head to head · open source
vllm vs Compartment
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. Compartment has 580 stars, 8 forks, 1 open issues and last shipped 14 days ago. vllm leads on adoption by 16,479% (96,158 vs 580 stars). vllm is written in Python under Apache-2.0; Compartment is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, Compartment 1%. 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 | Compartment | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 580 |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-10-20 |
| Forks | ⑂ 24K | ⑂ 8 |
| 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 Compartment if
- You want the Compartment 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 Compartment 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 Compartment
Compartment Encrypted, fully offline memory for AI agents. One vault on your own computer, read and written by Claude Code, Claude Desktop, Hermes Agent, OpenClaw, Cursor, Codex and any other MCP client. No API key, no account, no network, no telemetry. One click install (after pip install compartment && compartment init ): Claude Code, Claude Desktop, Hermes Agent and OpenClaw are wired by one command instead: compartment integrate claude , hermes or openclaw . Compartment is persistent memory for AI agents, stored on your own computer. What an agent learns in one session is available in every later session, in…
read the full Compartment overview →
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Frequently asked questions
Is vllm or Compartment more popular?
vllm has 96,158 GitHub stars and Compartment has 580. vllm has the larger community by that measure.
Are vllm and Compartment free?
Both are open source. vllm is licensed under Apache-2.0 and Compartment under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and Compartment?
vllm is written in Python and Compartment 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 Compartment?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose Compartment if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.