head to head · open source
llama_index vs FastDeploy
llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. FastDeploy has 3,716 stars, 756 forks, 649 open issues and last shipped 23 days ago. llama_index leads on adoption by 1,305% (52,202 vs 3,716 stars). llama_index is written in Python under MIT; FastDeploy is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, FastDeploy 20%. llama_index 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
| llama_index | FastDeploy | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 3.7K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-17 | 2026-08-26 |
| Forks | ⑂ 8.2K | ⑂ 756 |
| 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 FastDeploy if
- You want the FastDeploy 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 FastDeploy 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 FastDeploy
FastDeploy is a Python inference and deployment toolkit for large language models and vision language models in the PaddlePaddle ecosystem. It serves models such as ERNIE, ERNIE 4.5, ERNIE 4.5 VL, DeepSeek V3, Qwen3 MoE, Qwen3 VL, and PaddleOCR VL 0.9B on accelerators.
read the full FastDeploy overview →
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Frequently asked questions
Is llama_index or FastDeploy more popular?
llama_index has 52,202 GitHub stars and FastDeploy has 3,716. llama_index has the larger community by that measure.
Are llama_index and FastDeploy free?
Both are open source. llama_index is licensed under MIT and FastDeploy under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and FastDeploy?
llama_index is written in Python and FastDeploy 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 FastDeploy?
Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose FastDeploy if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.