head to head · open source
Ollama vs langchain4j
Ollama has 185,702 GitHub stars, 18,873 forks, 3,957 open issues and last shipped yesterday. langchain4j has 13,344 stars, 2,657 forks, 878 open issues and last shipped yesterday. Ollama leads on adoption by 1,292% (185,702 vs 13,344 stars). Ollama is written in Go under MIT; langchain4j is written in Java under Apache-2.0. Ollama has attracted 10% as many forks as stars, langchain4j 20%. Ollama was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (llama, llm, llms), 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
| Ollama | langchain4j | |
|---|---|---|
| GitHub stars | ★ 186K | ★ 13K |
| License | MIT | Apache-2.0 |
| Written in | Go | Java |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 19K | ⑂ 2.7K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Ollama if
- You weight community size — 186K stars and counting
- You want the MIT license terms
- Your stack matches Go
- 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 Ollama
Ollama Start building with open models. Download macOS or download manually Windows or download manually Linux Manual install instructions Docker The official Ollama Docker image ollama/ollama is available on Docker Hub. Libraries ollama python ollama js Community Discord 𝕏 (Twitter) Reddit Get started You'll be prompted to run a model or connect Ollama to your existing agents or applications such as Claude Code , OpenClaw , OpenCode , Codex , Copilot , and more. Coding To launch a specific integration: Supported integrations include Claude Code, Codex, Copilot CLI, DeepSeek Harness, Droid, and OpenCode. AI…
read the full Ollama overview →
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 Ollama or langchain4j more popular?
Ollama has 185,702 GitHub stars and langchain4j has 13,344. Ollama has the larger community by that measure.
Are Ollama and langchain4j free?
Both are open source. Ollama is licensed under MIT and langchain4j under Apache-2.0. Neither carries a licence fee.
What is the difference between Ollama and langchain4j?
Ollama is written in Go 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, Ollama or langchain4j?
Choose Ollama if you want the larger community (185,702 stars) or its MIT licence terms. Choose langchain4j if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.