head to head · open source
vllm vs langchain4j
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. langchain4j has 13,344 stars, 2,657 forks, 878 open issues and last shipped yesterday. vllm leads on adoption by 621% (96,158 vs 13,344 stars). vllm is written in Python under Apache-2.0; langchain4j is written in Java under Apache-2.0. vllm has attracted 25% as many forks as stars, langchain4j 20%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (gpt, llama, llm), so they are genuine substitutes rather than adjacent tools.
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 | langchain4j | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 13K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Java |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 24K | ⑂ 2.7K |
| 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 langchain4j if
- You want the langchain4j 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 langchain4j 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 langchain4j
LangChain4j: idiomatic, open source Java library for building LLM powered applications on the JVM Introduction Welcome! The goal of LangChain4j is to simplify integrating LLMs into Java applications. Here's how: 1. Unified APIs: LLM providers (like OpenAI or Google Vertex AI) and embedding (vector) stores (such as Pinecone or Milvus) use proprietary APIs. LangChain4j offers a unified API to avoid the need for learning and implementing specific APIs for each of them. To experiment with different LLMs or embedding stores, you can easily switch between them without the need to rewrite your code. LangChain4j…
read the full langchain4j overview →
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Frequently asked questions
Is vllm or langchain4j more popular?
vllm has 96,158 GitHub stars and langchain4j has 13,344. vllm has the larger community by that measure.
Are vllm and langchain4j free?
Both are open source. vllm is licensed under Apache-2.0 and langchain4j under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and langchain4j?
vllm is written in Python and langchain4j 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 langchain4j?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose langchain4j if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.