I did a short test of the different reasoning efforts, since on default xhigh the model thinks a lot.

Not very scientific, just a quick "generate an SVG of a pelican on a bicycle" prompt with 3 different seeds. I think the result is interesting none the less: xhigh gives *much\* higher visual fidelity - but it also takes about 7x as long as low. Low and medium seem to be very close to each other.

https://preview.redd.it/fkbx5qf41qjh1.png?width=1560&format=png&auto=webp&s=bfc1e9679802605c61af203ca27422ed763b6a19

Hardware and setup

• GPU: NVIDIA RTX 5080 Laptop GPU, 16 GB VRAM
• Model: unsloth/Qwen3.8-27B-UD-IQ3_XXS
• llama.cpp: build 10451, commit 10bf611e5
• Context: 65,536
• KV cache: Q8_0
• Flash Attention: enabled
• MTP speculative decoding: --spec-default --spec-type draft-mtp
• --fit off
• One concurrent slot

Prompt:

Create a polished SVG graphic of a pelican riding a bicycle. The result must clearly show a recognizable pelican actively riding a recognizable two-wheeled bicycle. Return only one complete, self-contained SVG document with a viewBox; no Markdown fences, prose, external images, JavaScript, or animation.

Average results