head to head · open source
vllm vs InferenceX
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. InferenceX has 1,964 stars, 351 forks, 254 open issues and last shipped yesterday. vllm leads on adoption by 4,796% (96,158 vs 1,964 stars). vllm is written in Python under Apache-2.0; InferenceX is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, InferenceX 18%. InferenceX was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 6 topic tags (amd, cuda, deepseek, 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 | InferenceX | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 2.0K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 24K | ⑂ 351 |
| 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 InferenceX if
- You want the InferenceX 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 InferenceX 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 InferenceX
InferenceX™, Open Source Continuous Inference Standard and Research Platform / 开源持续推理标准与研究平台 English 中文 Trusted by Operators of Trillion Dollar Token Factories such as OpenAI, Meta, Microsoft, Oracle, etc, & ML Community such as PyTorch Foundation, vLLM, SGLang, Tri Dao News [2026/08] 🔥 AgentX: World's First Fully Open Source Apache 2.0 Realistic 1Mil+ Long Context, Multi Turn Benchmark Live dashboard [2026/08] 🔥 GLM5.3: continuous agentic benchmarks live too dashboard [2026/07] 🔥 Kimi K3 2.8T: continuous benchmarks live since Day 0 [2026/06] 🔥 MiniMax M3: continuous benchmarks live since Day 0 dashboard…
read the full InferenceX overview →
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Frequently asked questions
Is vllm or InferenceX more popular?
vllm has 96,158 GitHub stars and InferenceX has 1,964. vllm has the larger community by that measure.
Are vllm and InferenceX free?
Both are open source. vllm is licensed under Apache-2.0 and InferenceX under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and InferenceX?
vllm is written in Python and InferenceX 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 InferenceX?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose InferenceX if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.