LangGraphFreemium
A low-level orchestration framework for building stateful, multi-step agent workflows with explicit control over state, branching, and human-in-the-loop steps.
AI / LLM comparison
LangGraph vs Temporal
Pricing, pros, cons, and ideal use cases — side by side.
TemporalFreemium
A durable execution platform that makes long-running, failure-prone workflows — including AI agents — reliable by default.
At a glance
| LangGraph | Temporal | |
|---|---|---|
| Pricing | FreemiumOpen-source framework, free to use. Paid tiers apply to the surrounding LangSmith platform, not the framework itself. | FreemiumOpen-source and self-hostable for free. Temporal Cloud is a usage-based managed service. |
| Category | AI / LLM | AI / LLM |
| Ideal for | Engineering teams building multi-step agentsEnterprise platform teamsWorkflows needing human-in-the-loop control | Teams running agents in productionPlatform teams building reliable workflow infrastructureEnterprises with long-running, multi-step AI processes |
Pros & cons
LangGraph
Pros
- Explicit control over agent state and branching
- First-class human-in-the-loop and checkpointing
- Strong fit for durable, long-running workflows
- Large ecosystem and active development
Cons
- Requires real engineering investment
- Lower-level than no-code agent builders
- You own deployment and observability
Temporal
Pros
- Makes long-running agent workflows crash-proof
- Automatic retries and full execution history
- Battle-tested well beyond AI use cases
- Self-host or managed Temporal Cloud
Cons
- Significant learning curve and architectural commitment
- Not AI-specific — you build the agent layer yourself
- Self-hosting the cluster is non-trivial
Which should you choose?
LangGraph is built around engineering teams building multi-step agents; Temporal leans more toward teams running agents in production. Shortlist the one whose strengths line up with your biggest constraint.