head to head · open source
llama_index vs txtai
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. txtai has 13,062 stars, 960 forks, 9 open issues and last shipped 2 days ago. llama_index leads on adoption by 304% (52,779 vs 13,062 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%. txtai 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.
← all 20902 open source comparisons
Side by side
| llama_index | txtai | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 13K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-10-26 | 2026-11-01 |
| Forks | ⑂ 8.5K | ⑂ 960 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 53K 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 (OSS Framework) 🦙 [!NOTE] The current focus of LlamaIndex is to build the best AI powered engine for document parsing and extraction. LlamaParse is our enterprise platform for agentic OCR, parsing, extraction, indexing and more. LiteParse represents our efforts to build the best free, fast, cheap text parser in the market. ParseBench and ExtractBench represent our commitment towards open benchmarking for parsing and extraction. The company itself has undergone an evolution since when this OSS framework first launched 3 years ago in 2023. Since the early days, the framework has consisted of a…
read the full llama_index overview →
About txtai
All in one AI framework txtai is an all in one AI framework for semantic search, LLM orchestration and language model workflows. The key component of txtai is an embeddings database, which is a union of vector indexes (sparse and dense), graph networks and relational databases. This foundation enables vector search and/or serves as a powerful knowledge source for large language model (LLM) applications. Build autonomous agents, retrieval augmented generation (RAG) processes, multi model workflows and more. Summary of txtai features: 🔎 Vector search with SQL, object storage, topic modeling, graph analysis and…
read the full txtai 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 llama_index or txtai more popular?
llama_index has 52,779 GitHub stars and txtai has 13,062. 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 (52,779 stars) or its MIT licence terms. Choose txtai if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.