head to head · open source
llama_index vs FastDeploy
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. FastDeploy has 3,724 stars, 758 forks, 649 open issues and last shipped 1 months ago. llama_index leads on adoption by 1,317% (52,779 vs 3,724 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 | ★ 53K | ★ 3.7K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-10-26 | 2026-09-24 |
| Forks | ⑂ 8.5K | ⑂ 758 |
| 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 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 (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 FastDeploy
English 简体中文 安装指导 快速入门 支持模型列表 FastDeploy 飞桨大模型高效部署套件 最新活动 [2026 03] FastDeploy v2.5 全新发布! 新增Qwen3 VL与Qwen3 VL MoE模型部署支持，新增W4AFP8量化方法，增强强化学习训练支持能力，包含170+项Bug修复与性能优化，升级全部内容参阅 v2.5 ReleaseNote。 [2026 01] FastDeploy v2.4 : 新增 DeepSeek V3 与 Qwen3 MoE 模型的 PD 分离部署，增强MTP 投机解码能力，全面优化多硬件平台上的 MoE 推理与多模态前缀缓存性能，升级全部内容参阅 v2.4 ReleaseNote。 [2025 11] FastDeploy v2.3 : 新增ERNIE 4.5 VL 28B A3B Thinking与PaddleOCR VL 0.9B两大重磅模型在多硬件平台上的部署支持，进一步优化全方位推理性能，以及带来更多部署功能和易用性的提升，升级全部内容参阅v2.3 ReleaseNote。 [2025 09] FastDeploy v2.2 : HuggingFace生态模型兼容，性能进一步优化，更新增对baidu/ERNIE 21B A3B Thinking支持! [2025 08] FastDeploy v2.1 :全新的KV…
read the full FastDeploy overview →
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Frequently asked questions
Is llama_index or FastDeploy more popular?
llama_index has 52,779 GitHub stars and FastDeploy has 3,724. 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 (52,779 stars) or its MIT licence terms. Choose FastDeploy if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.