head to head · open source
llama_index vs MineContext
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. MineContext has 5,541 stars, 413 forks, 121 open issues and last shipped 6 months ago. llama_index leads on adoption by 853% (52,779 vs 5,541 stars). llama_index is written in Python under MIT; MineContext is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, MineContext 7%. 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 (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 | MineContext | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 5.5K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-10-26 | 2026-05-07 |
| Forks | ⑂ 8.5K | ⑂ 413 |
| 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 MineContext if
- You want the MineContext 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 MineContext 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 MineContext
MineContext: Create with Context, Clarity from Chaos An open source, proactive context aware AI partner, dedicated to bringing clarity and efficiency to your work, study and creation. 中文 / English Community Best Practice · Report Issues · Feedback [![][release shield]][release link] [![][github stars shield]][github stars link] [![][github issues shield]][github issues shield link] [![][github contributors shield]][github contributors link] [![][license shield]][license shield link] [![][last commit shield]][last commit shield link] [![][wechat shield]][wechat shield link] 👋 Join our WeChat / Lark / Red Note…
read the full MineContext 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 MineContext more popular?
llama_index has 52,779 GitHub stars and MineContext has 5,541. llama_index has the larger community by that measure.
Are llama_index and MineContext free?
Both are open source. llama_index is licensed under MIT and MineContext under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and MineContext?
llama_index is written in Python and MineContext 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 MineContext?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose MineContext if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.