# QwenPaw vs OpenClaw: Feature Comparison

| Category            | Dimension                       | OpenClaw                                                                                                                                                                                                                                                                                     | QwenPaw                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| :------------------ | :------------------------------ | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :  |
| Tech Stack          | Primary Language                | TypeScript / Node.js                                                                                                                                                                                                                                                                         | Python                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
|                     | Agent Framework                 | • [Pi agent runtime](https://docs.openclaw.ai/concepts/agent)                                                                                                                                                                                                                                | • [AgentScope](https://github.com/agentscope-ai/agentscope)<br>• [AgentScope-Runtime](https://github.com/agentscope-ai/agentscope-runtime)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         |
|                     | Memory System                   | • Workspace file memory<br>• Session model: group isolation, context compaction (`/compact`), and [session pruning](https://docs.openclaw.ai/concepts/session-pruning)                                                                                                                       | • Long-term workspace memory powered by [ReMe](https://github.com/agentscope-ai/ReMe)<br>• Layered context: key information and recent turns in memory; history, rolling summaries, and tool outputs persisted<br>• Dynamic compaction before inference: prioritize recent high-signal content; compress older content into structured summaries with indexed recall to originals when needed<br>• Time-tiered compression of tool outputs to save tokens<br>• Hybrid retrieval: vector search + full-text search (e.g. BM25)<br>• Structured summaries and long-term memory files for user preferences and task experience<br>• Per-role memory isolation in multi-agent setups to reduce cross-task interference                 |
| User Experience     | Installation                    | • Global install of `openclaw` via `npm` / `pnpm` / `bun`<br>• `openclaw onboard` wizard; optional `--install-daemon` for the Gateway daemon                                                                                                                                                 | • .zip / .exe installers<br>• One-line script installation<br>• `pip install qwenpaw`<br>• Docker installation<br>• One-click cloud deployment                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
|                     | Supported Platforms             | macOS / Linux / Windows                                                                                                                                                                                                                                                                      | macOS / Linux / Windows (PowerShell/CMD)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
|                     | Local Model Support             | • Configure Ollama / llama.cpp and other endpoints via config<br>• [Models and failover](https://docs.openclaw.ai/concepts/model-failover)                                                                                                                                                   | • Install-time `--extras` for the underlying inference runner; supports LM Studio, Ollama, llama.cpp<br>• Built-in llama.cpp local model provider and global LLM rate limiting (QPM sliding window)<br>• Optional [QwenPaw-Flash](https://huggingface.co/agentscope-ai) series tuned for QwenPaw ([Trinity-RFT](https://github.com/agentscope-ai/Trinity-RFT) post-training and [OpenJudge](https://github.com/agentscope-ai/OpenJudge) evaluation alignment; emphasizes docs, scheduling, memory updates, retrieval, and other high-frequency tasks)<br>• 2B / 4B / 9B and full / Q8 / Q4 variants; hardware-aware recommendations; download, enable, and switch in the Console                                                   |
|                     | Skills Support                  | • Local Skills<br>• Bundled / managed / workspace Skills with install gating<br>• Install from [ClawHub](https://docs.openclaw.ai/tools/skills)                                                                                                                                              | • Local Skills<br>• Direct import from multiple public Skills Hubs (skills.sh, clawhub.ai, skillsmp.com, lobehub.com, GitHub, modelscope.cn/skills, etc.)<br>• Two-layer skill pool architecture                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
|                     | Channel Integrations            | WhatsApp, Telegram, Slack, Discord, Google Chat, Signal, BlueBubbles/iMessage, IRC, Teams, Matrix, Feishu, LINE, Mattermost, Nextcloud Talk, Nostr, Synology Chat, Tlon, Twitch, Zalo, WeChat, WebChat, etc.; extensible                                                                     | DingTalk, Feishu, WeChat, WeCom, QQ, Xiaoyi, Discord, Telegram, iMessage, Mattermost, Matrix, Twilio, MQTT; extensible                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
| Community Ecosystem | Open-source License             | MIT                                                                                                                                                                                                                                                                                          | Apache 2.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         |
| Features            | Memory System                   | • Workspace file memory<br>• Session model: group isolation, context compaction (`/compact`), and [session pruning](https://docs.openclaw.ai/concepts/session-pruning)                                                                                                                       | • Powered by [ReMe](https://github.com/agentscope-ai/ReMe)<br>• Dynamic compaction before inference: prioritize recent high-signal content; compress older content into structured summaries with indexed recall to originals when needed<br>• Time-tiered compression of tool results<br>• Structured summaries combined with long-term memory files<br>• Hybrid retrieval: vector search + full-text search<br>• Per-role memory isolation in multi-agent setups<br>• Multimodal memory fusion; experience distillation & Skill extraction; context-aware proactive delivery (planned)                                                                                                                                           |
|                     | Multi-agent                     | • [Route channels / accounts / peers](https://docs.openclaw.ai/gateway/configuration) to isolated agents (workspace + per-agent sessions)<br>• [`sessions_*` tools](https://docs.openclaw.ai/concepts/session-tool) for cross-session coordination                                           | • [AgentScope](https://github.com/agentscope-ai/agentscope)-based multi-workspace isolation and collaboration<br>• Several agents in parallel in one instance; separate config, [ReMe](https://github.com/agentscope-ai/ReMe) memory, skills, and chat history per agent<br>• Concurrent load with locking; per-workspace hot reload and atomic cutover when a new instance is ready<br>• CLI `--background` and `/stop`; enable/disable agents in Console and API<br>• Collaborator agents use fresh sessions by default to avoid polluting the main agent context<br>• Async collaboration and multi-agent collaboration Skills for complex tasks; cross-turn state externalized to the filesystem first to limit context growth |
|                     | Reliability & operations        | • [`openclaw doctor`](https://docs.openclaw.ai/gateway/doctor) diagnostics and migrations<br>• [Retry policy](https://docs.openclaw.ai/concepts/retry), [model failover](https://docs.openclaw.ai/concepts/model-failover), logging                                                          | • Daemon Agent for long-horizon tasks and health monitoring<br>• Memory-related and Daemon-related [magic commands](https://qwenpaw.agentscope.io/docs/commands)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
|                     | Security                        | • Default [DM pairing](https://docs.openclaw.ai/gateway/security) and allowlist across channels<br>• Optional Docker sandbox<br>• [Security documentation](https://docs.openclaw.ai/gateway/security)<br>• ClawHub marketplace VirusTotal scanning                                           | • Tool guard<br>• Skill scanning<br>• File guard<br>• Tool sandbox (Seatbelt / Bubblewrap / Landlock / AppContainer)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
|                     | Cloud & remote access           | • [Tailscale Serve/Funnel](https://docs.openclaw.ai/gateway/tailscale), [SSH tunnels](https://docs.openclaw.ai/gateway/remote), and remote Gateway control<br>• Docker / Nix deployment                                                                                                      | • Extend cloud compute, storage, and services via AgentScope Runtime<br>• Docker deployment                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
|                     | Large-Small Model Collaboration | • Multi-model configuration and failover<br>• Docs recommend latest-generation strong models to reduce prompt-injection risk                                                                                                                                                                 | • Optional [QwenPaw-Flash](https://www.modelscope.cn/organization/AgentScope) series tuned for QwenPaw ([Trinity-RFT](https://github.com/agentscope-ai/Trinity-RFT) post-training and [OpenJudge](https://github.com/agentscope-ai/OpenJudge) evaluation alignment; emphasizes docs, scheduling, memory updates, retrieval, and other high-frequency tasks)<br>• Lightweight local models for privacy-sensitive data; long-context planning and reasoning to cloud LLMs (planned)                                                                                                                                                                                                                                                  |
|                     | Multimodal Interaction          | • [Voice Wake](https://docs.openclaw.ai/nodes/voicewake) / [Talk Mode](https://docs.openclaw.ai/nodes/talk)<br>• [Media pipeline](https://docs.openclaw.ai/nodes/images) <br>• [Live Canvas](https://docs.openclaw.ai/platforms/mac/canvas) (A2UI)<br>• macOS / iOS / Android companion apps | • Multimodal preview in Console chat<br>• Voice and video interaction                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
|                     | Skills & ecosystem              | • [ClawHub](https://docs.openclaw.ai/tools/skills) and built-in Skills continue to expand                                                                                                                                                                                                    | • Continuously enrich the [AgentScope Skills](https://github.com/agentscope-ai/agentscope-skills) repository and improve discovery and use of high-quality Skills                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
