Letta vs Microsoft AutoGen

Detailed side-by-side comparison to help you choose the right tool

Letta

πŸ”΄Developer

AI Agents

Stateful AI agent platform from the MemGPT team, providing long-term memory, tools, and a managed runtime for production agents.

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Starting Price

Free

Microsoft AutoGen

AI Automation Platforms

Microsoft's open-source framework for building multi-agent AI systems with asynchronous, event-driven architecture.

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Starting Price

Free

Feature Comparison

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FeatureLettaMicrosoft AutoGen
CategoryAI AgentsAI Automation Platforms
Pricing Plans327 tiers11 tiers
Starting PriceFreeFree
Key Features
  • β€’ Persistent agents instead of stateless chat sessions
  • β€’ Memory palace for viewing an agent’s memory
  • β€’ Background memory agents / dream agents that refine prompts, context, and skills over time
  • β€’ Multi-agent conversation orchestration with flexible topologies
  • β€’ Built-in observability via OpenTelemetry integration
  • β€’ Cross-language interoperability between Python and .NET

πŸ’‘ Our Take

Choose Letta when long-term memory, model-agnostic state, and API-hosted persistent agents matter more than flexible conversation patterns between agents. Choose AutoGen when experimental multi-agent conversation design is the main need.

Letta - Pros & Cons

Pros

  • βœ“Built by the team that invented MemGPT-style stateful memory
  • βœ“Memory blocks are inspectable and editable β€” no black-box embeddings vault
  • βœ“Model-agnostic: switch between Claude, GPT, Gemini, and local Ollama freely
  • βœ“MCP support layers Letta's memory on top of the broader tool ecosystem
  • βœ“Generous Free tier for prototyping stateful agents

Cons

  • βœ—Memory editing adds tokens to every turn β€” costs grow on long sessions
  • βœ—Dashboard debugging is less mature than dedicated tracing tools
  • βœ—Hosted runtime locks you into Letta's data model unless you self-host
  • βœ—Memory tuning still benefits from periodic human-curated summaries

Microsoft AutoGen - Pros & Cons

Pros

  • βœ“MIT-licensed open source with active development
  • βœ“Backed by Microsoft Research with strong academic foundations
  • βœ“v0.4's async event-driven architecture enables scalable agent systems
  • βœ“Native cross-language support for Python and .NET
  • βœ“AutoGen Studio provides a no-code interface for rapid prototyping
  • βœ“Tight Azure AI Foundry integration for enterprise deployment

Cons

  • βœ—Microsoft's agent strategy is evolving; monitor official announcements for roadmap changes
  • βœ—v0.4 introduced major breaking changes from v0.2, requiring significant migration effort
  • βœ—Steep learning curve compared to simpler frameworks like CrewAI
  • βœ—AutoGen Studio is experimental and not production-ready
  • βœ—No commercial support tier outside of Azure AI Foundry

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πŸ”’ Security & Compliance Comparison

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Security FeatureLettaMicrosoft AutoGen
SOC2β€”β€”
GDPRβ€”β€”
HIPAAβ€”β€”
SSOβ€”β€”
Self-HostedπŸ”€ Hybridβœ… Yes
On-Premβœ… Yesβœ… Yes
RBACβ€”β€”
Audit Logβ€”β€”
Open Sourceβœ… Yesβœ… Yes
API Key Authβœ… Yesβ€”
Encryption at Restβ€”β€”
Encryption in Transitβœ… Yesβ€”
Data Residencynot publicly documentedβ€”
Data Retentionconfigurableconfigurable
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