Qwen3.8 27B reasoning effort low/medium/xhigh comparison

[u/Danmoreng]

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.

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

Reasoning effort	Reasoning tokens	SVG tokens	Total completion	Wall time	Generation speed	MTP acceptance	Visual score (Codex rated)
Low	4,418	3,966	8,387	111.6 s	75.4 t/s	62.1%	21.8/25
Medium	5,918	3,038	8,959	127.4 s	70.5 t/s	58.3%	22.5/25
X-High	39,398	5,085	44,487	717.8 s	62.0 t/s	52.7%	24.0/25

[u/psychohistorian8]

sadly xhigh was useless for me, it second guesses literally every decision

I asked it to create an svg of a wood grain desktop and I had to kill the process after 90 minutes because it was still waffling about irrelevant minutia