Qwen's last two months: great for work, risky if chosen blindly

Let me share something. Over the past two months, I've intermittently used Tongyi Qianwen (Qwen) for various tasks: summarizing Chinese materials, generating code snippets, recognizing tables in screenshots, and testing both API and local small models. My impression isn't that of a model that makes you gasp right away; it's more like a diligent worker doing heavy lifting.

The most obvious evidence is with long Chinese documents. I threw in an instruction manual with screenshots and asked which conditions conflicted. It managed to extract constraints scattered across different pages and synthesized them into a coherent Chinese paragraph. However, it occasionally missed table titles, requiring me to add a prompt like "output according to the original table structure." This flaw isn't fatal, but it shows it's still far from being a "throw it in and done" solution.

The downsides are also apparent. The versioning and naming are too dense; with so many sizes and capabilities listed, beginners easily pick the wrong one. Its open-source ecosystem is a strength, but a big ecosystem doesn't equal a smooth experience. For local deployment, you still have to troubleshoot GPU issues, quantization, and dependencies yourself.

Qwen is definitely worth adding to your toolbox, but don't treat it as a universal entry point.

If you mainly process Chinese materials, build lightweight agents, or do local deployments, give Qwen a try. If you just want zero configuration, stable formatting, and no hassle, it depends—start with mature cloud applications.