head to head · open source
vllm vs infinity
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. infinity has 4,755 stars, 458 forks, 126 open issues and last shipped yesterday. vllm leads on adoption by 1,922% (96,158 vs 4,755 stars). vllm is written in Python under Apache-2.0; infinity is written in C++ under Apache-2.0. vllm has attracted 25% as many forks as stars, infinity 10%. 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 | infinity | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 4.8K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | C++ |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 24K | ⑂ 458 |
| 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 infinity if
- You want the infinity feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches C++
- You evaluated both and infinity 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 infinity
The AI native database built for LLM applications, providing incredibly fast hybrid search of dense embedding, sparse embedding, tensor and full text Document Benchmark Twitter Discord Infinity is a cutting edge AI native database that provides a wide range of search capabilities for rich data types such as dense vector, sparse vector, tensor, full text, and structured data. It provides robust support for various LLM applications, including search, recommenders, question answering, conversational AI, copilot, content generation, and many more RAG (Retrieval augmented Generation) applications. Key Features Get…
read the full infinity overview →
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Frequently asked questions
Is vllm or infinity more popular?
vllm has 96,158 GitHub stars and infinity has 4,755. vllm has the larger community by that measure.
Are vllm and infinity free?
Both are open source. vllm is licensed under Apache-2.0 and infinity under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and infinity?
vllm is written in Python and infinity in C++. 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 infinity?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose infinity if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.