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← Back to Letta Overview

Letta Pricing & Plans 2026

Complete pricing guide for Letta. Compare all plans, analyze costs, and find the perfect tier for your needs.

Try Letta Free →Compare Plans ↓

Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether Letta is worth it →

🆓Free Tier Available
💎2 Paid Plans
⚡No Setup Fees

Choose Your Plan

Open Source

Free

forever

Unlimited local use

  • ✓Self-hosted
  • ✓Core features
  • ✓Community support
Start Free →
Most Popular

Cloud / Pro

Check website for pricing

month

Usage-based

  • ✓Managed hosting
  • ✓Dashboard
  • ✓Team features
  • ✓Priority support
Start Free Trial →

Enterprise

Contact sales

month

Unlimited

  • ✓SSO/SAML
  • ✓Dedicated support
  • ✓Custom SLA
  • ✓Advanced security
Contact Sales →

Pricing sourced from Letta · Last verified March 2026

Feature Comparison

FeaturesOpen SourceCloud / ProEnterprise
Self-hosted✓✓✓
Core features✓✓✓
Community support✓✓✓
Managed hosting—✓✓
Dashboard—✓✓
Team features—✓✓
Priority support—✓✓
SSO/SAML——✓
Dedicated support——✓
Custom SLA——✓
Advanced security——✓

Is Letta Worth It?

✅ Why Choose Letta

  • • Self-directed memory management means the agent adapts its memory strategy to each conversation instead of using fixed retrieval patterns
  • • Truly persistent and stateful agents that maintain context, memory, and state across unlimited interactions
  • • Multi-agent architecture with independent agent state and inter-agent communication support
  • • Agent Development Environment (ADE) provides a visual interface for building and testing agents
  • • Research-backed approach (MemGPT paper) with demonstrated effectiveness for long-context memory management

⚠️ Consider This

  • • Self-directed memory management can be unpredictable — agents sometimes miss relevant memories or make unnecessary updates
  • • Server-based architecture adds operational complexity compared to stateless agent frameworks
  • • Transition from research project to production platform means some features are polished while others feel experimental
  • • Higher learning curve than simpler frameworks — understanding the memory hierarchy is essential for effective use

What Users Say About Letta

👍 What Users Love

  • ✓Self-directed memory management means the agent adapts its memory strategy to each conversation instead of using fixed retrieval patterns
  • ✓Truly persistent and stateful agents that maintain context, memory, and state across unlimited interactions
  • ✓Multi-agent architecture with independent agent state and inter-agent communication support
  • ✓Agent Development Environment (ADE) provides a visual interface for building and testing agents
  • ✓Research-backed approach (MemGPT paper) with demonstrated effectiveness for long-context memory management

👎 Common Concerns

  • ⚠Self-directed memory management can be unpredictable — agents sometimes miss relevant memories or make unnecessary updates
  • ⚠Server-based architecture adds operational complexity compared to stateless agent frameworks
  • ⚠Transition from research project to production platform means some features are polished while others feel experimental
  • ⚠Higher learning curve than simpler frameworks — understanding the memory hierarchy is essential for effective use

Pricing FAQ

What happened to MemGPT? Is Letta the same thing?

Letta is the production platform that evolved from the MemGPT research project. The core concept (LLM-managed virtual memory) is the same, but Letta adds a server architecture, REST API, ADE, multi-agent support, and production deployment features that weren't in the original MemGPT.

How does Letta's memory compare to RAG?

RAG retrieves relevant documents using vector similarity. Letta gives the agent active control over its memory — it decides what to store, search, update, and forget. RAG is passive retrieval; Letta is active memory management. They can be complementary, with archival memory functioning like a RAG-accessible store.

Can Letta agents run on local/open-source LLMs?

Yes. Letta supports OpenAI, Anthropic, local models via Ollama or vLLM, and other providers. However, self-directed memory management requires strong instruction-following capabilities, so smaller open-source models may not manage memory as effectively as GPT-4 or Claude.

Is Letta suitable for production use?

It's being used in production by some teams, particularly for persistent assistant use cases. The server architecture is designed for production, but some features are still maturing. Evaluate carefully for your specific use case and plan for the operational complexity of running stateful agent servers.

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