head to head · open source
vllm vs sglang-omni
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. sglang-omni has 1,674 stars, 681 forks, 644 open issues and last shipped yesterday. vllm leads on adoption by 5,644% (96,158 vs 1,674 stars). vllm is written in Python under Apache-2.0; sglang-omni is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, sglang-omni 41%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (cuda, inference), 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 | sglang-omni | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 1.7K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 24K | ⑂ 681 |
| 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 sglang-omni if
- You want the sglang-omni 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 sglang-omni 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 sglang-omni
Blog Documentation Quick Start Cookbook SGLang Join Slack ⭐ Star SGLang Omni to help more builders discover open infrastructure for multimodal and speech serving! News [2026/09] 🐧 Day 0 support for AuK and AuK Flash: text + voice instructions → 24 kHz speech on /v1/audio/speech , audio + editing instructions → edited speech on /generate . \[Cookbook\] [2026/09] 🚀 SGLang Omni v0.1.5 is on PyPI. Install with uv pip install prerelease=allow "sglang omni==0.1.5" . \[Installation\] [2026/08] 🎵 Day 0 support for MiniMax Music 3: lyrics + caption → 32 kHz stereo song on /v1/audio/speech . \[Cookbook\] [2026/08] 🚀…
read the full sglang-omni overview →
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Frequently asked questions
Is vllm or sglang-omni more popular?
vllm has 96,158 GitHub stars and sglang-omni has 1,674. vllm has the larger community by that measure.
Are vllm and sglang-omni free?
Both are open source. vllm is licensed under Apache-2.0 and sglang-omni under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and sglang-omni?
vllm is written in Python and sglang-omni 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 sglang-omni?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose sglang-omni if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.