Side-by-Side Comparison · 2026

LangChain vs LangGraph: Full Comparison (2026)

LangChain is the framework for building llm-powered applications. LangGraph is build stateful multi-agent applications with graph-based flows. Use the breakdown below to find the right fit for your needs.

LangChain

LangChain

Free
vs

LangGraph

LangChain

Free
This page presents factual information sourced from publicly available vendor documentation and product pages. AIHub does not endorse either product. The right tool depends on your specific use case, team, and requirements — we recommend evaluating both tools directly before making a decision.

Side-by-Side Overview

Pricing Model
LangChain: FreeLangGraph: Free
API Access
LangChain: AvailableLangGraph: Not available
Platforms
LangChain: Python, JavaScript/TypeScript, LangGraph Platform (deployment), LangSmith (observability)LangGraph: Web
Integrations
LangChain: 8 integrationsLangGraph: —
Vendor
LangChain: LangChainLangGraph: LangChain
Category
LangChain: FrameworksLangGraph: Frameworks
Launch
LangChain: Oct 2022LangGraph: —

About LangChain

LangChain provides abstractions for chaining LLM calls, integrating tools and memory, building agents, and connecting to data sources. Available in Python and JavaScript.

Designed For

  • RAG applications
  • AI agents
  • Document Q&A
  • Chatbots
Full LangChain details

About LangGraph

LangGraph extends LangChain with graph-based orchestration for building stateful, cyclic multi-agent applications. Enables complex agent workflows with conditional edges, state persistence, and human-in-the-loop checkpoints.

Designed For

  • Stateful AI agents
  • Complex multi-step workflows
  • Cyclic agent loops
  • Human-in-the-loop
Full LangGraph details

Strengths & Limitations

LangChain

Strengths

  • Large ecosystem
  • Many integrations
  • Active community

Limitations

  • Steep learning curve
  • Over-abstracted
  • Rapid API changes

LangGraph

Strengths

  • Stateful by design
  • LangChain ecosystem
  • Complex flow support

Limitations

  • Requires LangChain knowledge
  • Complex for simple tasks

Frequently Asked Questions

What is the difference between LangChain and LangGraph?

LangChain is the framework for building llm-powered applications, while LangGraph is build stateful multi-agent applications with graph-based flows. LangChain is designed for LLM app developers, RAG system builders; LangGraph is designed for Frameworks. The right fit depends on your specific requirements.

How do the pricing models compare?

LangChain is available under a Free model. LangGraph is available under a Free model. LangChain's entry tier starts at Free. Always verify pricing on each vendor's official website as it may change.

What integrations does each tool support?

LangChain integrates with All major LLMs, Pinecone, Weaviate, Chroma. LangGraph integrates with various tools. Check each vendor's documentation for the full and current list.

How do I choose between LangChain and LangGraph?

Consider your team's technical requirements, budget, existing tooling, and use case before deciding. We recommend signing up for free trials or demos of both tools where available, and consulting each vendor's documentation. AIHub provides this comparison for informational purposes only.