head to head · open source
vllm vs pegainfer
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. pegainfer has 731 stars, 121 forks, 89 open issues and last shipped yesterday. vllm leads on adoption by 13,054% (96,158 vs 731 stars). vllm is written in Python under Apache-2.0; pegainfer is written in Rust under Apache-2.0. vllm has attracted 25% as many forks as stars, pegainfer 17%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 6 topic tags (cuda, deepseek, inference, kimi), 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 | pegainfer | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 731 |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Rust |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 24K | ⑂ 121 |
| 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 pegainfer if
- You want the pegainfer 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 pegainfer 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 pegainfer
Quickstart · Performance · Models · Architecture · API · Development PegaInfer serves LLMs through an OpenAI compatible API. Each model owns its scheduler, state, and kernels; serving and KV infrastructure are shared. No PyTorch or Python runtime. Quickstart Prebuilt binary · Qwen3 on Linux The Qwen3 only release bundles CUDA 13 and cuBLAS. It requires Linux x86 64 , an NVIDIA GPU with compute capability 8.x–12.x , driver 580+ , glibc 2.35+ , and OpenSSL 3 . Model weights are downloaded separately. Download Qwen3 4B into models/Qwen3 4B , then start the server: The server…
read the full pegainfer overview →
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Frequently asked questions
Is vllm or pegainfer more popular?
vllm has 96,158 GitHub stars and pegainfer has 731. vllm has the larger community by that measure.
Are vllm and pegainfer free?
Both are open source. vllm is licensed under Apache-2.0 and pegainfer under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and pegainfer?
vllm is written in Python and pegainfer 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 pegainfer?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose pegainfer if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.