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.