head to head · open source
LocalAI vs deep-searcher
LocalAI has 50,187 GitHub stars, 4,574 forks, 201 open issues and last shipped yesterday. deep-searcher has 8,378 stars, 816 forks, 55 open issues and last shipped 1 months ago. LocalAI leads on adoption by 499% (50,187 vs 8,378 stars). LocalAI is written in Go under MIT; deep-searcher is written in Python under Apache-2.0. LocalAI has attracted 9% as many forks as stars, deep-searcher 10%. 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.
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Side by side
| LocalAI | deep-searcher | |
|---|---|---|
| GitHub stars | ★ 50K | ★ 8.4K |
| License | MIT | Apache-2.0 |
| Written in | Go | Python |
| Last push | 2026-11-04 | 2026-09-22 |
| Forks | ⑂ 4.6K | ⑂ 816 |
| 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 deep-searcher if
- You want the deep-searcher 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 deep-searcher 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 deep-searcher
DeepSearcher combines cutting edge LLMs (OpenAI o3, Qwen3, DeepSeek, Grok 4, Claude 4 Sonnet, Llama 4, QwQ, etc.) and Vector Databases (Milvus, Zilliz Cloud etc.) to perform search, evaluation, and reasoning based on private data, providing highly accurate answer and comprehensive report. This project is suitable for enterprise knowledge management, intelligent Q&A systems, and information retrieval scenarios. 🚀 Features Private Data Search : Maximizes the utilization of enterprise internal data while ensuring data security. When necessary, it can integrate online content for more accurate answers. Vector…
read the full deep-searcher overview →
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Frequently asked questions
Is LocalAI or deep-searcher more popular?
LocalAI has 50,187 GitHub stars and deep-searcher has 8,378. LocalAI has the larger community by that measure.
Are LocalAI and deep-searcher free?
Both are open source. LocalAI is licensed under MIT and deep-searcher under Apache-2.0. Neither carries a licence fee.
What is the difference between LocalAI and deep-searcher?
LocalAI is written in Go and deep-searcher 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, LocalAI or deep-searcher?
Choose LocalAI if you want the larger community (50,187 stars) or its MIT licence terms. Choose deep-searcher if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.