LangChain vs LlamaIndex: Which Is More Actively Maintained? Live GitHub Data

LangChain and LlamaIndex are two widely used Python frameworks for building retrieval-augmented generation (RAG) and other LLM applications. This page compares how actively each one is maintained, using live data from GitHub.

GitHub data checked 7 minutes ago.

Side by side

MeasureLangChainLlamaIndex
StatusActiveSlowing down
Commits, last 91 days553105
Same 91 days a year earlier797357
Change vs last year−31%−71%
Last commit16 Oct 202614 Oct 2026
GitHub stars148,04052,554
Stars gained, daily snapshots+111 in 2 days+29 in 2 days
LicenceMITMIT
Managed cloudNot checkedNot checked
Visitor rating—0 of 3 ratings needed—0 of 3 ratings needed

What the numbers say

In the last 91 days, LangChain’s default branch received 553 commits and LlamaIndex’s received 105. That is about 5.3 times as many for LangChain, though projects that squash each pull request into one commit show fewer commits for the same work, so treat the gap as a rough signal. Against the same 91 days a year earlier, LangChain is at −31% and LlamaIndex at −71%. The index labels LangChain “active” and LlamaIndex “slowing down”. LangChain has 148,040 GitHub stars and LlamaIndex has 52,554; stars show how many people bookmarked a project, not how many use it.

What this comparison does not tell you

These are maintenance signals only. They do not measure speed, output quality, features, documentation or how easy either tool is to run, and we have not benchmarked either tool for this page. A quiet repository can still be a good fit for a stable job, and a busy one can still break between releases. Use the numbers to decide what to check next, not which tool is better.

Each tool’s full record

How this is measured: commits on each repository’s default branch counted through the GitHub API, the last 91 days against the same 91 days a year earlier; stars, licence and archived flag from the repository; README checked daily for maintenance notices. Visitor ratings come from visitors to each tool’s page, not from EvalAITools.