LangGraph vs Letta
Detailed side-by-side comparison to help you choose the right tool
LangGraph
🔴DeveloperAI agent framework
LangGraph is LangChain's open-source framework for building stateful, durable, multi-agent workflows in Python and JavaScript with graph-based control flow.
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FreeLetta
🔴DeveloperAI Knowledge Tools
Letta is the open-source successor to MemGPT — a stateful agent platform with persistent memory, tool use, and a visual Agent Development Environment.
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💡 Our Take
Choose Letta if you want a memory-first agent platform with hosted pricing, Letta Code, AgentFile portability, and a REST API for stateful agents. Choose LangGraph if you need a lower-level graph runtime with explicit state transitions.
LangGraph - Pros & Cons
Pros
- ✓Open-source library is MIT-licensed and runs anywhere without platform lock-in
- ✓Native checkpointing makes durable, resumable, human-in-the-loop agents straightforward
- ✓First-class multi-agent patterns: supervisor, hierarchical, sequential, parallel branches
- ✓Tight integration with LangSmith for production observability, evaluations, and replays
- ✓Active maintenance from the LangChain team with frequent releases and strong community
Cons
- ✗More verbose than LangChain for simple agents — explicit state schemas and edge functions add overhead
- ✗LangSmith trace pricing ($2.50/1k base traces) is a real cost at production scale
- ✗LCU + deployment-minute billing makes pricing harder to predict than seat-only competitors
- ✗Steeper learning curve than role-based frameworks like CrewAI for newcomers
- ✗Best documented in Python; JavaScript SDK exists but lags in features
Letta - Pros & Cons
Pros
- ✓Stateful by design — agents remember across sessions without prompt-stuffing
- ✓Visual ADE makes memory behavior inspectable and debuggable
- ✓Truly open source (Apache 2.0); self-hostable on commodity infra
- ✓Provider-agnostic so you can swap models without rewriting agents
- ✓Direct lineage from the MemGPT paper gives strong technical credibility
Cons
- ✗More moving parts than a stateless agent loop; not the right tool for one-shot tasks
- ✗Cloud pricing not fully transparent in static HTML; verify before signup
- ✗Memory management adds latency vs. raw chat completions
- ✗Production deployment of self-host requires managing vector store + database
- ✗Smaller community than LangChain or CrewAI
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