Qwen 3.8 27B is impressive but defaults to overthinking

Qwen 3.8 27B is the latest addition to the Qwen family of large language models and has quickly attracted attention from AI enthusiasts and developers around the world. Simon Willison, a prominent voice in the tech community, published a thorough analysis of the model on his blog, highlighting both its impressive capabilities and its most notable limitation.

According to Willison, Qwen 3.8 27B performs exceptionally well across a range of complex tasks, including code generation, reasoning, and text comprehension. The model demonstrates a sophisticated ability to handle nuanced questions and deliver well-structured responses, making it a strong contender among open and semi-open models in its size class.

The central criticism, however, concerns the model's default behavior of overthinking problems. Even for relatively simple queries, Qwen 3.8 27B tends to go through lengthy and sometimes unnecessarily complex reasoning chains before arriving at an answer. This can lead to slower response times and wasteful resource consumption, particularly in production environments where efficiency is critical.

The lively discussion on Hacker News, with nearly 300 points and over 120 comments, underscores the broad interest in this topic within the tech community. Users have been sharing experiences and tips on how to tune the model's behavior to avoid overthinking, such as modifying system prompts or adjusting inference parameters. Overall, Qwen 3.8 27B appears to be a promising addition to the AI landscape, though its default configuration leaves room for improvement.