Letta vs Mem0
Detailed side-by-side comparison to help you choose the right tool
Letta
π΄DeveloperAgent Framework
Stateful agent framework and cloud from the MemGPT team β agents that actually remember across sessions.
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Starting Price
FreeMem0
π΄DeveloperAgent Memory
Persistent memory infrastructure that lets AI applications add, update, and retrieve useful context across sessions.
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Starting Price
$0/monthFeature Comparison
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π‘ Our Take
Choose Letta if you need a full stateful-agent runtime with memory blocks, tools, API deployment, coding-agent workflows, and agent portability. Choose Mem0 if you mainly need a memory layer to plug into an existing agent stack.
Letta - Pros & Cons
Pros
- βPersistent, editable memory is built into the agent runtime
- βADE exposes agent state and tool calls for debugging
- βPython, TypeScript, REST, multiple model providers, and MCP offer flexible integration
- βOpen-source self-hosting avoids mandatory platform lock-in
Cons
- βStateful agents add privacy, retention, deletion, and migration responsibilities
- βCloud plan and model usage can create separate cost layers
- βMemory quality still depends on prompts, models, and application-specific evaluation
Mem0 - Pros & Cons
Pros
- βFocused add-and-search API can be integrated without building a complete memory pipeline.
- βPublished request limits make cloud capacity and cost easier to estimate.
- βFree and $19 tiers support prototypes before a larger production commitment.
- βEnterprise offers on-premises deployment, audit logs, SSO, and SLA support.
Cons
- βThe jump from $19 Starter to $249 Pro is substantial for teams needing graph memory or multiple projects.
- βPersistent memory creates privacy, consent, retention, and deletion obligations.
- βRetrieval quality and cross-user isolation must be tested on the buyer's own data.
- βMem0 adds a stateful production dependency alongside the model provider and application database.
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π― Take our quiz βπ Security & Compliance Comparison
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