Tooling
LangGraph vs LangChain
LangGraph is a graph-based orchestration layer for stateful agents and cycles on top of LangChain primitives; LangChain is the broader orchestration ecosystem.
Featured · Updated 8 weeks ago · Last verified: August 2026
Choose LangGraph when
First-class graphs, cycles, and branching—built for non-linear workflows.
Choose LangChain when
Chains, LCEL, and routing are ideal for many linear and lightly branching flows.
Decision axes: Workflow shape · Agents & tools · State & durability · Learning curve
How they compare
Criterion-by-criterion notes from the catalog—not a ranking. Validate on your own gold set.
| Choice | LangGraph | LangChain |
|---|---|---|
| Workflow shape | First-class graphs, cycles, and branching—built for non-linear workflows. | Chains, LCEL, and routing are ideal for many linear and lightly branching flows. |
| Agents & tools | Strong for agents that revisit tools, branch, or wait for approvals. | Broad agent abstractions; LangGraph extends when complexity grows. |
| State & durability | Checkpointing and resume patterns for durable execution. | Can be added via LangGraph when needed. |
| Learning curve | Higher cognitive load—teams need graph/state discipline. | Large ecosystem; many tutorials and integrations. |
| Interop | Designed to compose with LangChain primitives; incremental adoption path. | LangGraph sits on top—start simple and evolve. |
Overview
LangGraph is a graph/state layer for complex agents; LangChain is the broader toolkit for chains, tools, and integrations. They compose: many teams start with LangChain and add LangGraph when workflows become non-linear.
Who should choose LangGraph
Choose LangGraph if:
- Use LangGraph when you need cycles, branching, approvals, and checkpointed execution in production
- Use LangGraph when your agents revisit tools, wait on humans, or require durable retries
- Workflow shape is a top priority — First-class graphs, cycles, and branching—built for non-linear workflows
Who should choose LangChain
Choose LangChain if:
- Use LangChain alone when linear chains, light routing, and standard tool calling cover your product
- Use LangChain when team familiarity and integration breadth matter more than graph formalism today
- Workflow shape is a top priority — Chains, LCEL, and routing are ideal for many linear and lightly branching flows
Limitations and trade-offs
Graph complexity can become hard to debug without tracing. LangChain’s fast releases require disciplined version pinning.
Final verdict
Start simple; add LangGraph when you can name the state transitions you need. Invest in observability the moment you introduce cycles.
Choose LangGraph when Use LangGraph when you need cycles, branching, approvals, and checkpointed execution in production.
Choose LangChain when Use LangChain alone when linear chains, light routing, and standard tool calling cover your product.
Key insights
Concrete technical or product signals.
- Don’t start with LangGraph if a simple chain solves the problem—add graphs when state and cycles become real requirements.
Use cases
Where this shines in production.
- Designing agents with explicit approval loops
- Evolving from chains to stateful workflows
FAQ
Is LangGraph better than LangChain?
Neither LangGraph nor LangChain is a universal winner. Use the comparison table and the choose-when notes, then validate on your workload.
Which is better for coding: LangGraph or LangChain?
LangGraph: Strong for agents that revisit tools, branch, or wait for approvals. LangChain: Broad agent abstractions; LangGraph extends when complexity grows. The catalog does not declare a winner on agents & tools.
Can I use both LangGraph and LangChain?
Yes. Many teams keep both and route by constraint. Use LangGraph for First-class graphs, cycles, and branching—built for non-linear workflows, and LangChain for Chains, LCEL, and routing are ideal for many linear and lightly branching flows. Confirm vendor terms before mixing them in one production workflow.