LangGraph vs Letta
Detailed side-by-side comparison to help you choose the right tool
LangGraph
Agent Frameworks
Graph-based stateful orchestration runtime for agent loops.
Starting Price
Custom
Letta
Memory & State
Stateful agent platform inspired by persistent memory architectures.
Starting Price
Custom
Feature Comparison
| Feature | LangGraph | Letta |
|---|---|---|
| Category | Agent Frameworks | Memory & State |
| Pricing Plans | 19 tiers | 19 tiers |
| Starting Price | ||
| Key Features |
|
|
LangGraph - Pros & Cons
Pros
- ✓State-machine approach provides fine-grained control over agent flows
- ✓Tight integration with the broader LangChain ecosystem
- ✓Built-in persistence for durable, long-running workflows
- ✓Cloud deployment option via LangSmith for production scale
- ✓Supports cyclic graphs enabling iterative agent reasoning
Cons
- ✗Tightly coupled to LangChain — harder to use standalone
- ✗Graph-based paradigm has a learning curve for new developers
- ✗Cloud features require a LangSmith subscription
- ✗Verbose configuration for simple linear workflows
Letta - Pros & Cons
Pros
- ✓Advanced stateful agent framework with persistent memory
- ✓Agents that learn and adapt over extended interactions
- ✓Open-source with research-backed memory architecture
- ✓Supports complex agent personalities and long-term context
- ✓Built-in memory management beyond simple context windows
Cons
- ✗Complex architecture requires understanding memory management concepts
- ✗Higher resource usage due to memory processing overhead
- ✗Smaller community compared to mainstream agent frameworks
- ✗Production deployment patterns are still maturing