AI tool comparison
QwenPaw vs QwenPaw
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
AI Assistants
QwenPaw
Alibaba's open-source personal assistant that runs on your machine across every chat app
50%
Panel ship
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Community
Paid
Entry
QwenPaw (formerly CoPaw/Tongyi CoPaw) is an open-source personal AI assistant from Alibaba's AgentScope team that rebounded in April 2026 with a v1.1 series of releases and a full ecosystem rebrand. It runs locally on your machine or in the cloud, connects to every major chat platform (DingTalk, Feishu, QQ, Discord, iMessage, and more), and executes scheduled tasks, agentic workflows, and memory-based recall — all from a unified interface. The v1.1.3 and v1.1.4 releases in April brought a backup and restore system, QwenPaw as ACP Server (allowing other agents to call into it), proactive agent messaging, a console plugin system, agent statistics, and a shell evasion guard. The rebrand to QwenPaw signals deeper integration with Alibaba's Qwen model ecosystem, meaning you get native access to Qwen 3 and Qwen 3.5 series models out of the box. The appeal is data sovereignty: everything runs on your infrastructure, conversations stay on your machines, and you configure which channels it monitors. For teams already embedded in Alibaba's cloud stack, this is a natural fit. For everyone else, it's an intriguing open-source alternative to commercial personal assistant platforms — if you're willing to self-host.
Personal AI
QwenPaw
Self-hosted personal AI with evolving memory, runs on 6+ chat apps
75%
Panel ship
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Community
Free
Entry
QwenPaw (formerly CoPaw, rebranded April 2026) is an open-source personal AI assistant built by the AgentScope team at Alibaba. You deploy it locally or on a cloud VM, connect it to messaging apps like Telegram, Discord, WeChat, DingTalk, or Feishu, and interact with a persistent, memory-evolving agent that learns your preferences and proactively surfaces relevant information. Version 1.1.4, released April 24, brings a refactored memory and context architecture, built-in DeepSeek V4 models, ACP Server exposure for multi-agent communication, and a console plugin system. For LLM backends it supports cloud APIs (Qianwen, DeepSeek, OpenAI) and fully offline local inference via Ollama, LM Studio, or llama.cpp — meaning you can run it with zero API costs on your own hardware. The built-in skill library covers daily news digests, video summarization, email triage, PDF/Office processing, and calendar management. The multi-agent capability — where you can spin up specialized agents that collaborate — puts it in interesting territory between a personal assistant and a lightweight team-of-agents platform. Desktop apps for Windows and macOS are in beta.
Reviewer scorecard
“The ACP Server capability in v1.1.3 is genuinely interesting — being able to call QwenPaw from other agents creates an orchestration layer you can build on. The multi-channel support is real and well-implemented. If you're in the Alibaba / Qwen ecosystem already, this is a no-brainer deploy.”
“The Ollama backend support is the key feature — this is the first personal assistant I've seen where you can genuinely go fully offline and fully free. The ACP server in v1.1.4 opens it up for multi-agent coordination that's actually useful for automating dev workflows.”
“The China-ecosystem platforms (DingTalk, Feishu, QQ) are the primary channels, which narrows the appeal significantly for Western teams. The rebrand from CoPaw to QwenPaw is the third name in two years — signs of product identity confusion. Self-hosting requirements also raise the bar considerably.”
“The skill library looks impressive on paper but most of the demos are China-centric platforms (Xiaohongshu, Zhihu, DingTalk). International users will find meaningful gaps and will need to build their own skills. The documentation is also still primarily in Chinese despite multilingual README efforts.”
“Personal AI assistants that you fully own, run locally, and connect to every communication channel you already use — this is where the market is heading. QwenPaw is one of the most complete implementations of this vision available as open source today.”
“The future of personal AI is self-hosted, memory-persistent, and connected to where you actually communicate. QwenPaw's architecture — LLM backend agnostic, multi-platform, multi-agent — is the right shape for that future. The Alibaba team building this in the open is a meaningful contribution.”
“The interface is very developer-facing and the supported channels are enterprise-centric Asian platforms I don't use. The concept is great — a personal assistant you fully own — but the execution doesn't feel polished enough for non-technical creative workflows yet.”
“The 'describe your goal before sleep, wake up to a prototype' workflow is the creator feature I didn't know I needed. Video pipeline automation and newsletter digests pushed to Telegram cover 80% of my daily content research. This one's getting installed.”
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