head to head · open source
LocalAI vs gpu-hot
LocalAI has 50,187 GitHub stars, 4,574 forks, 201 open issues and last shipped today. gpu-hot has 1,643 stars, 86 forks, 8 open issues and last shipped 2 months ago. LocalAI leads on adoption by 2,955% (50,187 vs 1,643 stars). LocalAI is written in Go under MIT; gpu-hot is written in JavaScript under MIT. LocalAI has attracted 9% as many forks as stars, gpu-hot 5%. LocalAI was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (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.
← all 20902 open source comparisons
Side by side
| LocalAI | gpu-hot | |
|---|---|---|
| GitHub stars | ★ 50K | ★ 1.6K |
| License | MIT | MIT |
| Written in | Go | JavaScript |
| Last push | 2026-11-04 | 2026-08-25 |
| Forks | ⑂ 4.6K | ⑂ 86 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick LocalAI if
- You weight community size — 50K stars and counting
- You want the MIT license terms
- Your stack matches Go
- 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 LocalAI
Deutsch Español français 日本語 한국어 Português Русский 中文 LocalAI is the open source AI engine. Run any model LLMs, vision, voice, image, video on any hardware. No GPU required. A small core, not a bundle. Each backend wraps a best in class engine (llama.cpp, vLLM, whisper.cpp, stable diffusion, MLX...) in its own image, pulled only when a model needs it. You install nothing you don't use. Composable by design : backends are separate and pulled on demand, so you install only what your model needs Open and extensible : load any model, or build your own backend in any language against an open interface Drop in API…
read the full LocalAI overview →
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 →
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 LocalAI or gpu-hot more popular?
LocalAI has 50,187 GitHub stars and gpu-hot has 1,643. LocalAI has the larger community by that measure.
Are LocalAI and gpu-hot free?
Both are open source. LocalAI is licensed under MIT and gpu-hot under MIT. Neither carries a licence fee.
What is the difference between LocalAI and gpu-hot?
LocalAI is written in Go 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, LocalAI or gpu-hot?
Choose LocalAI if you want the larger community (50,187 stars) or its MIT licence terms. Choose gpu-hot if its feature set, stack or MIT licence fits better. Both are self-hostable.