head to head · open source
faiss vs deep-searcher
faiss has 41,256 GitHub stars, 4,586 forks, 327 open issues and last shipped 2 days ago. deep-searcher has 8,378 stars, 816 forks, 55 open issues and last shipped 1 months ago. faiss leads on adoption by 392% (41,256 vs 8,378 stars). faiss is written in C++ under MIT; deep-searcher is written in Python under Apache-2.0. faiss has attracted 11% as many forks as stars, deep-searcher 10%. faiss 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
| faiss | deep-searcher | |
|---|---|---|
| GitHub stars | ★ 41K | ★ 8.4K |
| License | MIT | Apache-2.0 |
| Written in | C++ | Python |
| Last push | 2026-11-03 | 2026-09-22 |
| Forks | ⑂ 4.6K | ⑂ 816 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick faiss if
- You weight community size — 41K stars and counting
- You want the MIT license terms
- Your stack matches C++
- 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 faiss
Faiss Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed primarily at Meta's Fundamental AI Research group. News See CHANGELOG.md for detailed information about latest features. Introduction Faiss contains several methods for similarity search. It assumes that…
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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 faiss or deep-searcher more popular?
faiss has 41,256 GitHub stars and deep-searcher has 8,378. faiss has the larger community by that measure.
Are faiss and deep-searcher free?
Both are open source. faiss is licensed under MIT and deep-searcher under Apache-2.0. Neither carries a licence fee.
What is the difference between faiss and deep-searcher?
faiss is written in C++ 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, faiss or deep-searcher?
Choose faiss if you want the larger community (41,256 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.