THE COMPARISON / A CLOSER LOOK
Google ADK vs Letta
Compare the listed plans, useful capabilities, and practical tradeoffs.
Prices and features reflect editorial records. Check vendor terms before you buy; documentary checks do not imply hands-on testing.
Google ADK
🔴DeveloperAgent framework
Google’s development kit for constructing, evaluating, and deploying modular AI agents.
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FreeLetta
🔴DeveloperAI Agents
Open-source stateful agent framework from the MemGPT team — persistent, self-editing memory across conversations, model-agnostic, plus a hosted cloud platform…
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FreeFeature Comparison
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Google ADK - Pros & Cons
Pros
- ✓Code-first abstractions support versioning and testable agent behavior
- ✓Evaluation and deployment workflows address more than prompt prototyping
- ✓Natural fit for teams already using Gemini and Google Cloud
Cons
- ✗Requires software engineering skills and operational ownership
- ✗End-to-end cost depends on separate model and cloud services
- ✗Deep Google integration may reduce portability to other stacks
Letta - Pros & Cons
Pros
- ✓One of the few frameworks where memory is a first-class primitive, not a bolted-on RAG layer
- ✓Model-agnostic — swap providers mid-conversation without losing agent state
- ✓Fully Apache 2.0, backed by the academic MemGPT paper (real research pedigree)
- ✓ADE visual debugger makes memory issues actually inspectable, unlike opaque vector DBs
- ✓MCP client support means Letta agents can call any MCP tool alongside their memory
Cons
- ✗Steeper learning curve than stateless frameworks like LangChain or CrewAI
- ✗Letta Cloud pricing is inconsistently published — hard to budget without vendor call
- ✗Ecosystem/integrations are smaller than LangChain's
- ✗Structured memory model requires up-front schema thinking many teams skip
- ✗Debugging in production still relies heavily on the ADE — no mature APM yet
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