LangGraph vs smolagents
A side-by-side comparison of LangGraph and smolagents, two Orchestration tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
LangGraph
OrchestrationGraph-based agent orchestration. Stateful loops with checkpoints.
View LangGraphAt a glance
| Attribute | LangGraph | smolagents |
|---|---|---|
| Category | Orchestration | Orchestration |
| Pricing | FREE | FREE |
| License | Open source | Open source |
| Deployment | — | — |
| Platforms (differs) | API, CLI | API |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | LangChain | Hugging Face |
The honest brief
LangGraph
Durable checkpointed state-graph with human-in-the-loop — long agent runs pause and resume, unlike one-shot chains.
- Durable checkpointed state
- Low-level graph control
- Debuggable long-running agents
- Runs in production at major firms
- Steeper learning curve
- More boilerplate than chains
- Tied to LangChain conventions
smolagents
Agents 'think in code' — actions are executable Python snippets instead of JSON tool calls, which the docs say cuts step count by about 30%.
- Tiny, readable core (~1,000 LOC)
- Code-writing agents, fewer steps
- Model-agnostic via LiteLLM
- Sandboxed execution options
- Tight Hugging Face Hub integration
- Minimal by design — less batteries-included
- Code execution needs careful sandboxing
- Smaller feature surface than larger frameworks