Agent engineers
Model multi-step tool use with explicit control flow and reviewable source code.
Independent tool overview
LangGraph review: features, pricing and alternatives
Orchestrate stateful AI agents with LangGraph’s graph-based, open-source runtime.
Visit the official LangGraph site ↗
- Product type
- Open-source stateful agent orchestration
- Languages
- Python and JavaScript ecosystem
- Core pattern
- Nodes, edges and persisted graph state
- Managed companion
- LangSmith tracing and deployment
Overview
What LangGraph is
LangGraph is LangChain’s open-source runtime for stateful agent workflows. Developers define nodes and transitions for model calls, tools, approvals and other steps, then run the graph with persistence and streaming. It is suited to programs that need to pause, resume, retry or branch rather than one request to one model. LangChain’s own documentation says it can be used without the broader LangChain library.
The framework should be distinguished from the paid LangSmith platform. LangGraph code can run on infrastructure your team manages; LangSmith adds hosted tracing, evaluation and deployment services with seats and usage meters. LangGraph Platform was renamed LangSmith Deployment, so older articles using the former label can confuse a current buying comparison. The graph gives execution control, but reliable behavior still depends on carefully designed state, idempotent actions and evaluation.
Use cases
Who LangGraph is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Teams needing human checkpoints
Pause a workflow for approval or correction before sensitive actions continue.
Production AI teams
Use persistence and traces to investigate long-running work and improve failure recovery.
Capabilities
Core LangGraph features
Graph orchestration
Define nodes and conditional transitions for complex agent control flow.
Durable execution
Persist workflow state so tasks can resume after interruption.
Human-in-the-loop
Interrupt a run for review and continue with approved state.
Streaming
Expose intermediate events or results to applications during long tasks.
LangSmith integration
Optional platform services support traces, evaluation and managed deployment.
Process
How the LangGraph workflow works
Step 1
Map the task as states
Identify input, steps, decisions, tools and stopping conditions.
Step 2
Implement nodes and transitions
Keep side effects isolated and design every retryable action to avoid duplicate writes.
Step 3
Test recovery and approval
Simulate exceptions, interrupted runs, bad tool data and human edits.
Step 4
Deploy with observability
Run on chosen infrastructure or LangSmith Deployment, then trace cost, latency and outcome quality.
Cost
LangGraph pricing and free plan
LangGraph itself is open source. LangSmith is a separate commercial platform with a free one-seat Developer level, $39/seat/month Plus and custom Enterprise; traces, deployment and other resources can add pay-as-you-go charges.
LangGraph open source
$0 framework fee
Run the graph code on your own infrastructure.
- Pay model and hosting providers separately
- Own operational controls and storage
LangSmith Developer
$0/seat plus usage
One-seat entry to observability and testing.
- Includes a limited monthly base trace allowance
- Additional use can be metered
LangSmith Plus
$39/seat/month plus usage
Team observability and deployment access.
- Includes a small serverless deployment and traces
- Resource time and storage can be charged
Enterprise
Custom quote plus usage
Advanced hosting, permissions and support.
- Self-hosted or hybrid options
- Contract-specific controls
Pricing checked . Check current pricing at the source ↗
Assessment
LangGraph strengths and limitations
Where it stands out
- Explicit graph structure supports understandable branching and approval points.
- Persistence and streaming suit tasks that cannot complete in one model call.
- Open-source framework can be deployed independently of the paid LangSmith services.
What to consider
- A graph runtime does not guarantee correct tool decisions or high-quality answers; evaluation remains essential.
- Durable execution requires careful treatment of state changes and idempotent side effects.
- LangSmith’s seat price is only part of the cost if traces and deployment resources are used heavily.
Compare
LangGraph alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Coding
LangChain
A higher-level agent framework when standard abstractions cover the job without custom graph control.
Explore LangChain →Agents
Zapier Agents
A configured agent option when a team prefers app-connected automation over implementing a graph runtime.
Explore Zapier Agents →Business Operations
n8n
A visual app automation option for teams that prefer configured workflows over code.
Explore n8n →Questions
LangGraph FAQs
What is LangGraph?
An open-source framework for building stateful, multi-step AI agent workflows as graphs.
Do I need LangChain to use it?
No. LangChain says LangGraph can be used independently, though the projects integrate well.
Is LangGraph free?
The framework is open source; LangSmith observability and deployment have separate plans and usage charges.
What happened to LangGraph Platform?
LangChain renamed that managed deployment product LangSmith Deployment in October 2025.
Bottom line
Our LangGraph verdict
LangGraph is a strong option for engineers who need durable, explicit agent control flow. Start with one graph, test interruptions and duplicate-action handling, and cost the optional LangSmith services separately from the framework.
Visit LangGraph website ↗Similar Coding Tools
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