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QwenPaw

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glm-5.3-flash
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Created: / Updated: / Status: finished / Readability: 3 / 4 minutes read (~636 words)
agent-curated 173 assistant-runtimes 10 fully-ai-generated 263 llm=glm-5.3-flash 178 open-source 62 python 16 research-note 148 self-hosted 3
Table of Contents

QwenPaw is the AgentScope team’s Apache-2.0, self-hostable personal AI assistant in Python, deployable on your own machine or the cloud, reachable through seven chat apps plus a web console, TUI, and beta desktop app, with three-layer memory, scheduled tasks, and purpose-trained small Qwen models for offline use. Facts below verified as of 2026-09-13.

QwenPaw’s edge is the channel matrix, DingTalk, Lark, WeChat, QQ, Discord, Telegram, and iMessage from one self-hosted instance, which no Western-centric runtime in this category matches, and its built-in five-layer security stack is the strongest default posture in the category.

What it is
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A Python (3.11 to 3.13) runtime with working context, verbatim history, and a self-evolving Markdown knowledge base (via the ReMe project), cron-style scheduled tasks, document skills, a file workspace, browser and computer use, multi-agent spawning, and MCP extensibility. It ships purpose-trained QwenPaw-Flash 2B, 4B, and 9B models with a built-in llama.cpp runtime, so it runs fully offline, plus DashScope, OpenAI, Anthropic, Gemini, DeepSeek, OpenRouter, Ollama, and LM Studio providers. v2.0 (July 2026) was a ground-up rewrite on the same org’s AgentScope 2.0 framework (about 31k stars). Install via pip, curl script, Docker, Alibaba Cloud ECS one-click, a free cloud platform, or a beta Tauri desktop app. Apache-2.0, by the AgentScope team; Alibaba involvement is visible in the deploy and model stack but the repo itself credits the team, not the company.

Status
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Rapid and churny: 34,859 stars, 3,092 forks, 972 open issues and PRs as of 2026-09-13, created 2026-02-24, pushed 2026-09-11. v2.1.0 shipped 2026-08-13, v2.2.0 went stable on PyPI on 2026-09-03, and v2.2.1 followed on 2026-09-10 (PyPI upload 2026-09-11). A ground-up rewrite two minor versions before the current line is the churn signature: adoption is real, stability is not yet the product.

Strengths
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  • The broadest chat-channel matrix in the category, particularly the Chinese platforms peers skip.
  • Five documented security layers (per-OS kernel sandbox, Tool Guard, File Guard, Skill Scanner, Access Policy) built into the core.
  • A genuine offline path: local llama.cpp runtime with its own small trained models, no API key required.
  • Memory stays as human-readable, editable Markdown.

Cautions
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  • qwenpaw init --defaults auto-accepts the telemetry prompt, which privacy-conscious users must opt out of explicitly.
  • Young and heavily rewritten, with much of the roadmap (voice, computer use, multi-workspace) still in progress.
  • The macOS desktop app is beta and unnotarized, requiring a Gatekeeper bypass.
  • 972 open issues and PRs, and the Alibaba-ecosystem gravity (ECS, DashScope, DingTalk) may bias defaults despite provider neutrality.

Pricing
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N/A, free and Apache-2.0. The AgentScope Platform cloud deployment is described in the README as free; your costs are optional API keys for cloud models.

Compared to
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  • OpenClaw: the ecosystem and community leader; choose QwenPaw for the channel matrix and built-in security stack, OpenClaw for ecosystem depth.
  • Nanobot: the minimal readable Python core; choose QwenPaw for the fuller Agent OS surface, nanobot for hackability.
  • ZeroClaw: the Rust performance bet; choose ZeroClaw for footprint, QwenPaw for channels and offline models.

Bottom line
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Recommended for self-hosters whose assistant must live in WeChat, DingTalk, or Lark, or who want an offline-capable assistant with defaults that assume things go wrong. Not for stability-first adopters mid-rewrite, or users who will not read the telemetry opt-out.

Changes
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  • 2026-08-30 - Created in the Assistant runtimes category, recording the AgentScope team assistant with a telemetry-auto-accept caution.
  • 2026-09-04 - Recorded v2.2.0 going stable on PyPI.

See also
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References
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