head to head · open source

llama_index vs OpenLIT

llama_index has 52,202 GitHub stars, 8,162 forks, 770 open issues and last shipped yesterday. OpenLIT has 2,770 stars, 388 forks, 60 open issues and last shipped yesterday. llama_index leads on adoption by 1,785% (52,202 vs 2,770 stars). llama_index is written in Python under MIT; OpenLIT is written in TypeScript under Apache-2.0. llama_index has attracted 16% as many forks as stars, OpenLIT 14%. 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.

llama_index ★ 52K OpenLIT ★ 2.8K category AI & Machine Learning

← all 8884 open source comparisons

Side by side

llama_index OpenLIT
GitHub stars ★ 52K ★ 2.8K
License MIT Apache-2.0
Written in Python TypeScript
Last push 2026-09-17 2026-09-17
Forks ⑂ 8.2K ⑂ 388
Self-hosting Yes Yes
Data ownership Your server Your server

pick llama_index if

  • You weight community size — 52K stars and counting
  • You want the MIT license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full llama_index profile →

pick OpenLIT if

  • You want the OpenLIT feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches TypeScript
  • You evaluated both and OpenLIT fits your workflow better

full OpenLIT profile →

About llama_index

LlamaIndex is an MIT licensed, open source Python framework for building agentic applications — retrieval augmented generation systems, agents and multi agent workflows — on top of private documents and data, and it is aimed at AI engineers and teams who need to connect large language models to their own sources of context.

read the full llama_index overview →

About OpenLIT

OpenLIT is an open source, OpenTelemetry native observability and evaluation platform for AI applications, AI agents and coding agents, built for engineers who run LLM backed systems and need to see what those systems actually did.

read the full OpenLIT overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

Related comparisons

ollama vs llama-index ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs localai llama-cpp vs vllm ollama vs pageindex ollama vs langfuse openclaw vs hermes-agent openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm openclaw vs cherry-studio openclaw vs nanobot openclaw vs jan openclaw vs librechat dify vs langchain dify vs ponytail langchain vs ponytail dify vs graphify langchain vs graphify ponytail vs graphify dify vs claude-mem dify vs ragflow

More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

llama_index vs Ollama llama_index vs llama.cpp llama_index vs vllm llama_index vs GPT4All llama_index vs LocalAI llama_index vs PageIndex llama_index vs Langfuse llama_index vs cognee llama_index vs taipy llama_index vs dagster llama_index vs zvec llama_index vs langchain4j

Frequently asked questions

Is llama_index or OpenLIT more popular?

llama_index has 52,202 GitHub stars and OpenLIT has 2,770. llama_index has the larger community by that measure.

Are llama_index and OpenLIT free?

Both are open source. llama_index is licensed under MIT and OpenLIT under Apache-2.0. Neither carries a licence fee.

What is the difference between llama_index and OpenLIT ?

llama_index is written in Python and OpenLIT in TypeScript. 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 OpenLIT ?

Choose llama_index if you want the larger community (52,202 stars) or its MIT licence terms. Choose OpenLIT if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.