Memos
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings
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What is Memos?
MemOS is a memory management operating system for AI applications that gives artificial intelligence continuous memory and growth capabilities. It provides a unified memory-management substrate for AGI, enabling intelligent systems to possess adaptable, transferable, and shareable long-term and instant memories like the human brain. The platform delivers production-grade memory service with millisecond-level response times, making it suitable for enterprise deployments requiring highly available, scalable memory infrastructure.
Key features include a structured memory architecture that unifies parametric, activation, and plaintext memory into a multi-tiered system, enabling dynamic retrieval, updates, and composed memory operations. MemOS employs predictive and asynchronous scheduling to preload relevant memory based on dialogue history, task semantics, or environmental cues. The Memory Interchange Protocol (MIP) enables memory sharing across models, devices, sessions, and applications. The framework includes an Application & API Layer for unified memory operations, a Memory Scheduling Layer, and a Storage & Substrate Layer supporting containerized user, expert, and domain memory.
MemOS is designed for developers building AI applications across universal AI companions, games, education, financial services, industrial applications, e-commerce, healthcare, legal services, enterprise knowledge management, and customer support. It supports long-term assistants that remember user preferences, multi-scenario task coordination retaining memory across tools, and intelligent agent collaboration with memory sharing or isolation. The platform is model-agnostic and compatible with Agent frameworks, RAG setups, and major model ecosystems.
The product ecosystem includes MemOS Cloud (ready-to-use cloud memory service with 5-minute integration), MemOS Lite (lightweight local-first memory service with zero cloud dependency), and the official open-source version. Enterprise deployment supports public cloud, private cloud, on-premises, and hybrid architectures, seamlessly connecting with existing data and model frameworks.
Memos pricing
Pricing model: Freemium
MemOS offers four pricing tiers. Free tier: $0/month with 50K add per month, 20K search per month, 3M input tokens, 1M output tokens, 10 Knowledge Base items at 1G each, community support. Starter tier: $0/month (originally $19) with 600K add per month, 200K search per month, 12M input tokens, 4M output tokens, 30 Knowledge Base items at 10G each, community support. Pro tier: $0/month (originally $286) with 80M add per month, 30M search per month, 90M input tokens, 30M output tokens, 100 Knowledge Base items at 100G each, dedicated support. Enterprise tier: Custom pricing with unlimited Memory API, unlimited Chat API, unlimited Knowledge Base, private deployment, custom integration, and lower latency.
Memos pros
- Millisecond-level response times for production-grade performance
- Unified memory architecture combining parametric, activation, and plaintext memory
- Memory Interchange Protocol (MIP) for cross-model and cross-device memory sharing
- Predictive and asynchronous scheduling preloads memory before needed
- Model-agnostic compatibility with Agent frameworks and RAG setups
- Full lifecycle memory control including CRUD, batch cleanup, tagging, and governance
- Supports public cloud, private cloud, on-premises, and hybrid deployment
- 5-minute integration with just a few lines of code
- Consistent low latency even under heavy concurrency
- Persistent memory reduces Token usage in AI applications
- Cross-session persistent memory for personalized AI experiences
- Dynamic knowledge graph for structured memory management
- Intent-aware scheduling based on dialogue history and task semantics
- Scalable from startups to large enterprises seamlessly
- Open-source version available with deep customization support
Memos cons
- Primarily designed for AI/LLM applications, not general users
- Complex architecture may require specialized knowledge to implement
- Free tier has limited token quotas for production use
- Cloud dependency for MemOS Cloud version (not fully local)
- Enterprise features require custom pricing negotiations
- Learning curve for understanding memory scheduling layers
- Documentation may be sparse for advanced customization scenarios
- Limited to AI application ecosystems, not standalone note-taking
Frequently asked questions about Memos
What is MemOS?
MemOS is a memory management operating system for AI applications that provides scalable memory for AI, ensuring consistent understanding and personalization across tasks and scenarios. It is a Memory-Native Framework for Building Intelligent Systems that Remember, Adapt, and Evolve, unifying parametric, activation, and plaintext memory into a structured, multi-tiered architecture.
How fast is MemOS?
MemOS provides production-grade memory service with millisecond-level response times. Whether adding or searching memory, requests complete in milliseconds, with each call being stable and reliable, ensuring every response is fast and predictable even at enterprise scale.
What benchmarks does MemOS perform well on?
MemOS is evaluated on the LoCoMo Benchmark with LLM-as-a-Judge Metrics, reporting average scores across Temporal Reasoning, Multi-Hop, Open-Domain, and Single-Hop tasks. It achieves SOTA (State-of-the-Art) performance on these benchmarks.
What deployment options does MemOS support?
MemOS supports multi-scenario deployment including public cloud, private cloud, on-premises, and hybrid architectures. This meets the needs of teams from startups to large enterprises, seamlessly connecting with existing data and model frameworks without changing existing infrastructure.
What is the Memory Interchange Protocol (MIP)?
The Memory Interchange Protocol (MIP) enables MemOS to share and transfer memory across models, devices, sessions, and applications through a unified protocol. This makes memory persistent and portable for collaboration and adaptability between different AI systems.
What is the difference between MemOS Cloud and MemOS Lite?
MemOS Cloud is a ready-to-use cloud memory service with 5-minute integration and millisecond response. MemOS Lite is a lightweight memory service for local-first scenarios with zero cloud dependency, fully local runtime, designed specifically for Agent workflows.
Can MemOS reduce Token usage in AI applications?
Yes, MemOS reduces Token usage by injecting cloud persistent memory into applications like OpenClaw. The persistent memory plus skill evolution in the local plugin also lowers Token usage while operating fully locally.
What industries can use MemOS?
MemOS is suitable for all intelligent application ecosystems including Universal AI, Companion, Game, Education, Financial, Industrial, E-commerce, Healthcare, Legal, Enterprise Knowledge, and Customer Support applications.
What support options are available?
Free and Starter tiers include community support. Pro tier includes dedicated support. Enterprise tier offers custom integration and lower latency. There is also a Developer Support Program for Unlimited Chat API Tokens for those who need more than the standard plans provide.
How do I get started with MemOS?
You can activate MemOS with just a few lines of code in minutes to add long-term memory to your AI. The Memory APIs are ready to use, and you can join the OpenMem Open Source community which is dedicated to advancing memory-centered AI systems.