head to head · open source
llama_index vs mlop
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. mlop has 394 stars, 12 forks, 3 open issues and last shipped 8 months ago. llama_index leads on adoption by 13,296% (52,779 vs 394 stars). llama_index is written in Python under MIT; mlop is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, mlop 3%. llama_index 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 | mlop | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 394 |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-10-26 | 2026-03-05 |
| Forks | ⑂ 8.5K | ⑂ 12 |
| 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 mlop if
- You want the mlop 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 mlop 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 mlop
mlop is a Machine Learning Operations (MLOps) framework. It provides self hostable superior experimental tracking capabilities and lifecycle management for training ML models. To get started, try out our introductory notebook or get an account with us today! 🎥 Demo mlop adopts a KISS philosophy that allows it to outperform all other tools in this category. Supporting high and stable data throughput should be THE top priority for efficient MLOps. mlop logger (bottom left) v. a conventional logger (bottom right) 🚀 Getting Started Try mlop on our platform in a notebook & start integrating in just 5 lines of…
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Frequently asked questions
Is llama_index or mlop more popular?
llama_index has 52,779 GitHub stars and mlop has 394. llama_index has the larger community by that measure.
Are llama_index and mlop free?
Both are open source. llama_index is licensed under MIT and mlop under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and mlop?
llama_index is written in Python and mlop 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 mlop?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose mlop if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.