head to head · open source
serviette vs ServerlessLLM
serviette has 58,732 GitHub stars, 1,547 forks, 8 open issues and last shipped yesterday. ServerlessLLM has 718 stars, 80 forks, 45 open issues and last shipped 2 months ago. serviette leads on adoption by 8,080% (58,732 vs 718 stars). serviette is written in Python under MIT; ServerlessLLM is written in Python under Apache-2.0. serviette has attracted 3% as many forks as stars, ServerlessLLM 11%. serviette was the more recently maintained of the two, and both are self-hostable with no licence fee.
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 | ServerlessLLM | |
|---|---|---|
| GitHub stars | ★ 59K | ★ 718 |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-09-04 |
| Forks | ⑂ 1.5K | ⑂ 80 |
| 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 ServerlessLLM if
- You want the ServerlessLLM 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 ServerlessLLM 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 ServerlessLLM
ServerlessLLM Load models 10x faster. Serve 10 models with 1 GPU. Docs • Quick Start • OSDI'24 Paper ⚡ Performance ServerlessLLM loads models 6 10x faster than SafeTensors , enabling true serverless deployment where multiple models efficiently share GPU resources. Model Scenario SafeTensors ServerlessLLM Speedup Qwen/Qwen3 32B Random 20.6s 3.2s 6.40x Cached 12.5s 1.3s 9.95x DeepSeek R1 Distill Qwen 32B Random 19.1s 3.2s 5.93x Cached 10.2s 1.2s 8.58x Llama 3.1 8B Instruct Random 4.4s 0.7s 6.54x Results obtained on NVIDIA H100 GPUs with NVMe SSD. "Random" simulates serverless multi model serving; "Cached" shows…
read the full ServerlessLLM overview →
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Frequently asked questions
Is serviette or ServerlessLLM more popular?
serviette has 58,732 GitHub stars and ServerlessLLM has 718. serviette has the larger community by that measure.
Are serviette and ServerlessLLM free?
Both are open source. serviette is licensed under MIT and ServerlessLLM under Apache-2.0. Neither carries a licence fee.
What is the difference between serviette and ServerlessLLM?
serviette is written in Python and ServerlessLLM 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 ServerlessLLM?
Choose serviette if you want the larger community (58,732 stars) or its MIT licence terms. Choose ServerlessLLM if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.