head to head · open source
vllm vs ollaya
vllm has 95,262 GitHub stars, 23,866 forks, 7,953 open issues and last shipped yesterday. ollaya has 1,388 stars, 83 forks, 4 open issues and last shipped yesterday. vllm leads on adoption by 6,763% (95,262 vs 1,388 stars). vllm is written in Python under Apache-2.0; ollaya is written in Rust under Apache-2.0. vllm has attracted 25% as many forks as stars, ollaya 6%. vllm 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
| vllm | ollaya | |
|---|---|---|
| GitHub stars | ★ 95K | ★ 1.4K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Rust |
| Last push | 2026-10-24 | 2026-10-24 |
| Forks | ⑂ 24K | ⑂ 83 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick vllm if
- You weight community size — 95K 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 ollaya if
- You want the ollaya feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Rust
- You evaluated both and ollaya 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 ollaya
ollaya Run open decision models locally, the way Ollama runs LLMs. System 1 for AI agents: fast, typed, calibrated decisions for routing, guardrails, triage and tool approval. Website · Models · Bench · Docs · Releases · Hugging Face Created and maintained by Mert Cobanov ( @mertcobanov ). A decision model reads a state (a message, an email, a ticket, any JSON) plus typed questions ( choice , score , noul ) and returns calibrated probabilities in a single forward pass, in milliseconds. It never generates text. Ollaya pulls these models by name and serves them from a local daemon behind a self hosted, Jev…
read the full ollaya overview →
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Frequently asked questions
Is vllm or ollaya more popular?
vllm has 95,262 GitHub stars and ollaya has 1,388. vllm has the larger community by that measure.
Are vllm and ollaya free?
Both are open source. vllm is licensed under Apache-2.0 and ollaya under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and ollaya?
vllm is written in Python and ollaya in Rust. 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 ollaya?
Choose vllm if you want the larger community (95,262 stars) or its Apache-2.0 licence terms. Choose ollaya if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.