head to head · open source
vllm vs ServerlessLLM
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. ServerlessLLM has 718 stars, 80 forks, 45 open issues and last shipped 2 months ago. vllm leads on adoption by 13,292% (96,158 vs 718 stars). vllm is written in Python under Apache-2.0; ServerlessLLM is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, ServerlessLLM 11%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (cuda), 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.
← all 20902 open source comparisons
Side by side
| vllm | ServerlessLLM | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 718 |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-09-04 |
| Forks | ⑂ 24K | ⑂ 80 |
| 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 ServerlessLLM if
- You want the ServerlessLLM 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 ServerlessLLM 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 ServerlessLLM
ServerlessLLM Load models 10x faster. Serve 10 models with 1 GPU. Docs • Quick Start • OSDI'24 Paper ⚡ Performance ServerlessLLM loads models 6 10x faster than SafeTensors , enabling true serverless deployment where multiple models efficiently share GPU resources. Model Scenario SafeTensors ServerlessLLM Speedup Qwen/Qwen3 32B Random 20.6s 3.2s 6.40x Cached 12.5s 1.3s 9.95x DeepSeek R1 Distill Qwen 32B Random 19.1s 3.2s 5.93x Cached 10.2s 1.2s 8.58x Llama 3.1 8B Instruct Random 4.4s 0.7s 6.54x Results obtained on NVIDIA H100 GPUs with NVMe SSD. "Random" simulates serverless multi model serving; "Cached" shows…
read the full ServerlessLLM overview →
More in AI & Machine Learning
Related comparisons
More Machine Learning Infrastructure projects
Compare either of these against the rest of the Machine Learning Infrastructure field.
Frequently asked questions
Is vllm or ServerlessLLM more popular?
vllm has 96,158 GitHub stars and ServerlessLLM has 718. vllm has the larger community by that measure.
Are vllm and ServerlessLLM free?
Both are open source. vllm is licensed under Apache-2.0 and ServerlessLLM under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and ServerlessLLM?
vllm is written in Python and ServerlessLLM 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 ServerlessLLM?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose ServerlessLLM if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.