head to head · open source
llama_index vs txtai
llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. txtai has 12,956 stars, 891 forks, 9 open issues and last shipped 3 days ago. llama_index leads on adoption by 303% (52,202 vs 12,956 stars). llama_index is written in Python under MIT; txtai is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, txtai 7%. llama_index was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (agents, llm, rag), 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
| llama_index | txtai | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 13K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-17 | 2026-09-15 |
| Forks | ⑂ 8.2K | ⑂ 891 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 52K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick txtai if
- You want the txtai 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 txtai fits your workflow better
About llama_index
LlamaIndex is an MIT licensed, open source Python framework for building agentic applications — retrieval augmented generation systems, agents and multi agent workflows — on top of private documents and data, and it is aimed at AI engineers and teams who need to connect large language models to their own sources of context.
read the full llama_index overview →
About txtai
txtai is an all in one AI framework for semantic search, LLM orchestration and language model workflows, written in Python and released under the Apache 2.0 license. It lives in the Python machine learning ecosystem and is built on Hugging Face Transformers, Sentence Transformers and FastAPI. The core component is an embeddings database, which is a union of vector indexes (both sparse and dense), graph networks and relational databases. That foundation enables vector search and also serves as a knowledge source for large language model applications.
read the full txtai overview →
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Frequently asked questions
Is llama_index or txtai more popular?
llama_index has 52,202 GitHub stars and txtai has 12,956. llama_index has the larger community by that measure.
Are llama_index and txtai free?
Both are open source. llama_index is licensed under MIT and txtai under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and txtai?
llama_index is written in Python and txtai 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, llama_index or txtai?
Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose txtai if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.