head to head · open source
vllm vs gpu-hot
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. gpu-hot has 1,642 stars, 86 forks, 8 open issues and last shipped 2 months ago. vllm leads on adoption by 5,756% (96,158 vs 1,642 stars). vllm is written in Python under Apache-2.0; gpu-hot is written in JavaScript under MIT. vllm has attracted 25% as many forks as stars, gpu-hot 5%. vllm was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (cuda, 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 | gpu-hot | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 1.6K |
| License | Apache-2.0 | MIT |
| Written in | Python | JavaScript |
| Last push | 2026-11-02 | 2026-08-25 |
| Forks | ⑂ 24K | ⑂ 86 |
| 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 gpu-hot if
- You want the gpu-hot feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches JavaScript
- You evaluated both and gpu-hot 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 gpu-hot
GPU Hot Real time NVIDIA GPU monitoring dashboard. Lightweight, web based, and self hosted. Usage Monitor a single machine or an entire cluster with the same Docker image. Single machine: Multiple machines: Open Older GPUs: Add e NVIDIA SMI=true if metrics don't appear. Process monitoring: Add init pid=host to see process names. Note: This allows the container to access host process information. From source: Requirements: Docker + NVIDIA Container Toolkit Features Real time metrics (sub second) Automatic multi GPU detection Process monitoring (PID, memory usage) Historical charts (utilization, temperature…
read the full gpu-hot overview →
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Frequently asked questions
Is vllm or gpu-hot more popular?
vllm has 96,158 GitHub stars and gpu-hot has 1,642. vllm has the larger community by that measure.
Are vllm and gpu-hot free?
Both are open source. vllm is licensed under Apache-2.0 and gpu-hot under MIT. Neither carries a licence fee.
What is the difference between vllm and gpu-hot?
vllm is written in Python and gpu-hot in JavaScript. 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 gpu-hot?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose gpu-hot if its feature set, stack or MIT licence fits better. Both are self-hostable.