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Letta vs Memobase

A side-by-side comparison of Letta and Memobase, two Memory tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

Letta

Memory

Stateful agents with structured memory. Successor to MemGPT.

View Letta

Memobase

Memory

User profile-based long-term memory for LLM applications.

View Memobase

At a glance

Feature comparison of Letta and Memobase
AttributeLettaMemobase
CategoryMemoryMemory
PricingFREEMIUMFREEMIUM
LicenseOpen coreOpen core
DeploymentHybridHybrid
Platforms (differs)API, CLI, macOS, Windows, LinuxAPI
Model supportBYO key / modelBYO key / model
Vendor (differs)LettaMemobase

The honest brief

Letta

The productized MemGPT successor — agents edit their own memory blocks (memory-as-OS) to manage a finite context window.

  • Self-editing agent memory
  • Open source, model-agnostic
  • REST APIs + multi-language SDKs
  • Reference architecture for memory
  • Developer-focused, not no-code
  • Memory model has a learning curve
  • Younger, evolving framework

Memobase

Models memory as a structured user profile plus timestamped event timeline — tops LOCOMO temporal-reasoning (~85%).

  • Distills chats, not raw embeddings
  • Strong temporal-reasoning benchmark
  • Low-latency on FastAPI/Postgres/Redis
  • Python/Node/Go SDKs + MCP server
  • Smaller community than mem0/Zep
  • Profile schema needs upfront design
  • Less production-server tooling than Zep
  • Newer, less battle-tested