Comparison
letta vs mem0
Verdict
Pick letta if letta is a Python-based platform designed to foster the development of stateful AI agents with capabilities for advanced memory techniques that support continuous learning and self-improvement. The Apache-2.0 license it鳧; pick mem0 if mem0 is a Python-based memory infrastructure for AI agents and applications, offering a persistent context layer suitable for production environments.
Markdown twin · letta alternatives · mem0 alternatives
GraphCanon updated Sep 20, 2026
18views this month
Trust & integrity
| Signal | letta | mem0 |
|---|---|---|
| Maintenance | Very active (0d since push) As of Aug 17, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Aug 17, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- letta
- Platform for stateful agents: AI with advanced memory that can learn and self-improve over time.
- mem0
- Drop-in memory infrastructure for AI agents and apps
Stars
- letta
- 24k
- mem0
- 66k
Forks
- letta
- 2.6k
- mem0
- 7.7k
Open issues
- letta
- 41
- mem0
- 754
Language
- letta
- -
- mem0
- Python
Adopt for
- letta
- letta is a Python-based platform designed to foster the development of stateful AI agents with capabilities for advanced memory techniques that support continuous learning and self-improvement. The Apache-2.0 license it鳧
- mem0
- mem0 is a Python-based memory infrastructure for AI agents and applications, offering a persistent context layer suitable for production environments.
Persona
- letta
- -
- mem0
- -
Runtime
- letta
- -
- mem0
- -
License
- letta
- letta operates under the Apache-2.0 license.
- mem0
- mem0 is distributed under the Apache-2.0 license, allowing for broad usage and modification with attribution.
Last pushed
- letta
- Aug 16, 2026
- mem0
- Sep 18, 2026
Categories
- letta
- AI Agents
- mem0
- AI Agents, Data & Retrieval
Trust and health
Open issues (now)
- letta
- 41
- mem0
- 754
Stars delta
- letta
- +443 (30d)
- mem0
- +2.8k (30d)
Open issues delta
- letta
- -8 (30d)
- mem0
- +63 (30d)
Full report
- letta
- Trust report
- mem0
- Trust report
Typed relationship
letta alternative mem0Mem0 is designed as a universal memory layer for AI Agents, similar to the advanced memory components in Letta agents.
Shared compatibility
- Node.js · letta: Node.js runtime · mem0: Node.js runtime
Choose letta if…
- Mem0 is designed as a universal memory layer for AI Agents, similar to the advanced memory components in Letta agents.
- Tags unique to letta: advanced memory, agents development framework, self-improving ai, stateful ai.
- When you require an AI agent with robust memory features that enable continuous learning and adaptation over time.
When NOT to use letta
- If you are looking for a simple stateless AI solution without advanced memory capabilities, as letta is geared towards more complex stateful agent development.
- When your project's requirements involve strict limitations around data retention and privacy where even anonymized interaction logs might be considered sensitive.
Choose mem0 if…
- Pricing: The core functionality of mem0 is free to use under the Apache-2.0 license, but additional features or support might come at a cost..
- Requirements: Min 2 GB RAM; Python environment is required for installation and use..
- Mem0 is designed as a universal memory layer for AI Agents, similar to the advanced memory components in Letta agents.
- Tags unique to mem0: agentic-memory, ai-agents, genai, long-term-memory.
- Also covers Data & Retrieval.
- When you need a persistent memory layer for AI agents that can be easily integrated into existing applications without significant changes.
When NOT to use mem0
- If your project is not in Python, as mem0 is specifically designed for Python environments.
- When you require a more customizable memory management system that allows for extensive configuration beyond what mem0 offers.
- If your application does not need a persistent memory layer or if the existing memory management solutions are sufficient.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (letta-ai/letta) · observed Sep 20, 2026
- GitHub forks (letta-ai/letta) · observed Sep 20, 2026
- Last push (letta-ai/letta) · observed Aug 16, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (mem0ai/mem0) · observed Sep 20, 2026
- GitHub forks (mem0ai/mem0) · observed Sep 20, 2026
- Last push (mem0ai/mem0) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: letta 24k · mem0 66k (synced Sep 20, 2026).
Common questions
- What is the difference between letta and mem0?
- letta: Platform for stateful agents: AI with advanced memory that can learn and self-improve over time.. mem0: Drop-in memory infrastructure for AI agents and apps. See the comparison table for live GitHub stats and shared categories.
- When should I choose letta over mem0?
- Choose letta over mem0 when Mem0 is designed as a universal memory layer for AI Agents, similar to the advanced memory components in Letta agents; Tags unique to letta: advanced memory, agents development framework, self-improving ai, stateful ai; When you require an AI agent with robust memory features that enable continuous learning and adaptation over time.
- When should I choose mem0 over letta?
- Choose mem0 over letta when Pricing: The core functionality of mem0 is free to use under the Apache-2.0 license, but additional features or support might come at a cost.; Requirements: Min 2 GB RAM; Python environment is required for installation and use.; Mem0 is designed as a universal memory layer for AI Agents, similar to the advanced memory components in Letta agents; Tags unique to mem0: agentic-memory, ai-agents, genai, long-term-memory; Also covers Data & Retrieval; When you need a persistent memory layer for AI agents that can be easily integrated into existing applications without significant changes.
- When should I avoid letta?
- If you are looking for a simple stateless AI solution without advanced memory capabilities, as letta is geared towards more complex stateful agent development. When your project's requirements involve strict limitations around data retention and privacy where even anonymized interaction logs might be considered sensitive.
- When should I avoid mem0?
- If your project is not in Python, as mem0 is specifically designed for Python environments. When you require a more customizable memory management system that allows for extensive configuration beyond what mem0 offers. If your application does not need a persistent memory layer or if the existing memory management solutions are sufficient.
- Is letta or mem0 more popular on GitHub?
- mem0 has more GitHub stars (65,557 vs 24,274). Stars measure visibility, not whether either tool fits your constraints.
- Are letta and mem0 open source?
- Yes - both are open-source projects on GitHub (letta: Apache-2.0, mem0: Apache-2.0).
- Where can I find alternatives to letta or mem0?
- GraphCanon lists graph-backed alternatives at letta alternatives and mem0 alternatives (letta markdown twin, mem0 markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, letta or mem0?
- letta: Very active. mem0: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for letta and mem0?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: letta trust report; mem0 trust report.