head to head · open source
serviette vs trnrt
serviette has 58,708 GitHub stars, 1,549 forks, 8 open issues and last shipped 2 days ago. trnrt has 1,317 stars, 12 forks, 10 open issues and last shipped yesterday. serviette leads on adoption by 4,358% (58,708 vs 1,317 stars). serviette is written in Python under MIT; trnrt is written in Python under Apache-2.0. serviette has attracted 3% as many forks as stars, trnrt 1%. trnrt 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
| serviette | trnrt | |
|---|---|---|
| GitHub stars | ★ 59K | ★ 1.3K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-10 | 2026-11-11 |
| Forks | ⑂ 1.5K | ⑂ 12 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick serviette if
- You weight community size — 59K stars and counting
- You want the MIT 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 serviette
serviette Looking for llm app templates? All templates, cookbooks and examples are still available in full in the Pathway repository under examples/llm app . A no code, always up to date RAG server for any vector database — built on the Pathway Live Data Framework. Point serviette at a folder of documents, pick a vector database and an embedder in one YAML file, and run two commands: you get a chat and a REST API that answer from those documents and cite their sources. From then on, any change to the documents — an edit, a new file, a deletion — is reflected in the answers within seconds. serviette runs on…
read the full serviette overview →
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 serviette or trnrt more popular?
serviette has 58,708 GitHub stars and trnrt has 1,317. serviette has the larger community by that measure.
Are serviette and trnrt free?
Both are open source. serviette is licensed under MIT and trnrt under Apache-2.0. Neither carries a licence fee.
What is the difference between serviette and trnrt?
serviette 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, serviette or trnrt?
Choose serviette if you want the larger community (58,708 stars) or its MIT licence terms. Choose trnrt if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.