27 |
| Forks | ⑂ 24K | ⑂ 366 |
| 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 vearch if
- You want the vearch 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 vearch 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 vearch
简体中文 English Overview Vearch is a cloud native distributed vector database for efficient similarity search of embedding vectors in your AI applications. Key features Hybrid search : Both vector search and scalar filtering. Performance : Fast vector retrieval search from millions of objects in milliseconds. Scalability & Reliability : Replication and elastic scaling out. Document Restful APIs Tutorial 参考文档 OpenAPIs API Documentation SDK Usage Cases Use Vearch as a Memory Backend Vearch integrates with popular AI frameworks: Real world Demos VisualSearch : Vearch can be leveraged to build a complete visual search…
read the full vearch overview →
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Frequently asked questions
Is vllm or vearch more popular?
vllm has 96,158 GitHub stars and vearch has 2,333. vllm has the larger community by that measure.
Are vllm and vearch free?
Both are open source. vllm is licensed under Apache-2.0 and vearch under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and vearch?
vllm is written in Python and vearch 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 vearch?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose vearch if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.