Open-Source AI · LLM / RAG framework

LangChain vs LlamaIndex

LangChain vs LlamaIndex compared for 2026 — features, license, ease of use, performance and which one to choose. Compose chains, tools and agents vs The data framework for RAG.

Updated regularly · curated by olud.ai

Choose LangChain for developers building tool-using LLM apps. Choose LlamaIndex for developers building data-heavy RAG apps.

LangChain vs LlamaIndex at a glance

SpecLangChainLlamaIndex
CategoryLLM / RAG frameworkLLM / RAG framework
TypeLLM app frameworkData / RAG framework
LicenseMITMIT
Runs locallyCloud-optionalCloud-optional
Primary languagePython / JSPython
Ease of useIntermediateIntermediate
Best fordevelopers building tool-using LLM appsdevelopers building data-heavy RAG apps
GitHub stars142.3k51k

Feature comparison

FeatureLangChainLlamaIndex
Python✓✓
JavaScript / TS✓✓
Agents✓✓
RAG✓✓
Streaming✓✓
Many integrations✓✓

How LangChain and LlamaIndex score

🤝 Too close to call — LangChain and LlamaIndex land within a hair (4.4 vs 4.3 / 5). Pick on fit, not on score.
CriterionLangChainLlamaIndex
Popularity5.04.5
Maintenance5.05.0
Ease of use3.53.5
Privacy3.53.5
License freedom5.05.0

Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.

What each one is

LangChain

LLM app framework · MIT

LangChain is a framework for building LLM applications by composing prompts, models, tools, memory and agents, with a vast ecosystem of integrations.

  • Huge ecosystem of integrations
  • Building blocks for chains, tools and agents
  • Python and JavaScript support
See the LangChain page →

LlamaIndex

Data / RAG framework · MIT

LlamaIndex is a data framework focused on connecting LLMs to your data, with best-in-class ingestion, indexing and retrieval for RAG applications.

  • Best-in-class ingestion and indexing for RAG
  • Many data connectors and retrievers
  • Focused, RAG-first design
See the LlamaIndex page →

Key differences

LangChain is lLM app framework, while LlamaIndex is data / RAG framework. In short, LangChain fits developers building tool-using LLM apps, and LlamaIndex fits developers building data-heavy RAG apps.

Which should you choose?

Choose LangChain for developers building tool-using LLM apps. Choose LlamaIndex for developers building data-heavy RAG apps.

There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.

Frequently asked questions

Is LangChain or LlamaIndex easier to use?

Both sit at a similar level (Intermediate). Your choice should come down to fit rather than difficulty.

Are LangChain and LlamaIndex free?

LangChain is free and open source (MIT), and LlamaIndex is free and open source (MIT). Neither charges for the core software.

Can I run LangChain and LlamaIndex locally?

LangChain: cloud-optional · LlamaIndex: cloud-optional. Both can be used without sending your data to a third-party cloud where their setup allows.

LangChain vs LlamaIndex — which should I pick in 2026?

Choose LangChain for developers building tool-using LLM apps. Choose LlamaIndex for developers building data-heavy RAG apps.

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