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.
Personal AI
QwenPaw
Self-hosted personal AI assistant that runs in your own environment
75%
Panel ship
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Community
Free
Entry
QwenPaw (formerly CoPaw) is an open-source personal AI assistant you run on your own machine or cloud server. It connects to multiple chat platforms — Discord, DingTalk, Feishu, QQ, iMessage — and handles scheduled tasks, custom skills, and document processing all from a single local process. Nothing leaves your infrastructure. The April 22 v1.1.3 release added a Backup & Restore system, the ability to run QwenPaw as an ACP (Agent Communication Protocol) server, proactive agent messaging, a Console Plugin System, and a Shell Evasion Guard for security. It's built on the AgentScope framework and is now deeply integrated with the Qwen open-source model ecosystem, including local model support. QwenPaw sits in a sweet spot between consumer AI apps (which own your data) and raw agent frameworks (which require heavy engineering). The skills system makes it extensible without requiring code changes for each new capability — built-in skills handle PDF/Office files, news digests, and cron jobs, with custom skills easily added.
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 mode in v1.1.3 is underrated — it means QwenPaw can act as an agent backend for other tools. Apache 2.0 license, multi-channel support, and local Qwen model integration make this a genuinely solid self-hosted assistant stack.”
“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 Qwen branding pivot is a bit of a red flag — it suggests this is now more of a Alibaba/Qwen showcase than a truly independent project. The multi-channel support sounds good but each integration adds surface area for breakage when APIs change.”
“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.”
“Local-first AI assistants that run across all your communication channels are the next wave of personal productivity. QwenPaw's Shell Evasion Guard and offline-capable architecture show the team understands that security and privacy are table stakes for self-hosted agents.”
“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.”
“Having your AI assistant available in Discord, iMessage, AND DingTalk from one local setup is genuinely useful. The proactive messaging feature means it can push you reminders and digests without you having to ask — that's where personal assistants actually earn their keep.”
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