Letta (formerly MemGPT): Free vs Paid — Is the Free Plan Enough?

⚡ Quick Verdict

Stay free if you only need 5,000 monthly credits and api access. Upgrade if you need saml/oidc sso and rbac. Most solo builders can start free.

Try Free Plan →Compare Plans ↓

Who Should Stay Free vs Who Should Upgrade

👤

Stay Free If You're...

✓Individual user
✓Basic needs only
✓Personal projects
✓Getting started
✓Budget-conscious

👤

Upgrade If You're...

✓Business professional
✓Advanced features needed
✓Team collaboration
✓Higher usage limits
✓Premium support

What Users Say About Letta (formerly MemGPT)

👍 What Users Love

✓Purpose-built for persistent agent memory, making it a stronger fit than stateless chat tools for assistants that need to remember users, preferences, and prior work across sessions.
✓Supports both cloud-hosted and self-hosted deployment according to the existing directory record, giving technical teams a path for managed usage or more direct infrastructure control.
✓Model-agnostic positioning allows teams to design around an agent memory layer instead of tying all context and behavior to a single LLM provider.
✓Its virtual context approach addresses a concrete limitation of LLM applications: important information can outlive the immediate context window instead of being lost between sessions.
✓The existing listing identifies 5 core feature areas, including persistent memory, virtual context, self-editing agents, document analysis beyond context limits, and multi-session conversation tracking.
✓Compared to broader agent frameworks in our directory, Letta has a clearer focus on long-running, stateful agents rather than general workflow orchestration.

👎 Common Concerns

⚠The provided scraped website content did not expose complete current customer counts, founding year, or integration counts, so buyers should verify commercial details before procurement.
⚠Persistent memory adds design and governance complexity because teams must decide what agents should store, retrieve, update, or forget over time.
⚠Usage-based charges on the API Plan, including $0.10 per active agent per month and $0.00015 per second for server-side tool execution, can make costs harder to forecast for high-volume applications.
⚠Self-hosted deployment can require engineering resources for installation, model provider configuration, monitoring, upgrades, and data management.
⚠Letta is more specialized than broad frameworks like LangChain or Semantic Kernel, so teams that mainly need general tool orchestration may find its memory-first focus narrower.

🔒 What Free Doesn't Include

🎯 Unlimited agents

Why it matters: The provided scraped website content did not expose complete current customer counts, founding year, or integration counts, so buyers should verify commercial details before procurement.

Available from: API Plan

🎯 $0.10 per active agent per month

Why it matters: Persistent memory adds design and governance complexity because teams must decide what agents should store, retrieve, update, or forget over time.

Available from: API Plan

🎯 $0.00015 per second for server-side tool execution

Why it matters: Usage-based charges on the API Plan, including $0.10 per active agent per month and $0.00015 per second for server-side tool execution, can make costs harder to forecast for high-volume applications.

Available from: API Plan

🎯 Pay-as-you-go LLM usage

Why it matters: Self-hosted deployment can require engineering resources for installation, model provider configuration, monitoring, upgrades, and data management.

Available from: API Plan

🎯 API access for production agent development

Why it matters: Letta is more specialized than broad frameworks like LangChain or Semantic Kernel, so teams that mainly need general tool orchestration may find its memory-first focus narrower.

Available from: API Plan

Frequently Asked Questions

What is Letta best used for?

Letta is best suited for AI agents that need continuity across sessions rather than one-off responses. Practical examples include customer assistants that remember prior issues, research agents that maintain source notes, and developer assistants that retain project context.

How is Letta different from LangChain or other agent frameworks?

Letta is focused on stateful agents and persistent memory, while frameworks like LangChain and Semantic Kernel are broader tools for building LLM workflows. Teams may use Letta when memory is the defining requirement rather than general orchestration.

Can Letta be self-hosted?

The existing directory record indicates that Letta offers both cloud-hosted and self-hosted deployment options. Self-hosting is most relevant for teams that need greater control over infrastructure, data handling, or model-provider configuration.

How much does Letta cost?

Letta has a free tier at $0/month with 5,000 monthly credits, API access, visual agent editing in the ADE, 2 agent templates, and 1 GB of storage. The API Plan is listed at $20/month and includes unlimited agents, with additional usage-based charges.

What are the main risks of using persistent memory in an AI agent?

Persistent memory can make agents more useful, but it also creates product and governance risks. Stored memories may become outdated, incorrect, overly sensitive, or misapplied, so teams should design review, correction, and deletion workflows.

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More about Letta (formerly MemGPT)

Pricing Review Alternatives Pros & Cons Worth It?Tutorial

📖 Letta (formerly MemGPT) Overview 💰 Letta (formerly MemGPT) Pricing & Plans ⚖️ Is Letta (formerly MemGPT) Worth It?🔄 Compare Letta (formerly MemGPT) Alternatives

Last verified March 2026

What Users Say About Letta (formerly MemGPT)

👍 What Users Love

✓Purpose-built for persistent agent memory, making it a stronger fit than stateless chat tools for assistants that need to remember users, preferences, and prior work across sessions.
✓Supports both cloud-hosted and self-hosted deployment according to the existing directory record, giving technical teams a path for managed usage or more direct infrastructure control.
✓Model-agnostic positioning allows teams to design around an agent memory layer instead of tying all context and behavior to a single LLM provider.
✓Its virtual context approach addresses a concrete limitation of LLM applications: important information can outlive the immediate context window instead of being lost between sessions.
✓The existing listing identifies 5 core feature areas, including persistent memory, virtual context, self-editing agents, document analysis beyond context limits, and multi-session conversation tracking.
✓Compared to broader agent frameworks in our directory, Letta has a clearer focus on long-running, stateful agents rather than general workflow orchestration.

👎 Common Concerns

⚠The provided scraped website content did not expose complete current customer counts, founding year, or integration counts, so buyers should verify commercial details before procurement.
⚠Persistent memory adds design and governance complexity because teams must decide what agents should store, retrieve, update, or forget over time.
⚠Usage-based charges on the API Plan, including $0.10 per active agent per month and $0.00015 per second for server-side tool execution, can make costs harder to forecast for high-volume applications.
⚠Self-hosted deployment can require engineering resources for installation, model provider configuration, monitoring, upgrades, and data management.
⚠Letta is more specialized than broad frameworks like LangChain or Semantic Kernel, so teams that mainly need general tool orchestration may find its memory-first focus narrower.

🔒 What Free Doesn't Include

🎯 Unlimited agents

Available from: API Plan

🎯 $0.10 per active agent per month

Why it matters: Persistent memory adds design and governance complexity because teams must decide what agents should store, retrieve, update, or forget over time.

Available from: API Plan

🎯 $0.00015 per second for server-side tool execution

Available from: API Plan

🎯 Pay-as-you-go LLM usage

Why it matters: Self-hosted deployment can require engineering resources for installation, model provider configuration, monitoring, upgrades, and data management.

Available from: API Plan

🎯 API access for production agent development

Why it matters: Letta is more specialized than broad frameworks like LangChain or Semantic Kernel, so teams that mainly need general tool orchestration may find its memory-first focus narrower.