LangChain vs Letta
A side-by-side comparison of capabilities, autonomy, integrations, and pricing to help you choose.
Short answer: choose LangChain if you want open-source framework and platform for building and deploying llm agents (Supervised agent, freemium); choose Letta if you want open-source framework for stateful ai agents with long-term memory (Supervised agent, freemium).
| LangChain | Letta | |
|---|---|---|
| What it is | Open-source framework and platform for building and deploying LLM agents | Open-source framework for stateful AI agents with long-term memory |
| Type | framework | framework |
| Autonomy | Supervised agent | Supervised agent |
| Pricing | freemium · Framework free (MIT); LangSmith free Developer tier | freemium · Free (open source); Cloud Pro $20/mo + usage |
| Best for | developers, enterprise, mid-market | developers |
| Deployment | self-hosted, api, saas | self-hosted, saas, api |
| Modalities | text, code, api | text, code, api |
| Models | model-agnostic, gpt, claude, gemini, llama, open-source | model-agnostic, gpt, claude, open-source |
| Protocols | function-calling, mcp, rest-api | mcp, rest-api |
| Integrations | OpenAI, Anthropic, Google, AWS Bedrock, Pinecone, Hugging Face | MCP servers, OpenAI, Anthropic, Ollama, custom tools |
| Capabilities | 4 documented | 4 documented |
LangChain
- +Largest open-source LLM/agent framework community with very broad integration coverage
- +Model-agnostic design future-proofs apps against LLM churn
- +LangGraph adds production-grade primitives (durability, checkpointing, human-in-the-loop) that bare API calls lack
- -Frequently criticized for heavy abstractions and churn between API versions; debugging deep chains can be painful
- -Most production value (observability, deploy) lives in the paid LangSmith platform
Letta
- +Genuinely differentiated memory architecture (self-editing memory blocks from MemGPT research, not a RAG wrapper)
- +Open source under Apache-2.0, self-hostable, and model-agnostic, which avoids lock-in
- +Strong developer ergonomics: REST API, Python and TypeScript SDKs, and the ADE GUI with deep state visibility
- -Positioning has become muddy across research lab, stateful-agents platform, and a Letta Code coding agent
- -Real usage costs climb well beyond the $20 Pro tier once LLM token pass-through is counted
Which should you choose?
LangChain is open-source framework and platform for building and deploying llm agents, best for developers, enterprise, mid-market. Letta is open-source framework for stateful ai agents with long-term memory, best for developers. The right choice depends on the autonomy level you want, your existing integrations, and your budget, all compared above.
This comparison is generated from the sourced LangChain and Letta profiles. Open either profile to review its evidence and last-reviewed date.