head to head · open source
vllm vs FastDeploy
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. FastDeploy has 3,724 stars, 758 forks, 649 open issues and last shipped 1 months ago. vllm leads on adoption by 2,482% (96,158 vs 3,724 stars). vllm is written in Python under Apache-2.0; FastDeploy is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, FastDeploy 20%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (inference, llm, llm-serving), 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 | FastDeploy | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 3.7K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-09-24 |
| Forks | ⑂ 24K | ⑂ 758 |
| 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 FastDeploy if
- You want the FastDeploy 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 FastDeploy 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 FastDeploy
English 简体中文 安装指导 快速入门 支持模型列表 FastDeploy 飞桨大模型高效部署套件 最新活动 [2026 03] FastDeploy v2.5 全新发布! 新增Qwen3 VL与Qwen3 VL MoE模型部署支持，新增W4AFP8量化方法，增强强化学习训练支持能力，包含170+项Bug修复与性能优化，升级全部内容参阅 v2.5 ReleaseNote。 [2026 01] FastDeploy v2.4 : 新增 DeepSeek V3 与 Qwen3 MoE 模型的 PD 分离部署，增强MTP 投机解码能力，全面优化多硬件平台上的 MoE 推理与多模态前缀缓存性能，升级全部内容参阅 v2.4 ReleaseNote。 [2025 11] FastDeploy v2.3 : 新增ERNIE 4.5 VL 28B A3B Thinking与PaddleOCR VL 0.9B两大重磅模型在多硬件平台上的部署支持，进一步优化全方位推理性能，以及带来更多部署功能和易用性的提升，升级全部内容参阅v2.3 ReleaseNote。 [2025 09] FastDeploy v2.2 : HuggingFace生态模型兼容，性能进一步优化，更新增对baidu/ERNIE 21B A3B Thinking支持! [2025 08] FastDeploy v2.1 :全新的KV…
read the full FastDeploy overview →
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Frequently asked questions
Is vllm or FastDeploy more popular?
vllm has 96,158 GitHub stars and FastDeploy has 3,724. vllm has the larger community by that measure.
Are vllm and FastDeploy free?
Both are open source. vllm is licensed under Apache-2.0 and FastDeploy under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and FastDeploy?
vllm is written in Python and FastDeploy 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 FastDeploy?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose FastDeploy if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.