head to head · open source
vllm vs trnrt
vllm has 96,764 GitHub stars, 24,693 forks, 7,953 open issues and last shipped yesterday. trnrt has 1,317 stars, 12 forks, 10 open issues and last shipped yesterday. vllm leads on adoption by 7,247% (96,764 vs 1,317 stars). vllm is written in Python under Apache-2.0; trnrt is written in Python under Apache-2.0. vllm has attracted 26% as many forks as stars, trnrt 1%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (inference, llm, llm-serving), 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 | trnrt | |
|---|---|---|
| GitHub stars | ★ 97K | ★ 1.3K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-11 | 2026-11-11 |
| Forks | ⑂ 25K | ⑂ 12 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick vllm if
- You weight community size — 97K 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 trnrt if
- You want the trnrt 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 trnrt 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 trnrt
Quickstart · Benchmarks · Docs · Kernels · Blog post · runanywhere.ai TrnRT is an open inference engine for large language models on AWS Trainium. It serves an OpenAI compatible API from one trn2.48xlarge , runs decode as NKI megakernels (about one kernel per layer half), and keeps a prefix cache across device and host memory. GLM 5.3 Flash is the first supported model; more open models are on the way. How we built it, with the AgentX results: Serving GLM 5.3 Flash on one Trainium2 box with NKI layer megakernels. Highlights Quickstart You need Docker, a trn2.48xlarge to serve on, and any x86 64 host to compile…
read the full trnrt overview →
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Frequently asked questions
Is vllm or trnrt more popular?
vllm has 96,764 GitHub stars and trnrt has 1,317. vllm has the larger community by that measure.
Are vllm and trnrt free?
Both are open source. vllm is licensed under Apache-2.0 and trnrt under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and trnrt?
vllm is written in Python and trnrt 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 trnrt?
Choose vllm if you want the larger community (96,764 stars) or its Apache-2.0 licence terms. Choose trnrt if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.