Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things
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Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things
16th August 2026
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.
The default of extra high results in spectacular over-thinking
Qwen’s documentation describes the model as defaulting to xhigh for the reasoning effort, and the LM Studio GGUF I’ve been trying preserves that default:
Qwen3.8 comes with official support for reasoning_effort, which can be used to adjust reasoning depth and control cost:
xhigh (default): for complex tasks demanding thorough analysis
medium: balancing accuracy and speed
low: efficient reasoning optimizing for speed and cost
This is a hilarious default. It’s absolutely not a good way to run the model, especially on consumer hardware. I’ve been finding the results extremely entertaining.
I quickly ran into problems with LM Studio’s default context limit of 8,192 tokens—Qwen was using them all up thinking about even the most mundane of problems. I loaded the model with the full 262,144 maximum context length and that problem went away.
Here’s the pelican riding a bicycle SVG I got from my first attempt with that increased context length. It took 21 minutes to generate, using 22,276 reasoning tokens to produce 3,223 tokens of output. You can read the reasoning trace here.
This is by far the best pelican SVG I’ve been able to generate with a model that runs on a local machine—and this Qwen is pretty small, just a 17GB file on disk. There’s a lot to like about this:
The bicycle frame is the right shape
It has legs on each side of the bike—that’s very rare
Good, clear pelican pouch
The wings extend to touch the handlebars!
The motion lines are behind, not in front
It has a tasteful background—nice sun, clouds, hill, flowers and grass.
Was that worth waiting 21 minutes for? Absolutely not.
Here’s that same prompt run with reasoning turned off—transcript here. This one produced 3,715 tokens and took 137s—just over two minutes.
And just for completeness, I used OpenRouter to run the same prompt through the much larger Qwen 3.8 2.4T-A95B (released last week) and got this snazzy animated SVG:
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I said Qwen at xhigh has a tendency to over-think things, but how bad really is it?<br>I tried a much simpler prompt, again with that default extra high setting:
draw an svg of a circle
Qwen’s reasoning trace started like this:
The user is asking for an SVG drawing of a circle. Simple request — but I want it to be a carefully crafted piece. Let me make something that goes beyond just : a single self-contained SVG file with character — maybe a geometric “circle study,” with subtle animation, layered rings, and a distinctive palette.
Keep the scope right: they asked for an SVG of a circle. So the core is a circle. But I can add craft: concentric guide circles (like a compass/geometry drawing), tick marks, a soft gradient fill on the main circle, restrained ambient motion (a slowly rotating dashed ring, pulsing glow). Respect prefers-reduced-motion? That’s more for CSS; SVG SMIL or CSS inside SVG will do.
Palette options: deep teal ink on warm paper? Or bold vermilion circle on off-white with navy construction lines — Bauhaus/compass-drawing vibe. Let me go with a “geometric study” look: cool slate background, or bright paper white? Paper white is fine if it’s not the cream-and-terracotta combo. [...]
Several minutes later it produced this absolutely beautiful animated circle, which was entirely not what I had asked for!
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My strong recommendation: ignore that default. Run Qwen 3.8 27B on low or even no reasoning levels at first. It’s a great model, but wow that default setting is a bad place to start.<br>It’s very good at bounding boxes
A fun way to test a vision model is to see how well it can return bounding boxes around items in a photograph. I’ve seen previous Qwen models deal well with this, so I decided to put it to the test drawing...