Letta
Build agents that actually remember — facts, preferences, and past interactions persist across every session without manual context management.
Letta — the verdict: Developers building agents that need to remember and update facts across arbitrarily long interaction histories Letta solves the problem that most agent memory implementations patch over: agents that need to remember and update facts across sessions without manual context management. Pricing: Open source / Free (Letta Cloud from $0.02/step). Last reviewed: August 2026.
Best For
Developers building agents that need to remember and update facts across arbitrarily long interaction histories
Standout Feature
Manages its own memory tiers and decides what to retain or summarize, more reliable than an ad-hoc RAG memory hack
Verdict
A genuinely more solid approach to agent memory than manual context management, per-step cloud pricing adds up for memory-heavy agents.
Alternatives
Overview
Letta (formerly MemGPT) is an agent framework built around stateful long-term memory — agents remember facts across sessions, update their knowledge as conversations evolve, and recall relevant context from arbitrarily long interaction histories. Each agent manages its own memory tiers (working, recall, and archival) and decides what to retain or summarize, solving the context-window problem at the framework level rather than prompting around it.
Our Take
Letta solves the problem that most agent memory implementations patch over: agents that need to remember and update facts across sessions without manual context management. The framework manages its own memory tiers and decides what to retain or summarize, which is more reliable than stitching together a RAG pipeline as an afterthought. The open-source core keeps you in control of your data. The cost consideration is real: per-step cloud pricing accumulates quickly for memory-heavy agents with frequent reads. Run your expected usage through the pricing model before committing to Letta Cloud for production.
Key Features
- Three-tier memory architecture: working, recall, and archival
- Self-directed memory management — agents decide what to store
- Cross-session persistence with no manual prompt engineering
- REST API and Python SDK for embedding agents in applications
- Agent builder UI for configuring memory and persona
- Open-source core with managed Letta Cloud option
- • Solves long-term memory without external memory databases or prompting tricks
- • Open-source core means full control over data and deployment
- • Framework-level memory is more reliable than ad-hoc RAG approaches
- • Memory management adds latency compared to stateless agents
- • Cloud pricing is per-step — complex agents with many memory reads get expensive
- • Steeper learning curve than simpler stateless frameworks
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