head to head · open source
vllm vs OpenLLMetry
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. OpenLLMetry has 7,516 stars, 1,183 forks, 676 open issues and last shipped yesterday. vllm leads on adoption by 1,179% (96,158 vs 7,516 stars). vllm is written in Python under Apache-2.0; OpenLLMetry is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, OpenLLMetry 16%. 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.
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Side by side
| vllm | OpenLLMetry | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 7.5K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 24K | ⑂ 1.2K |
| 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 OpenLLMetry if
- You want the OpenLLMetry 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 OpenLLMetry 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 OpenLLMetry
Open source observability for your LLM application Get started » Slack Docs Website 🎉 New : Our semantic conventions are now part of OpenTelemetry! Join the discussion and help us shape the future of LLM observability. Looking for the JS/TS version? Check out OpenLLMetry JS. OpenLLMetry is a set of extensions built on top of OpenTelemetry that gives you complete observability over your LLM application. Because it uses OpenTelemetry under the hood, it can be connected to your existing observability solutions Datadog, Honeycomb, and others. It's built and maintained by Traceloop under the Apache 2.0 license. The…
read the full OpenLLMetry overview →
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Frequently asked questions
Is vllm or OpenLLMetry more popular?
vllm has 96,158 GitHub stars and OpenLLMetry has 7,516. vllm has the larger community by that measure.
Are vllm and OpenLLMetry free?
Both are open source. vllm is licensed under Apache-2.0 and OpenLLMetry under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and OpenLLMetry?
vllm is written in Python and OpenLLMetry 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 OpenLLMetry?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose OpenLLMetry if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.