head to head · open source
llama_index vs OpenLLM
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. OpenLLM has 12,578 stars, 848 forks, 20 open issues and last shipped yesterday. llama_index leads on adoption by 320% (52,779 vs 12,578 stars). llama_index is written in Python under MIT; OpenLLM is written in Python under Apache-2.0. llama_index has attracted 16% as many forks as stars, OpenLLM 7%. OpenLLM was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (fine-tuning, 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 | OpenLLM | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 13K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-10-26 | 2026-11-02 |
| Forks | ⑂ 8.5K | ⑂ 848 |
| 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 OpenLLM if
- You want the OpenLLM 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 OpenLLM 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 OpenLLM
🦾 OpenLLM: Self Hosting LLMs Made Easy OpenLLM allows developers to run any open source LLMs (Llama 3.3, Qwen2.5, Phi3 and more) or custom models as OpenAI compatible APIs with a single command. It features a built in chat UI, state of the art inference backends, and a simplified workflow for creating enterprise grade cloud deployment with Docker, Kubernetes, and BentoCloud. Understand the design philosophy of OpenLLM. Get Started Run the following commands to install OpenLLM and explore it interactively. Supported models OpenLLM supports a wide range of state of the art open source LLMs. You can also add a…
read the full OpenLLM overview →
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Frequently asked questions
Is llama_index or OpenLLM more popular?
llama_index has 52,779 GitHub stars and OpenLLM has 12,578. llama_index has the larger community by that measure.
Are llama_index and OpenLLM free?
Both are open source. llama_index is licensed under MIT and OpenLLM under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and OpenLLM?
llama_index is written in Python and OpenLLM 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 OpenLLM?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose OpenLLM if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.