head to head · open source
vllm vs examples
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. examples has 3,051 stars, 1,062 forks, 64 open issues and last shipped 11 days ago. vllm leads on adoption by 3,052% (96,158 vs 3,051 stars). vllm is written in Python under Apache-2.0; examples is written in Jupyter Notebook under MIT. vllm has attracted 25% as many forks as stars, examples 35%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (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.
← all 20902 open source comparisons
Side by side
| vllm | examples | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 3.1K |
| License | Apache-2.0 | MIT |
| Written in | Python | Jupyter Notebook |
| Last push | 2026-11-02 | 2026-10-23 |
| Forks | ⑂ 24K | ⑂ 1.1K |
| 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 examples if
- You want the examples feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Jupyter Notebook
- You evaluated both and examples 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 examples
Pinecone Examples This repository is a collection of sample applications and Jupyter Notebooks that you can run, download, study and modify in order to get hands on with Pinecone vector databases and common AI patterns, tools and algorithms. Two kinds of examples This repo contains: 1. Production ready examples in ./docs that receive regular review and support from the Pinecone engineering team 2. Examples optimized for learning and exploration of AI techniques in ./learn and patterns for building different kinds of applications, created and maintained by the Pinecone Developer Advocacy team. We appreciate your…
read the full examples overview →
More in AI & Machine Learning
Related comparisons
More Machine Learning Infrastructure projects
Compare either of these against the rest of the Machine Learning Infrastructure field.
Frequently asked questions
Is vllm or examples more popular?
vllm has 96,158 GitHub stars and examples has 3,051. vllm has the larger community by that measure.
Are vllm and examples free?
Both are open source. vllm is licensed under Apache-2.0 and examples under MIT. Neither carries a licence fee.
What is the difference between vllm and examples?
vllm is written in Python and examples in Jupyter Notebook. 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 examples?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose examples if its feature set, stack or MIT licence fits better. Both are self-hostable.