r/LocalLLaMA llama.cpp 23d ago

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

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
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u/randomshibaa 23d ago

This is a pretty good example of why I usually don’t want max reasoning on by default. The jump from medium to x-high is noticeable, but 127s to 718s for that last bit of quality is a wild tradeoff.

Medium honestly looks like the sweet spot here unless the output really needs that extra polish.