head to head · open source
llama_index vs Agenta
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. Agenta has 4,881 stars, 722 forks, 309 open issues and last shipped yesterday. llama_index leads on adoption by 981% (52,779 vs 4,881 stars). llama_index is written in Python under MIT; Agenta is written in TypeScript under a custom or non-standard licence. llama_index has attracted 16% as many forks as stars, Agenta 15%. Agenta 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
| llama_index | Agenta | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 4.9K |
| License | MIT | Custom / other |
| Written in | Python | TypeScript |
| Last push | 2026-10-26 | 2026-11-02 |
| Forks | ⑂ 8.5K | ⑂ 722 |
| 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 Agenta if
- You want the Agenta feature set and don't need the biggest community
- You prefer the Custom / other license terms
- Your stack matches TypeScript
- You evaluated both and Agenta 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 Agenta
The open source workspace for building and running agents Build agents that automate your work by chatting with them. Share them with your team , connect them to the apps you use, and run them in the background . Documentation • Website • Agenta Cloud What is Agenta? Agenta is an open source workspace where you build specialized agents that automate and augment your work. You build agents by chatting with them. You describe the work, connect the apps they need, and improve them through feedback. You can work with your agents directly in chat and share them with your team. For recurring work, you can…
read the full Agenta overview →
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Frequently asked questions
Is llama_index or Agenta more popular?
llama_index has 52,779 GitHub stars and Agenta has 4,881. llama_index has the larger community by that measure.
Are llama_index and Agenta free?
Both are open source. llama_index is licensed under MIT, and Agenta has no licence declared in this registry. Both are free to self-host.
What is the difference between llama_index and Agenta?
llama_index is written in Python and Agenta in TypeScript. 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 Agenta?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose Agenta if its feature set, stack or Custom / other licence fits better. Both are self-hostable.