Qwen 3.8 27B is excellent, but it defaults to overthinking things
The Qwen 3.8 27B model is a powerful new open-weights LLM from Alibaba that excels at reasoning but defaults to an overly cautious 'thinking' mode. The author notes that while the model is highly capable, its default settings can consume excessive context and compute resources.
Why it matters
It highlights the trade-offs between reasoning depth and resource efficiency in local LLM deployment on consumer hardware.
Friday’s big release was Qwen 3.8 27B , an Apache 2 licensed 27B parameter vision-capable LLM from Alibaba’s Qwen research lab. I’ve been looking forward to this one: 27B is an excellent size for running a model on a reasonably specced laptop, and its predecessor Qwen 3.6 27B was impressive.
Qwen’s self-reported benchmarks for this model are eye-opening. They show a boost from both Qwen 3.6 27B and the closed-weight Qwen 3.7-Plus, which was one of Qwen’s strongest models of any size as recently as May this year . It will be interesting to hear what independent benchmarks have to say about the model.
I’ve been running the model on two different machines: my 128GB M5 Max MacBook Pro, and an NVIDIA DGX Spark . On both machines I’m running LM Studio and their 17GB Q4_K_M quantized build . I also tried using llama-server directly on the Spark.
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