Mem0
Drop-in AI memory layer that persists context across sessions and agents.
At a glance
Price not confirmed · Source review 2026-11-04- Price & billing
Free plan for developers building and testing: first 30 days 10,000 adds and 1,000 retrievals a month, then 50,000 adds and 10,000 retrievals a month with your own LLM key; model calls are on Mem0 for 30 days, then use your LLM key. Custom is a custom-priced plan. No charge fact is recorded: the Free plan is stated without a $0 amount in the text read, and the Custom plan has no stated amount.
- Free allowance
Free plan for developers building and testing: first 30 days 10,000 adds and 1,000 retrievals a month, then 50,000 adds and 10,000 retrievals a month with your own LLM key; model calls are on Mem0 for 30 days, then use your LLM key. No charge fact is recorded: the Free plan is stated without a $0 amount in the text read, and the Custom plan has no stated amount.
- Best suited to
Developers building agents or apps that must remember user preferences and past facts across sessions instead of starting each conversation blank.; Teams that want memory as infrastructure, with add and search calls from an SDK rather than building their own store and retrieval layer.; Builders testing memory features first, since the pricing page describes a Free plan for developers building and testing with Mem0.
Fit is editorial guidance, not a measured result.- Platforms
Access: not separately verified. Operating systems not separately verified.
Published-source facts and editorial guidance. No product test is implied. Confirm current conditions before purchase.
No product screenshot is claimed for this listing. Use the official website ↗ to inspect the current interface.
What to know before choosing
Good fit
Developers building agents or apps that must remember user preferences and past facts across sessions instead of starting each conversation blank.; Teams that want memory as infrastructure, with add and search calls from an SDK rather than building their own store and retrieval layer.; Builders testing memory features first, since the pricing page describes a Free plan for developers building and testing with Mem0.
Limits and trade-offs
Teams that need graph memory, user profiles, memory consolidation, advanced analytics or an on-prem deployment on the free tier, since the pricing page reserves those for the Custom plan.; Builders who expect model calls to stay on Mem0 indefinitely, since the pricing page states model calls are on Mem0 for the first 30 days and then use your own LLM key.; Users looking for a no-code consumer chatbot, since Mem0 is presented as developer infrastructure with SDKs, an API and an agent harness.
Plans and free allowances
Free plan for developers building and testing: first 30 days 10,000 adds and 1,000 retrievals a month, then 50,000 adds and 10,000 retrievals a month with your own LLM key; model calls are on Mem0 for 30 days, then use your LLM key. Custom is a custom-priced plan. No charge fact is recorded: the Free plan is stated without a $0 amount in the text read, and the Custom plan has no stated amount.
Evidence
Official homepage ↗ (reviewed 2026-11-04), Official pricing page ↗ (reviewed 2026-11-04)
Official published documentation reviewed; not a product test
Dates: Last reviewed 2026-11-04. Last reviewed is the latest source or editorial review date; it is not a content-change date.
A closer look at Mem0
Mem0 is a drop-in memory layer for AI agents and apps: it stores and retrieves context so agents remember preferences and facts across sessions, with SDKs for Python and Node, an agent harness and plugin, and a managed cloud option alongside self-hosted use with your own LLM key.
Editorial guidance based on published documentation. The workflow below is a suggested starting point, not a measured product result.
When to choose Mem0
- Developers building agents or apps that must remember user preferences and past facts across sessions instead of starting each conversation blank.
- Teams that want memory as infrastructure, with add and search calls from an SDK rather than building their own store and retrieval layer.
- Builders testing memory features first, since the pricing page describes a Free plan for developers building and testing with Mem0.
When to choose something else
- Teams that need graph memory, user profiles, memory consolidation, advanced analytics or an on-prem deployment on the free tier, since the pricing page reserves those for the Custom plan.
- Builders who expect model calls to stay on Mem0 indefinitely, since the pricing page states model calls are on Mem0 for the first 30 days and then use your own LLM key.
- Users looking for a no-code consumer chatbot, since Mem0 is presented as developer infrastructure with SDKs, an API and an agent harness.
A practical starting workflow
- Install the SDK and create a memory client with your API key.
- Add memories with a user ID, for example a stated preference, using the same user ID for every later call.
- Search memories by question with a user-ID filter, then use the returned context in the agent's next reply.
Check before committing
- Free-plan limits change after the first 30 days: the pricing page lists 10,000 adds and 1,000 retrievals a month for the first 30 days, and 50,000 adds and 10,000 retrievals a month with your own LLM key.
- Usage past the free limits is usage-based billing with a monthly cap you set, so check the cap before running large volumes.
Common questions
What does Mem0 store?
Memories added through the SDK, retrieved by question and filtered by user ID, so an agent can recall a preference stated in an earlier session.
What does the Free plan include?
Unlimited end users, with 10,000 adds and 1,000 retrievals a month for the first 30 days, and 50,000 adds and 10,000 retrievals a month with your own LLM key.
What is reserved for Custom?
Higher limits, graph memory, user profiles, memory consolidation, advanced analytics, private Slack support, SSO, audit logs, SLA and on-prem deployment.
Compare approaches for this task
- MemMachine — Agent builders who want persistent memory across sessions, agents and models, with profile memory that improves personalisation over time.; Developers building locally who want a self-hosted open-source memory layer before paying for managed cloud hosting.; Teams building production agents who need higher rate limits, premium integrations and managed hosting on the Pro plan.
- MemoryLake — People and teams whose memory must work across many AIs and agents instead of being locked inside one chat product.; Claude Code and Codex users who want to install memory once and keep the same memory in the terminal.; Teams that want to meter memory use by token and pay on demand beyond a plan, rather than buying seats.
Sources and checks
Last source review is not a date of product testing. No rating or test result is implied by inclusion. Check the current plan and terms before buying.