CrewAI vs Letta
Detailed side-by-side comparison to help you choose the right tool
CrewAI
🔴DeveloperAI Agents
Open-source Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a 'crew' to complete complex tasks.
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FreeLetta
🔴DeveloperAI Agent Framework
Framework and cloud service for building stateful AI agents that remember, learn continuously, and improve over time — the successor to MemGPT.
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FreeFeature Comparison
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💡 Our Take
Choose Letta if persistent memory and stateful agents are central to your product, especially when each user or customer needs an agent that remembers over time. Choose CrewAI for simpler role-based multi-agent workflow orchestration.
CrewAI - Pros & Cons
Pros
- ✓Most opinionated multi-agent framework — easy to read, easy to maintain
- ✓Free tier includes the full visual Studio editor and 50 executions/month
- ✓Trusted by 63% of the Fortune 500 according to CrewAI
- ✓MCP-native: crews can consume and expose MCP tools
- ✓Enterprise tier has FedRAMP High and dedicated VPC options that competitors lack
- ✓Active GitHub community and frequent releases
Cons
- ✗Less flexible than LangGraph if you need fine-grained control over state transitions
- ✗Free tier capped at 50 workflow executions per month — easy to hit
- ✗Enterprise pricing is sales-led with no public numbers, making budget planning hard
- ✗Hierarchical process can burn tokens fast with a chatty manager agent
Letta - Pros & Cons
Pros
- ✓Persistent, editable memory is built into the agent runtime
- ✓ADE exposes agent state and tool calls for debugging
- ✓Python, TypeScript, REST, multiple model providers, and MCP offer flexible integration
- ✓Open-source self-hosting avoids mandatory platform lock-in
Cons
- ✗Stateful agents add privacy, retention, deletion, and migration responsibilities
- ✗Cloud plan and model usage can create separate cost layers
- ✗Memory quality still depends on prompts, models, and application-specific evaluation
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