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syzsunshine219 merged 2 commits into from
Jun 11, 2026
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docs: Add FAQ section for common questions about MemOS Memory OS #1732

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docs: Add FAQ section for common questions about MemOS Memory OS
meichuanyi May 14, 2026
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docs: Add FAQ section for common questions
meichuanyi May 23, 2026
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Expand Up @@ -262,6 +262,126 @@ Your lobsters and Hermes Agents now have **the best** memory system — choose *

<br>


## FAQ

### What is MemOS?

MemOS is a **Memory Operating System** for LLMs and AI agents that unifies store/retrieve/manage for long-term memory. It enables context-aware and personalized interactions with knowledge base (KB), multi-modal memory, tool memory, and enterprise-grade optimizations built in.

### What are the benchmark results?

| Benchmark | MemOS Result | Improvement |
|-----------|--------------|-------------|
| LoCoMo | 75.80 | - |
| LongMemEval | +40.43% vs baseline | - |
| PrefEval-10 | +2568% | - |
| PersonaMem | +40.75% | - |
| **vs OpenAI Memory** | +43.70% Accuracy | - |
| **Token Savings** | 35.24% | - |

### How does MemOS compare to other memory solutions?

| Feature | MemOS | mem0 | LangChain Memory | Letta |
|---------|-------|------|------------------|-------|
| Multi-Modal Memory | ✅ Text/Images/Tools | ❌ Text only | ❌ Text only | ❌ Text only |
| Knowledge Base | ✅ Multi-Cube KB | ❌ No KB | ⚠️ RAG only | ❌ No KB |
| Memory Feedback | ✅ Natural language | ❌ No | ❌ No | ❌ No |
| Graph Memory | ✅ Inspectable/Editable | ❌ Black-box | ❌ Black-box | ❌ Limited |
| Async Ingestion | ✅ MemScheduler | ❌ No | ❌ No | ❌ No |
| Open Source | ✅ Apache 2.0 | ✅ MIT | ✅ Apache | ✅ MIT |
| ArXiv Paper | ✅ 2507.03724 | ❌ No | ❌ No | ❌ No |
Comment on lines +283 to +293

@shinetata shinetata Jun 11, 2026

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remove the "How does MemOS compare to other memory solutions?" table. It isn't sourced and contains factual errors about peers, which is risky in an official README.

Suggested change
### How does MemOS compare to other memory solutions?
| Feature | MemOS | mem0 | LangChain Memory | Letta |
|---------|-------|------|------------------|-------|
| Multi-Modal Memory | ✅ Text/Images/Tools | ❌ Text only | ❌ Text only | ❌ Text only |
| Knowledge Base | ✅ Multi-Cube KB | ❌ No KB | ⚠️ RAG only | ❌ No KB |
| Memory Feedback | ✅ Natural language | ❌ No | ❌ No | ❌ No |
| Graph Memory | ✅ Inspectable/Editable | ❌ Black-box | ❌ Black-box | ❌ Limited |
| Async Ingestion | ✅ MemScheduler | ❌ No | ❌ No | ❌ No |
| Open Source | ✅ Apache 2.0 | ✅ MIT | ✅ Apache | ✅ MIT |
| ArXiv Paper | ✅ 2507.03724 | ❌ No | ❌ No | ❌ No |
### Why MemOS?
- **Inspectable, editable graph memory** — not a black-box embedding store.
- **Multi-modal**: text, images, tool traces, and personas in one system.
- **Multi-Cube knowledge base** with isolation and controlled cross-user / project / agent sharing.
- **Asynchronous ingestion** via MemScheduler with millisecond-level latency.
- **Natural-language memory feedback** to correct, supplement, or replace memories over time.
- **Open source (Apache 2.0)**, with a published method ([arXiv:2507.03724](https://arxiv.org/abs/2507.03724)).


### What are the key features?

| Feature | Description |
|---------|-------------|
| **Unified Memory API** | Single API for add/retrieve/edit/delete, graph-structured, inspectable |
| **Multi-Modal Memory** | Text, images, tool traces, personas retrieved together |
| **Multi-Cube KB** | Composable memory cubes for users/projects/agents |
| **Async Ingestion** | MemScheduler with millisecond latency |
| **Memory Feedback** | Natural-language correction/supplement/replacement |
| **Self-evolving Memory** | L1 traces, L2 policies, L3 world model, crystallized Skills |

### What deployment options are available?

| Option | Description |
|--------|-------------|
| **Cloud API** | Hosted service at memos.openmem.net |
| **Self-Hosted** | Local/private deployment via Docker |
| **Quick Mode** | Lightweight deployment |
| **Full Mode** | Complete deployment |

### How do I get started with Cloud API?

1. Sign up at [MemOS dashboard](https://memos-dashboard.openmem.net/)
2. Go to **API Keys** and copy your key
3. Use the Cloud API for memory operations

See [Cloud Getting Started](https://memos-docs.openmem.net/memos_cloud/quick_start/).

### How do I self-host MemOS?

```bash
# Clone
git clone https://github.com/MemTensor/MemOS.git
cd MemOS

# Install dependencies
pip install -r ./docker/requirements.txt

# Configure .env (OPENAI_API_KEY, etc.)
cp docker/.env.example MemOS/.env

# Start service
# See docs for full setup
Comment on lines +333 to +337

@shinetata shinetata Jun 11, 2026

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fix the .env copy path and add the actual start command.

Suggested change
# Configure .env (OPENAI_API_KEY, etc.)
cp docker/.env.example MemOS/.env
# Start service
# See docs for full setup
# Configure .env (already inside the MemOS repo root after `cd MemOS`)
cp docker/.env.example .env
# Start the service (run from the docker directory)
cd docker && docker compose up

```

### What LLM providers are supported?

| Provider | Setting |
|----------|---------|
| OpenAI | `MOS_CHAT_MODEL_PROVIDER=openai` |
| Azure OpenAI | `MOS_CHAT_MODEL_PROVIDER=azure` |
| Qwen (DashScope) | `MOS_CHAT_MODEL_PROVIDER=qwen` |
| DeepSeek | `MOS_CHAT_MODEL_PROVIDER=deepseek` |
| MiniMax | `MOS_CHAT_MODEL_PROVIDER=minimax` |
| Ollama | `MOS_CHAT_MODEL_PROVIDER=ollama` |
| HuggingFace | `MOS_CHAT_MODEL_PROVIDER=huggingface` |
| vLLM | `MOS_CHAT_MODEL_PROVIDER=vllm` |

### What plugins are available?

| Plugin | Purpose |
|--------|---------|
| **memos-local-plugin 2.0** | Local-first memory for Hermes Agent & OpenClaw |
| **OpenClaw Cloud Plugin** | Hosted memory service, 72% token reduction |
| **OpenClaw Local Plugin** | 100% on-device SQLite memory |

### What is the memory architecture?

@shinetata shinetata Jun 11, 2026

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label it as the memos-local-plugin 2.0 self-evolving model, since it's not MemOS core's general storage.

Suggested change
### What is the memory architecture?
### What is the self-evolving memory architecture? (memos-local-plugin)
> This is the self-evolving memory model used by `memos-local-plugin 2.0`, not MemOS core's general storage layer.


| Layer | Purpose |
|-------|---------|
| **L1 Traces** | Raw interaction history |
| **L2 Policies** | Learned preferences/behaviors |
| **L3 World Model** | User understanding |
| **Crystallized Skills** | Reusable patterns |

### What license does MemOS use?

Apache 2.0 License (see [LICENSE](./LICENSE)).

### Where can I get help?

| Resource | Link |
|----------|------|
| Documentation | [memos-docs.openmem.net](https://memos-docs.openmem.net/home/overview/) |
| ArXiv Paper | [2507.03724](https://arxiv.org/abs/2507.03724) |
| Discord | [Join Server](https://discord.gg/Txbx3gebZR) |
| X/Twitter | [@MemOS_dev](https://x.com/MemOS_dev) |
| GitHub Issues | [Submit issues](https://github.com/MemTensor/MemOS/issues) |
| Awesome-AI-Memory | [IAAR-Shanghai/Awesome-AI-Memory](https://github.com/IAAR-Shanghai/Awesome-AI-Memory) |

## 📚 Resources

- **Awesome-AI-Memory**
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