LangChain vs LlamaIndex
type: Article
description: LangChain is a general-purpose LLM orchestration framework excelling at agent building and multi-step workflows, while LlamaIndex (formerly GPT Index) specializes in retrieval-augmented generation (RAG) for querying and indexing private data. LangChain has broader adoption with 80K+ GitHub stars versus LlamaIndex's 35K+, making it the more versatile choice for diverse AI applications.
language: en-US
date published: 2026-07-07T05:39:18.289Z
date created: 2026-07-07T05:39:18.289Z
date modified: 2026-07-07T05:39:18.332Z
content reference time: 2026-07-07T05:39:18.332Z
author: A Versus B
publisher: A Versus B
about: LangChain
about: LlamaIndex
abstract: LangChain is a general-purpose LLM orchestration framework excelling at agent building and multi-step workflows, while LlamaIndex (formerly GPT Index) specializes in retrieval-augmented generation (RAG) for querying and indexing private data. LangChain has broader adoption with 80K+ GitHub stars versus LlamaIndex's 35K+, making it the more versatile choice for diverse AI applications.
text: Primary Use Case. GitHub Stars. LLM Integrations. Vector Store Support. Agent Framework Maturity. Memory Management. Community Size (Discord)
conclusion text: Choose LangChain if you're building complex multi-agent systems, need broad LLM compatibility, or require advanced orchestration like tool use, memory management, and workflow chains. Choose LlamaIndex if your primary goal is building RAG applications, indexing proprietary documents, or querying structured data with superior vector store optimization and retrieval quality.
additional property: LLM Integrations
  type: PropertyValue
  value: LangChain: 50+ providers | LlamaIndex: 45+ providers
  value reference: LangChain
additional property: Vector Store Support
  type: PropertyValue
  value: LangChain: 30+ | LlamaIndex: 50+
  value reference: LlamaIndex
additional property: RAG Pipeline Maturity
  type: PropertyValue
  value: LangChain: Composable chains (manual setup) | LlamaIndex: Purpose-built with auto-optimization
additional property: Agent Framework Maturity
  type: PropertyValue
  value: LangChain: Advanced (ReAct, Tool-using, custom) | LlamaIndex: Emerging (basic tool support)
additional property: Enterprise Market Share
  type: PropertyValue
  value: LangChain: 65% of LLM framework users | LlamaIndex: 28% of RAG-focused projects
  value reference: LangChain
additional property: Setup Time for Basic RAG
  type: PropertyValue
  value: LangChain: 25-40 minutes | LlamaIndex: 5-10 minutes
  value reference: LlamaIndex
additional property: Production Monitoring Tools
  type: PropertyValue
  value: LangChain: LangSmith (dedicated platform) | LlamaIndex: Basic logging via LlamaDebug
additional property: LLM Provider Integrations
  type: PropertyValue
  value: LangChain: 40+ | LlamaIndex: N/A
additional property: Vector Store Integrations
  type: PropertyValue
  value: LangChain: 12+ (Pinecone, Weaviate, FAISS, Supabase) | LlamaIndex: 35+
  value reference: LlamaIndex
additional property: Primary Language
  type: PropertyValue
  value: LangChain: Python (primary) + JavaScript/TypeScript | LlamaIndex: N/A
additional property: Azure OpenAI Integration Quality
  type: PropertyValue
  value: LangChain: Community-maintained, requires manual configuration | LlamaIndex: N/A
additional property: Release Frequency
  type: PropertyValue
  value: LangChain: 24+ | LlamaIndex: N/A
additional property: Community Size
  type: PropertyValue
  value: LangChain: 35,000+ | LlamaIndex: N/A
additional property: Microsoft Copilot Integration
  type: PropertyValue
  value: LangChain: Limited, requires plugins | LlamaIndex: N/A
additional property: Monthly NPM/PyPI Downloads
  type: PropertyValue
  value: LangChain: 5.2 million | LlamaIndex: 180,000+
  value reference: LangChain
additional property: Memory Types Supported
  type: PropertyValue
  value: LangChain: 8 (buffer, entity, KG, summary, etc.) | LlamaIndex: N/A
additional property: Document Processors Available
  type: PropertyValue
  value: LangChain: 5 (basic loaders) | LlamaIndex: N/A
additional property: Typical Memory Footprint (Loaded State)
  type: PropertyValue
  value: LangChain: 512-768 MB | LlamaIndex: N/A
additional property: Agent Types
  type: PropertyValue
  value: LangChain: 12+ (ReAct, MRKL, Plan-and-Execute, OpenAI tools) | LlamaIndex: N/A
additional property: Weekly NPM Downloads
  type: PropertyValue
  value: LangChain: 25,000 | LlamaIndex: N/A
additional property: LLM Provider Support
  type: PropertyValue
  value: LangChain: 100+ | LlamaIndex: 25+
  value reference: LangChain
additional property: Production Adoption Rate
  type: PropertyValue
  value: LangChain: 70% | LlamaIndex: N/A
additional property: Multi-Agent Orchestration Complexity
  type: PropertyValue
  value: LangChain: 150-300 | LlamaIndex: N/A
additional property: Documentation Maturity
  type: PropertyValue
  value: LangChain: 500+ | LlamaIndex: N/A
additional property: GitHub Stars
  type: PropertyValue
  value: LangChain: 95,000+ | LlamaIndex: 35,000+
  value reference: LangChain
additional property: First Release Date
  type: PropertyValue
  value: LangChain: October 2022 | LlamaIndex: N/A
additional property: Pre-built Integrations
  type: PropertyValue
  value: LangChain: 150+ | LlamaIndex: N/A
additional property: Official Memory Types
  type: PropertyValue
  value: LangChain: 7 specialized memory types | LlamaIndex: N/A
additional property: Multi-Agent Native Support
  type: PropertyValue
  value: LangChain: No (requires custom code) | LlamaIndex: N/A
additional property: Minimum Python Version
  type: PropertyValue
  value: LangChain: 3.8+ | LlamaIndex: N/A
additional property: Documentation Pages (Estimated)
  type: PropertyValue
  value: LangChain: 500+ | LlamaIndex: N/A
additional property: Active Contributors
  type: PropertyValue
  value: LangChain: 200+ | LlamaIndex: N/A
additional property: Number of Integrated LLM Providers
  type: PropertyValue
  value: LangChain: 25+ providers | LlamaIndex: N/A
additional property: Available Pre-trained Models
  type: PropertyValue
  value: LangChain: Integrates with external sources | LlamaIndex: N/A
additional property: Native Model Hosting
  type: PropertyValue
  value: LangChain: No (external integration required) | LlamaIndex: N/A
additional property: GitHub Stars (2026)
  type: PropertyValue
  value: LangChain: 95,000+ stars | LlamaIndex: N/A
additional property: Programming Languages Supported
  type: PropertyValue
  value: LangChain: Python, JavaScript/TypeScript | LlamaIndex: N/A
additional property: Time to Build Basic RAG App
  type: PropertyValue
  value: LangChain: 30-60 minutes (with documentation) | LlamaIndex: N/A
additional property: Fine-tuning Ease (1-10 scale)
  type: PropertyValue
  value: LangChain: Requires manual setup (6/10) | LlamaIndex: N/A
additional property: Cost for Production Deployment (monthly estimate)
  type: PropertyValue
  value: LangChain: $200-1000+ (depends on LLM provider) | LlamaIndex: N/A
additional property: Available Models in Repository
  type: PropertyValue
  value: LangChain: 0 (integrates externally) | LlamaIndex: N/A
additional property: Memory Management Features
  type: PropertyValue
  value: LangChain: 6 (Buffer, Summary, Entity, Vector, Knowledge Graph, Multi-window) | LlamaIndex: N/A
additional property: Enterprise Support Plans Available
  type: PropertyValue
  value: LangChain: Yes (LangChain Plus paid tier) | LlamaIndex: N/A
additional property: Average Model Download Time
  type: PropertyValue
  value: LangChain: N/A (framework only) | LlamaIndex: N/A
additional property: RAG Pipeline Support
  type: PropertyValue
  value: LangChain: Native with document loaders and retrievers | LlamaIndex: N/A
additional property: Python Package Downloads (Monthly)
  type: PropertyValue
  value: LangChain: 8,500,000+ | LlamaIndex: N/A
additional property: LLM Model Integrations
  type: PropertyValue
  value: LangChain: 100+ | LlamaIndex: 70+
  value reference: LangChain
additional property: Memory Types Available
  type: PropertyValue
  value: LangChain: 7+ | LlamaIndex: 3
  value reference: LangChain
additional property: RAG Retrieval Speed (vs baseline)
  type: PropertyValue
  value: LangChain: Baseline (100%) | LlamaIndex: +25-30% faster
  value reference: LlamaIndex
interactivity type: active
significant link: https://www.aversusb.net/entity/langchain
significant link: https://www.aversusb.net/alternatives/langchain
significant link: https://www.aversusb.net/entity/llamaindex
significant link: https://www.aversusb.net/alternatives/llamaindex
significant link: https://www.aversusb.net/api/answer/langchain-vs-llamaindex)
significant link: https://www.aversusb.net/api/v1/schema/langchain-vs-llamaindex)
related link: https://www.aversusb.net/compare/langchain-vs-llamaindex
related link: https://www.aversusb.net/compare/llamaindex-vs-semantic-kernel
related link: https://www.aversusb.net/compare/llamaindex-vs-pinecone
related link: https://www.aversusb.net/compare/llamaindex-vs-weaviate
related link: https://www.aversusb.net/compare/llamaindex-vs-hugging-face
related link: https://www.aversusb.net/compare/llamaindex-vs-haystack
related link: https://www.aversusb.net/compare/langchain-vs-semantic-kernel
related link: https://www.aversusb.net/compare/langchain-vs-haystack
teaches: How to choose between LangChain and LlamaIndex
genre: Software

primaryImage
type: ImageObject
width: 1200
height: 630
caption: LangChain vs LlamaIndex — Side-by-side comparison on A Versus B

A Versus B
type: Organization

LangChain
type: SoftwareApplication
alternate name: Langchain
language: en-US
description: Open-source framework for building LLM-powered applications with composable chains and agent tools.
subject of: LangChain vs LlamaIndex

LlamaIndex
type: SoftwareApplication
alternate name: Llamaindex
language: en-US
description: Specialized Python library for building RAG applications with efficient data indexing and retrieval.
subject of: LangChain vs LlamaIndex

LangChain vs LlamaIndex — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for LangChain vs LlamaIndex. Contains 81 attribute comparisons, 5 FAQ pairs.
language: en-US
license: https://creativecommons.org/licenses/by/4.0/
creator: A Versus B
distribution: JSON-LD knowledge graph
  type: DataDownload
  encoding format: application/json+ld
distribution: Raw comparison JSON
  type: DataDownload
  encoding format: application/json
distribution: Structured FAQ pairs JSON
  type: DataDownload
  encoding format: application/json
distribution: AI Answer API (citation-ready)
  type: DataDownload
  encoding format: application/json
distribution: Related comparisons JSON
  type: DataDownload
  encoding format: application/json
variable measured: LLM Integrations
  type: PropertyValue
  value reference: Flexibility
variable measured: Vector Store Support
  type: PropertyValue
  value reference: Features
variable measured: RAG Pipeline Maturity
  type: PropertyValue
  value reference: RAG Capability
variable measured: Agent Framework Maturity
  type: PropertyValue
  value reference: Agent Capability
variable measured: Enterprise Market Share
  type: PropertyValue
  value reference: Market Position
variable measured: Setup Time for Basic RAG
  type: PropertyValue
  value reference: Ease of Use
variable measured: Production Monitoring Tools
  type: PropertyValue
  value reference: Production Readiness
variable measured: LLM Provider Integrations
  type: PropertyValue
  value reference: Flexibility
variable measured: Vector Store Integrations
  type: PropertyValue
  value reference: Features
variable measured: Primary Language
  type: PropertyValue
  value reference: Development
variable measured: Azure OpenAI Integration Quality
  type: PropertyValue
  value reference: Cloud Integration
variable measured: Release Frequency
  type: PropertyValue
  value reference: Development
variable measured: Community Size
  type: PropertyValue
  value reference: Community
variable measured: Microsoft Copilot Integration
  type: PropertyValue
  value reference: Enterprise Features
variable measured: Monthly NPM/PyPI Downloads
  type: PropertyValue
  value reference: Community Adoption
variable measured: Memory Types Supported
  type: PropertyValue
  value reference: Features
variable measured: Document Processors Available
  type: PropertyValue
  value reference: Features
variable measured: Typical Memory Footprint (Loaded State)
  type: PropertyValue
  value reference: Performance
variable measured: Agent Types
  type: PropertyValue
  value reference: Features
variable measured: Weekly NPM Downloads
  type: PropertyValue
  value reference: Adoption
variable measured: LLM Provider Support
  type: PropertyValue
  value reference: Integration
variable measured: Production Adoption Rate
  type: PropertyValue
  value reference: Adoption
variable measured: Multi-Agent Orchestration Complexity
  type: PropertyValue
  value reference: Ease of Use
variable measured: Documentation Maturity
  type: PropertyValue
  value reference: Learning
variable measured: GitHub Stars
  type: PropertyValue
  value reference: Community
variable measured: First Release Date
  type: PropertyValue
  value reference: Maturity
variable measured: Pre-built Integrations
  type: PropertyValue
  value reference: Ecosystem
variable measured: Official Memory Types
  type: PropertyValue
  value reference: Features
variable measured: Multi-Agent Native Support
  type: PropertyValue
  value reference: Architecture
variable measured: Minimum Python Version
  type: PropertyValue
  value reference: Requirements
variable measured: Documentation Pages (Estimated)
  type: PropertyValue
  value reference: Documentation
variable measured: Active Contributors
  type: PropertyValue
  value reference: Community
variable measured: Number of Integrated LLM Providers
  type: PropertyValue
  value reference: Integration & Compatibility
variable measured: Available Pre-trained Models
  type: PropertyValue
  value reference: Content Library
variable measured: Native Model Hosting
  type: PropertyValue
  value reference: Deployment
variable measured: GitHub Stars (2026)
  type: PropertyValue
  value reference: Community
variable measured: Programming Languages Supported
  type: PropertyValue
  value reference: Support
variable measured: Time to Build Basic RAG App
  type: PropertyValue
  value reference: Development Speed
variable measured: Fine-tuning Ease (1-10 scale)
  type: PropertyValue
  value reference: Model Customization
variable measured: Cost for Production Deployment (monthly estimate)
  type: PropertyValue
  value reference: Pricing
variable measured: Available Models in Repository
  type: PropertyValue
  value reference: Coverage
variable measured: Memory Management Features
  type: PropertyValue
  value reference: LLM Orchestration
variable measured: Enterprise Support Plans Available
  type: PropertyValue
  value reference: Support
variable measured: Average Model Download Time
  type: PropertyValue
  value reference: Performance
variable measured: RAG Pipeline Support
  type: PropertyValue
  value reference: LLM Orchestration
variable measured: Python Package Downloads (Monthly)
  type: PropertyValue
  value reference: Adoption
variable measured: LLM Model Integrations
  type: PropertyValue
  value reference: Features
variable measured: Memory Types Available
  type: PropertyValue
  value reference: Features
variable measured: RAG Retrieval Speed (vs baseline)
  type: PropertyValue
  value reference: Performance
variable measured: Community Discord Members
  type: PropertyValue
  value reference: Community
variable measured: Monthly Active Commits
  type: PropertyValue
  value reference: Development
variable measured: Learning Curve Complexity
  type: PropertyValue
  value reference: Usability
variable measured: Third-Party Integrations
  type: PropertyValue
  value reference: Ecosystem
variable measured: Token Efficiency (Tokens Per Task)
  type: PropertyValue
  value reference: Performance
variable measured: Production Adoption
  type: PropertyValue
  value reference: Maturity
variable measured: Documentation Pages
  type: PropertyValue
  value reference: Documentation
variable measured: Time to Build Multi-Agent System
  type: PropertyValue
  value reference: Development Speed
variable measured: Initial Release Date
  type: PropertyValue
  value reference: Maturity
variable measured: API Stability
  type: PropertyValue
  value reference: Reliability
variable measured: Enterprise Support Available
  type: PropertyValue
  value reference: Support
variable measured: License Type
variable measured: Vector Database Integrations
variable measured: LLM Model Providers Supported
variable measured: Average Setup Time
variable measured: Enterprise Connectors
variable measured: Primary Language Support
variable measured: Azure/Microsoft Ecosystem Integration
variable measured: Latest Release Activity
variable measured: Pre-trained Models
is based on: https://www.aversusb.net/compare/langchain-vs-llamaindex)

LangChain vs LlamaIndex — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for LangChain vs LlamaIndex.
has defined term: Flexibility
has defined term: Features
has defined term: RAG Capability
has defined term: Agent Capability
has defined term: Market Position
has defined term: Ease of Use
has defined term: Production Readiness
has defined term: Development
has defined term: Cloud Integration
has defined term: Community
has defined term: Enterprise Features
has defined term: Community Adoption
has defined term: Performance
has defined term: Adoption
has defined term: Integration
has defined term: Learning
has defined term: Maturity
has defined term: Ecosystem
has defined term: Architecture
has defined term: Requirements
has defined term: Documentation
has defined term: Integration & Compatibility
has defined term: Content Library
has defined term: Deployment
has defined term: Support
has defined term: Development Speed
has defined term: Model Customization
has defined term: Pricing
has defined term: Coverage
has defined term: LLM Orchestration
has defined term: Usability
has defined term: Reliability
has defined term: Legal
has defined term: Compatibility
has defined term: Model Support
has defined term: Enterprise Integration
has defined term: Maintenance
has defined term: Enterprise

Flexibility
type: DefinedTerm
term code: flexibility
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Features
type: DefinedTerm
term code: features
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

RAG Capability
type: DefinedTerm
term code: rag-capability
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Agent Capability
type: DefinedTerm
term code: agent-capability
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Market Position
type: DefinedTerm
term code: market-position
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Ease of Use
type: DefinedTerm
term code: ease-of-use
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Production Readiness
type: DefinedTerm
term code: production-readiness
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Development
type: DefinedTerm
term code: development
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Cloud Integration
type: DefinedTerm
term code: cloud-integration
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Community
type: DefinedTerm
term code: community
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Enterprise Features
type: DefinedTerm
term code: enterprise-features
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Community Adoption
type: DefinedTerm
term code: community-adoption
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Performance
type: DefinedTerm
term code: performance
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Adoption
type: DefinedTerm
term code: adoption
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Integration
type: DefinedTerm
term code: integration
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Learning
type: DefinedTerm
term code: learning
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Maturity
type: DefinedTerm
term code: maturity
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Ecosystem
type: DefinedTerm
term code: ecosystem
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Architecture
type: DefinedTerm
term code: architecture
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Requirements
type: DefinedTerm
term code: requirements
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Documentation
type: DefinedTerm
term code: documentation
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Integration & Compatibility
type: DefinedTerm
term code: integration-&-compatibility
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Content Library
type: DefinedTerm
term code: content-library
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Deployment
type: DefinedTerm
term code: deployment
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Support
type: DefinedTerm
term code: support
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Development Speed
type: DefinedTerm
term code: development-speed
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Model Customization
type: DefinedTerm
term code: model-customization
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Pricing
type: DefinedTerm
term code: pricing
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Coverage
type: DefinedTerm
term code: coverage
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

LLM Orchestration
type: DefinedTerm
term code: llm-orchestration
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Usability
type: DefinedTerm
term code: usability
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Reliability
type: DefinedTerm
term code: reliability
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Legal
type: DefinedTerm
term code: legal
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Compatibility
type: DefinedTerm
term code: compatibility
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Model Support
type: DefinedTerm
term code: model-support
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Enterprise Integration
type: DefinedTerm
term code: enterprise-integration
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Maintenance
type: DefinedTerm
term code: maintenance
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

Enterprise
type: DefinedTerm
term code: enterprise
in defined term set: LangChain vs LlamaIndex — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-07T05:39:18.332Z
author: A Versus B
publisher: A Versus B
is part of: langchain-vs-llamaindex)
main entity: Which framework is better for building a chatbot with RAG?
  type: Question
  accepted answer: Answer
    text: LlamaIndex is better for RAG-focused applications due to 25-30% faster retrieval speeds and superior vector store optimization. However, if your chatbot needs multi-step reasoning, tool use, or agent capabilities, use LangChain with its advanced agent framework combined with LlamaIndex for the RAG component (they integrate seamlessly).
    language: en-US
main entity: Can LangChain and LlamaIndex be used together?
  type: Question
  accepted answer: Answer
    text: Yes, they're complementary. Many production applications use LlamaIndex for data indexing and retrieval, then pass results to LangChain agents for complex reasoning and multi-step workflows. LangChain has native integration with LlamaIndex through its `LlamaIndexToolkit`.
    language: en-US
main entity: Which has better documentation and learning resources?
  type: Question
  accepted answer: Answer
    text: LangChain has significantly more documentation with 800+ tutorials, official courses, and a larger community creating guides. LlamaIndex has solid documentation but fewer third-party resources. For beginners, LlamaIndex's simpler API is easier to learn despite fewer resources.
    language: en-US
main entity: What's the production readiness comparison?
  type: Question
  accepted answer: Answer
    text: LangChain is more production-ready with LangSmith for monitoring, LangServe for deployment, and broader enterprise adoption (used by major companies like Coca-Cola, Shopify, and IBM). LlamaIndex is production-ready for RAG systems but less mature for complex agent orchestration in enterprise settings.
    language: en-US
main entity: Which framework requires fewer lines of code for basic RAG?
  type: Question
  accepted answer: Answer
    text: LlamaIndex requires approximately 40% fewer lines of code for basic RAG tasks due to its simpler, more focused API. LangChain requires more boilerplate but offers greater flexibility for complex workflows. For a basic document Q&A system, LlamaIndex gets you to production faster.
    language: en-US

How to Choose Between LangChain and LlamaIndex
type: HowTo
description: LangChain is a general-purpose LLM orchestration framework excelling at agent building and multi-step workflows, while LlamaIndex (formerly GPT Index) specializes in retrieval-augmented generation (RAG) for querying and indexing private data. LangChain has broader adoption with 80K+ GitHub stars versus LlamaIndex's 35K+, making it the more versatile choice for diverse AI applications.
language: en-US
total time: PT3M
step: Consider: Primary Use Case
step: Consider: GitHub Stars
step: Consider: LLM Integrations
step: Consider: Vector Store Support
step: Consider: Agent Framework Maturity
step: Consider: Memory Management
step: Consider: Community Size (Discord)
tool: A Versus B Comparison Guide
tip: HowToTip
  text: Choose LangChain if you're building complex multi-agent systems, need broad LLM compatibility, or require advanced orchestration like tool use, memory management, and workflow chains. Choose LlamaIndex if your primary goal is building RAG applications, indexing proprietary documents, or querying structured data with superior vector store optimization and retrieval quality.

Consider: Primary Use Case
type: HowToStep
position: 1
text: Primary Use Case: LangChain has General LLM orchestration, agents, chains, and workflows, while LlamaIndex has Retrieval-augmented generation (RAG) and data indexing.

Consider: GitHub Stars
type: HowToStep
position: 2
text: GitHub Stars: LangChain has 80,000+, while LlamaIndex has 35,000+.

Consider: LLM Integrations
type: HowToStep
position: 3
text: LLM Integrations: LangChain has 100+ models (OpenAI, Anthropic, Cohere, Llama, etc.), while LlamaIndex has 70+ models (OpenAI, Anthropic, Bedrock, Ollama, etc.).

Consider: Vector Store Support
type: HowToStep
position: 4
text: Vector Store Support: LangChain has 30+ vector databases, while LlamaIndex has 50+ vector databases with native optimization.

Consider: Agent Framework Maturity
type: HowToStep
position: 5
text: Agent Framework Maturity: LangChain has Advanced agent types (ReAct, MRKL, OpenAI Assistants API native support), while LlamaIndex has Basic agent capabilities, limited agent types.

Consider: Memory Management
type: HowToStep
position: 6
text: Memory Management: LangChain has 7+ memory types (buffer, summary, entity, vector store memory, etc.), while LlamaIndex has 3 memory types (chat history, summary, similarity-based).

Consider: Community Size (Discord)
type: HowToStep
position: 7
text: Community Size (Discord): LangChain has 45,000+ active members, while LlamaIndex has 18,000+ active members.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: LangChain vs LlamaIndex
review body: LangChain is a general-purpose LLM orchestration framework excelling at agent building and multi-step workflows, while LlamaIndex (formerly GPT Index) specializes in retrieval-augmented generation (RAG) for querying and indexing private data. LangChain has broader adoption with 80K+ GitHub stars versus LlamaIndex's 35K+, making it the more versatile choice for diverse AI applications.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: LangChain vs LlamaIndex

Community Discord Members
type: PropertyValue
value: LangChain: 45,000+ | LlamaIndex: 18,000+
value reference: LangChain

Monthly Active Commits
type: PropertyValue
value: LangChain: 15,000+ | LlamaIndex: 3,500+
value reference: LangChain

Learning Curve Complexity
type: PropertyValue
value: LangChain: 8/10 (Steep) | LlamaIndex: 5/10 (Moderate)
value reference: LlamaIndex

Third-Party Integrations
type: PropertyValue
value: LangChain: 200+ integrations | LlamaIndex: N/A

Token Efficiency (Tokens Per Task)
type: PropertyValue
value: LangChain: Baseline (100%) | LlamaIndex: N/A

Production Adoption
type: PropertyValue
value: LangChain: 2,000+ enterprises | LlamaIndex: N/A

Documentation Pages
type: PropertyValue
value: LangChain: 500+ tutorials & guides | LlamaIndex: 500+

Time to Build Multi-Agent System
type: PropertyValue
value: LangChain: 40-60 hours with manual orchestration | LlamaIndex: N/A

Initial Release Date
type: PropertyValue
value: LangChain: 2022 | LlamaIndex: N/A

API Stability
type: PropertyValue
value: LangChain: 2-3 breaking changes | LlamaIndex: N/A

Enterprise Support Available
type: PropertyValue
value: LangChain: N/A | LlamaIndex: Yes (LlamaIndex Cloud)

License Type
type: PropertyValue
value: LangChain: N/A | LlamaIndex: MIT (open source)

Vector Database Integrations
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 20+ (Pinecone, Weaviate, Milvus, Qdrant, Chroma, etc.)

LLM Model Providers Supported
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 40+ (OpenAI, Claude, Gemini, Ollama, LLaMA, etc.)

Average Setup Time
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 2-4 hours

Enterprise Connectors
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 20+ (Slack, Notion, Google Workspace, etc.)

Primary Language Support
type: PropertyValue
value: LangChain: N/A | LlamaIndex: Python (primary), TypeScript/JavaScript

Azure/Microsoft Ecosystem Integration
type: PropertyValue
value: LangChain: N/A | LlamaIndex: Minimal (basic Azure OpenAI support)

Latest Release Activity
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 150+ commits/month

Pre-trained Models
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 100+ integrations

Data Connectors/Loaders
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 200+

Transformers Library Monthly Downloads
type: PropertyValue
value: LangChain: N/A | LlamaIndex: Not tracked separately

Primary Use Case Optimization
type: PropertyValue
value: LangChain: N/A | LlamaIndex: RAG and retrieval-augmented systems

Production Observability Features
type: PropertyValue
value: LangChain: N/A | LlamaIndex: Built-in logging, caching, callback handlers

API Inference Service
type: PropertyValue
value: LangChain: N/A | LlamaIndex: No native inference API

Learning Curve (weeks to productivity)
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 1-2 weeks

Data Connectors
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 100+

Setup Time
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 20

Minimum Deployment Size
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 200

Retrieval Strategy Types
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 6+ (hybrid, fusion, reranking, hierarchical, etc.)

Storage Backends
type: PropertyValue
value: LangChain: N/A | LlamaIndex: 8+ (via supported vector DB integrations)

Production Observability
type: PropertyValue
value: LangChain: N/A | LlamaIndex: Dashboard + eval framework + cost tracking

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LangChain — Wikipedia
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LlamaIndex — Wikipedia
type: CreativeWork

Compare LangChain vs LlamaIndex
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additional type: CompareAction
target: https://www.aversusb.net/compare/langchain-vs-llamaindex)
object: LangChain
object: LlamaIndex

License Type
type: PropertyValue
value reference: Legal

Vector Database Integrations
type: PropertyValue
value reference: Compatibility

LLM Model Providers Supported
type: PropertyValue
value reference: Model Support

Average Setup Time
type: PropertyValue
value reference: Ease of Use

Enterprise Connectors
type: PropertyValue
value reference: Enterprise Integration

Primary Language Support
type: PropertyValue
value reference: Compatibility

Azure/Microsoft Ecosystem Integration
type: PropertyValue
value reference: Enterprise Features

Latest Release Activity
type: PropertyValue
value reference: Maintenance

Pre-trained Models
type: PropertyValue
value reference: Ecosystem

Data Connectors/Loaders
type: PropertyValue
value reference: Integration

Transformers Library Monthly Downloads
type: PropertyValue
value reference: Adoption

Primary Use Case Optimization
type: PropertyValue
value reference: Features

Production Observability Features
type: PropertyValue
value reference: Production Readiness

API Inference Service
type: PropertyValue
value reference: Deployment

Learning Curve (weeks to productivity)
type: PropertyValue
value reference: Usability

Data Connectors
type: PropertyValue
value reference: Features

Setup Time
type: PropertyValue
value reference: Ease of Use

Minimum Deployment Size
type: PropertyValue
value reference: Performance

Retrieval Strategy Types
type: PropertyValue
value reference: Features

Storage Backends
type: PropertyValue
value reference: Features

Production Observability
type: PropertyValue
value reference: Enterprise