head to head · open source
vllm vs mlop
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. mlop has 394 stars, 12 forks, 3 open issues and last shipped 8 months ago. vllm leads on adoption by 24,306% (96,158 vs 394 stars). vllm is written in Python under Apache-2.0; mlop is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, mlop 3%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee.
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 | mlop | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 394 |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-03-05 |
| Forks | ⑂ 24K | ⑂ 12 |
| 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 mlop if
- You want the mlop 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 mlop 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 mlop
mlop is a Machine Learning Operations (MLOps) framework. It provides self hostable superior experimental tracking capabilities and lifecycle management for training ML models. To get started, try out our introductory notebook or get an account with us today! 🎥 Demo mlop adopts a KISS philosophy that allows it to outperform all other tools in this category. Supporting high and stable data throughput should be THE top priority for efficient MLOps. mlop logger (bottom left) v. a conventional logger (bottom right) 🚀 Getting Started Try mlop on our platform in a notebook & start integrating in just 5 lines of…
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Frequently asked questions
Is vllm or mlop more popular?
vllm has 96,158 GitHub stars and mlop has 394. vllm has the larger community by that measure.
Are vllm and mlop free?
Both are open source. vllm is licensed under Apache-2.0 and mlop under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and mlop?
vllm is written in Python and mlop 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 mlop?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose mlop if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.