CoPaw-Flash-9B: Alibaba’s Agentic Fine-Tune of Qwen3.5-9B
On March 30, 2026, Alibaba’s AgentScope team formally released CoPaw v1.0.0 — a personal AI agent workstation built around CoPaw-Flash-9B, an agentic fine-tune of Qwen3.5-9B. The model and the broader CoPaw framework are fully open-sourced under the AgentScope organization on Hugging Face and GitHub, positioning CoPaw as a lightweight, locally-runnable alternative to cloud-only AI agent services.
Intermediate
What Is CoPaw-Flash-9B?
CoPaw-Flash-9B is a purpose-built agentic fine-tune of Qwen3.5-9B — not a general-purpose chat model, but a model trained specifically to act as a local AI agent. It is the backbone of the Co Personal Agent Workstation (CoPaw), Alibaba Cloud’s open-source framework for deploying multi-channel AI agent workflows on personal hardware.
The model family spans three sizes — 2B, 4B, and 9B — all fine-tuned from the corresponding Qwen3.5 base models. The fine-tuning is concentrated on five agent-critical behaviors that are underserved by standard instruction-tuning:
- Tool invocation — accurate web-search intent recognition and multi-step API navigation
- Command execution — terminal operations and file system orchestration
- Active memory management — autonomously identifying, storing, and retrieving user preferences and task state across sessions
- Multi-step planning — decomposing long-horizon tasks into executable subtasks
- Feature guidance — built-in awareness of the CoPaw feature map to proactively suggest functional paths
Memory is handled by ReMe (Remember Me, Refine Me), a dedicated memory management module that stores long-term user preferences locally or in the cloud — a key differentiator from stateless chat models.
Benchmark Performance
Benchmarks use a proprietary CoPaw-environment suite covering the five task categories above, rather than standard general-purpose benchmarks like MMLU or GPQA. The official model card claims that CoPaw-Flash-9B achieves performance comparable to leading flagship models on these agentic scenarios while running on significantly fewer resources. Given that the base Qwen3.5-9B already outperformed models 3–13× its size on general benchmarks (as we covered in March), the fine-tune builds on an already strong foundation.
The CoPaw Framework
CoPaw-Flash-9B is not designed to be used standalone — it is tightly integrated with the CoPaw framework, which provides:
- Multi-channel orchestration — coordinate tasks across different tools and interfaces from a single agent
- Persistent memory via ReMe — cross-session context retention without manual prompting
- Alibaba Cloud PAI-EAS deployment — a five-minute cloud deployment path for teams that don’t want local inference
- Open-source stack — Apache 2.0 license, fully auditable, no vendor lock-in
The project sits within Alibaba’s AgentScope ecosystem, a broader framework for building production-grade multi-agent applications. CoPaw is effectively AgentScope’s consumer-facing product layer — a ready-made personal agent, not just a library.
Why This Matters
The agentic AI space has been dominated by models designed for general instruction-following and then patched with tool-calling APIs. CoPaw-Flash-9B represents a different philosophy: train explicitly for agent behavior from the start, at a model size that fits on a single consumer GPU.
The release also comes at a turbulent moment for Alibaba’s AI efforts — just weeks after Qwen tech lead Junyang Lin’s abrupt departure. The AgentScope team’s CoPaw v1.0.0 launch, separate from the core Qwen team, signals that Alibaba’s AI model work is now distributed across multiple internal groups with distinct product directions.
For developers, CoPaw-Flash-9B offers a compelling option: a 9B model purpose-built for agent tasks, with an integrated memory system, and a full open-source deployment stack — available today at copaw.bot.
Related Coverage
- Qwen 3.5 Small Models: 9B Parameters That Beat 120B — the base model behind CoPaw-Flash-9B
- Junyang Lin Steps Down as Qwen Tech Lead in Abrupt Departure — context on the Qwen team restructuring
- Qwen 3.5: Alibaba’s Native Multimodal Agent Model Arrives — the broader Qwen 3.5 family launch