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Free plan + paidInformation reviewed 2026-10-15

Letta

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About this listing

Product and access model reviewed from current official sources; workflow and example are editorial suggestions, not a hands-on test.

Official source

Build stateful AI agents that retain memory across sessions, with a web app, CLI workflow, and developer API.

Best suited to

Letta suits builders who need an agent to maintain context beyond one conversation.

Meet Letta

Letta suits builders who need an agent to maintain context beyond one conversation. Its memory-oriented approach separates durable agent state from a single prompt. The web app, CLI and developer platform serve different workflows. Test how memory changes and how tools act; remembering an earlier statement does not establish that the statement was correct.

A practical workflow

  1. Choose the web, CLI or API setup described in the quickstart.
  2. Configure a supported model connection and a narrowly scoped task.
  3. Run more than one session and inspect what the agent retains.
  4. Review memory changes and tool behavior before allowing consequential actions.

Illustrative input

This example describes a task, not a tested output. Adjust the source material and settings to your own situation.

Remember the supplied project conventions across sessions, distinguish approved facts from suggestions, and ask before changing a recorded requirement.

Result check: Check the stored memory and tool trace for incorrect assumptions, stale facts or an action beyond the task scope.

Access and alternatives

The continuing Free option has limited stateful agents and model usage, with supported bring-your-own-key or external coding-plan connections. Pro and developer API access have separate quotas or usage billing. Model tokens and server-side tools can add charges.

Choose another workflow when its emphasis fits better: Mastra for a TypeScript agent framework; LangSmith for tracing and evaluation of agent applications.

Illustrative workspace photo
Illustrative stock photo from Unsplash; not a screenshot of Letta.

What you can do

Stateful agents

Persistent agent memory

Web and CLI workflows

Tool connections

Developer API

Where it helps

  • Persistent state supports work across sessions
  • Several interfaces serve different development needs
  • Memory can be inspected as part of an agent review

What to consider

  • Free agents and hosted usage are limited
  • External models and tool execution can add separate charges

Pricing & free access

Official pricing
Free plan + paid

The continuing Free option has limited stateful agents and model usage, with supported bring-your-own-key or external coding-plan connections. Pro and developer API access have separate quotas or usage billing. Model tokens and server-side tools can add charges.

Plan information can change. Prices and conditions are set by the provider. Information checked 2026-10-15.

Source for access details

Weekly AI tool changes in AI Agents & Workflows

One email a week with pricing and feature changes in this category. No per-tool price alerts.

Questions about Letta

Who is Letta useful for?

Letta suits builders who need an agent to maintain context beyond one conversation. Its memory-oriented approach separates durable agent state from a single prompt. The web app, CLI and developer platform serve different workflows. Test how memory changes and how tools act; remembering an earlier statement does not establish that the statement was correct.

Does Letta have continuing free access?

The continuing Free option has limited stateful agents and model usage, with supported bring-your-own-key or external coding-plan connections. Pro and developer API access have separate quotas or usage billing. Model tokens and server-side tools can add charges.

How should I start a small evaluation?

Choose the web, CLI or API setup described in the quickstart. Configure a supported model connection and a narrowly scoped task.

What should I check in the result?

Check the stored memory and tool trace for incorrect assumptions, stale facts or an action beyond the task scope.

When should I choose a different workflow?

Mastra for a TypeScript agent framework; LangSmith for tracing and evaluation of agent applications.

Did this help you complete your task?

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Review evidence

Documentation-based review · 2026-10-15

Reviewed from the linked official documentation. The workflow and example are editorial suggestions; no account-level product test or measured performance comparison was performed.

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