head to head · open source
LocalAI vs examples
LocalAI has 50,187 GitHub stars, 4,574 forks, 201 open issues and last shipped yesterday. examples has 3,050 stars, 1,062 forks, 64 open issues and last shipped 13 days ago. LocalAI leads on adoption by 1,545% (50,187 vs 3,050 stars). LocalAI is written in Go under MIT; examples is written in Jupyter Notebook under MIT. LocalAI has attracted 9% as many forks as stars, examples 35%. LocalAI was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (ai, 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
| LocalAI | examples | |
|---|---|---|
| GitHub stars | ★ 50K | ★ 3.0K |
| License | MIT | MIT |
| Written in | Go | Jupyter Notebook |
| Last push | 2026-11-04 | 2026-10-23 |
| Forks | ⑂ 4.6K | ⑂ 1.1K |
| 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 examples if
- You want the examples feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Jupyter Notebook
- You evaluated both and examples 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 examples
Pinecone Examples This repository is a collection of sample applications and Jupyter Notebooks that you can run, download, study and modify in order to get hands on with Pinecone vector databases and common AI patterns, tools and algorithms. Two kinds of examples This repo contains: 1. Production ready examples in ./docs that receive regular review and support from the Pinecone engineering team 2. Examples optimized for learning and exploration of AI techniques in ./learn and patterns for building different kinds of applications, created and maintained by the Pinecone Developer Advocacy team. We appreciate your…
read the full examples overview →
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Frequently asked questions
Is LocalAI or examples more popular?
LocalAI has 50,187 GitHub stars and examples has 3,050. LocalAI has the larger community by that measure.
Are LocalAI and examples free?
Both are open source. LocalAI is licensed under MIT and examples under MIT. Neither carries a licence fee.
What is the difference between LocalAI and examples?
LocalAI is written in Go and examples in Jupyter Notebook. 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 examples?
Choose LocalAI if you want the larger community (50,187 stars) or its MIT licence terms. Choose examples if its feature set, stack or MIT licence fits better. Both are self-hostable.