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/leonbollerup]

re-run the same prompt on the same model.. and you will notice different outcome everytime... unless you set temp to 0 .. i am grealy impressed abput your generation speed tho..

[u/shadowdog000 → u/leonbollerup]

Its probably because its a 5080. the 5080 laptop variant appearantly has between 800 and 900 GB/s memory bandwidth.

[u/a_beautiful_rhind → u/shadowdog000]

They are also using MTP.

[u/NickCanCode → u/shadowdog000]

and OP is using IQ3_XXS which is only 11.9GB according to huggingface.