head to head · open source
llama_index vs ome
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. ome has 523 stars, 106 forks, 134 open issues and last shipped yesterday. llama_index leads on adoption by 9,992% (52,779 vs 523 stars). llama_index is written in Python under MIT; ome is written in Go under Apache-2.0. llama_index has attracted 16% as many forks as stars, ome 20%. ome 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 | ome | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 523 |
| License | MIT | Apache-2.0 |
| Written in | Python | Go |
| Last push | 2026-10-26 | 2026-11-02 |
| Forks | ⑂ 8.5K | ⑂ 106 |
| 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 ome if
- You want the ome feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Go
- You evaluated both and ome 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 ome
OME (Open Model Engine) — Kubernetes Operator for LLM Serving What is OME? OME (Open Model Engine) is a Kubernetes operator for enterprise grade management and serving of Large Language Models (LLMs). It optimizes the deployment and operation of LLMs by automating model management, intelligent runtime selection, efficient resource utilization, and sophisticated deployment patterns. Read the documentation to learn more about OME capabilities and features. Features Overview Model Management: Models are first class citizen custom resources in OME. Sophisticated model parsing extracts architecture, parameter count…
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Frequently asked questions
Is llama_index or ome more popular?
llama_index has 52,779 GitHub stars and ome has 523. llama_index has the larger community by that measure.
Are llama_index and ome free?
Both are open source. llama_index is licensed under MIT and ome under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and ome?
llama_index is written in Python and ome in Go. 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 ome?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose ome if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.