LangChain
LangChain
FreeLangGraph
LangChain
FreeLangChain 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.
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
FreeAPI Access
LangChain
AvailableLangGraph
Not availablePlatforms
LangChain
Python, JavaScript/TypeScript, LangGraph Platform (deployment), LangSmith (observability)LangGraph
WebIntegrations
LangChain
8 integrationsLangGraph
—Vendor
LangChain
LangChainLangGraph
LangChainCategory
LangChain
FrameworksLangGraph
FrameworksLaunch
LangChain
Oct 2022LangGraph
—| Feature | LangChain | LangGraph |
|---|---|---|
| Pricing Model | Free | Free |
| API Access | Available | Not available |
| Platforms | Python, JavaScript/TypeScript, LangGraph Platform (deployment), LangSmith (observability) | Web |
| Integrations | 8 integrations | — |
| Vendor | LangChain | LangChain |
| Category | Frameworks | Frameworks |
| Launch | Oct 2022 | — |
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
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
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.
Feature Snapshot
Explore Further
LangChain full detailsLangGraph full detailsLangChain official siteLangGraph official siteRelated Comparisons
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Data sourced from public vendor documentation. Pricing, features, and availability may change. Always verify on official vendor websites before making purchasing decisions. AIHub is not affiliated with any of the listed vendors.