head to head · open source
vllm vs openlake
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. openlake has 2,645 stars, 420 forks, 138 open issues and last shipped 2 days ago. vllm leads on adoption by 3,535% (96,158 vs 2,645 stars). vllm is written in Python under Apache-2.0; openlake is written in Rust under Apache-2.0. vllm has attracted 25% as many forks as stars, openlake 16%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (blackwell, gpt, llm), 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 | openlake | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 2.6K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Rust |
| Last push | 2026-11-02 | 2026-11-01 |
| Forks | ⑂ 24K | ⑂ 420 |
| 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 openlake if
- You want the openlake feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Rust
- You evaluated both and openlake 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 openlake
Fast, easy and efficient storage for LLM Inference and Training 🔥 Distributed storage for GPU workloads. Built on Rust on io uring , OpenLake is a state of the art storage engine delivering million+ iops within 1ms. Updates [2026/09] 🔥 OpenLake tops the MLPerf Storage v3.0 2026 object checkpointing, leading NVIDIA and Nebius (blog). [2026/08] ExANS : a lossless GPU codec for BF16 KV cache: 1.51× cost savings, now available in OpenLake v0.8 (blog). [2026/07] Breaking the KV Wall: managing 100 TB of KV cache and 8× inference throughput with deferred materialization (blog). Older updates [2026/07] Introducing…
read the full openlake overview →
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Frequently asked questions
Is vllm or openlake more popular?
vllm has 96,158 GitHub stars and openlake has 2,645. vllm has the larger community by that measure.
Are vllm and openlake free?
Both are open source. vllm is licensed under Apache-2.0 and openlake under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and openlake?
vllm is written in Python and openlake in Rust. 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 openlake?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose openlake if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.