AI tool comparison
QwenPaw vs Sup AI
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.
AI Assistants
Sup AI
Confidence-weighted AI ensemble that topped Humanity's Last Exam
67%
Panel ship
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Community
Free
Entry
Sup AI uses a confidence-weighted ensemble of multiple AI models to answer hard questions. Each model rates its own confidence, and the system aggregates responses weighted by that confidence. Achieved 52.15% on Humanity's Last Exam benchmark, outperforming individual models.
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.”
“No API, no self-hosting option, and the ensemble approach means your per-query cost is 3-5x a single model call. The benchmark numbers are compelling but I cannot integrate this into a product. Ship an API and I will reconsider.”
“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 benchmark result is legitimately impressive and the methodology is transparent. My concern is latency — querying multiple models and aggregating adds significant time. For research and high-stakes questions it is worth the wait. For everyday chat it is overkill.”
“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.”
“Confidence-weighted ensembling is the quiet breakthrough everyone is sleeping on. Individual models plateau — but smart aggregation keeps pushing the frontier. Sup AI scoring 52% on Humanity's Last Exam when no single model breaks 40% proves the thesis.”
“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.”
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