This is Unsloth's UD-Q4_K_S quantization (edit -- on llama.cpp, via the Vulkan backend, on an RX 7900 XT, with Unsloth's recommended sampler config), for "as replicable as LLMs can be" disclosure, done through llama.cpp's web UI. In another thread, via Open WebUI (both with no custom prompt, so whatever the "default" system prompt is), a reasoning block opens as such:

  We need answer user's request: write complete short story scene 2000-3000 words, third-person limited with Rowan, no outline preamble analysis. Need satisfy plot elements: raccoon, Milo returns, storm power failure, elderly customer knocks, thermos somewhere. End scene feels finished. Need produce only story. Need think in English (user English). Need craft 2000-3000 words. Need no meta. Let's plan.

Now, I will add that when I use Qwen3.8 in a coding harness, the reasoning tends to NOT look like this, and instead looks more Qwen3.6-ish.

But when I give short prompts to Qwen3.8 with no system prompt or previous instructions, it seems to strongly gravitate towards grug-talk.

▲ stymaar 3 hours ago | parent [-]

I just tried to reproduce in Llama-cpp's webui: with the following (reverse-engineered) prompt:

“Write a complete short story scene of 2000-3000 words. Use a third-person limited perspective focused on a character named Rowan. The scene must include the following plot elements: a raccoon, Milo returns, a storm power failure, an elderly customer knocks, and a thermos somewhere. Make sure the scene ends feeling finished. Output only the story; do not include any outline, preamble, analysis, or meta-commentary.”

And here's Qwen's thinking trace:

> The user is asking for a short story scene of 2000–3000 words. Third-person limited POV, Rowan. Plot elements: a raccoon, Milo returns, a storm causing a power outage, an elderly customer knocks on the door, a thermos. End with a sense of closure. Output only the story.

> Let me plan carefully. I need to count words in my head—roughly 2400–2600 words would be safely in range. Let me draft.

> Setting: a small-town shop or a gas station/diner where Rowan works the night shift. Milo returns—Milo is probably Rowan's partner, brother, or ex. Let me make Milo Rowan's brother who's been away (military? a road trip? rehab?). Better: Milo is the younger brother who disappeared/went away after a fight. He comes back in the middle of a storm.

While at the very beginning it rephrases the prompt in very short sentence, it's nowhere near close to the above GPT thinking trace and it quickly moves to plain sentences.

▲ spijdar 2 hours ago | parent | next [-]

Yeah, I dunno. For me it does "talk normally" for the most part when used in an actual coding harness.

One thing though, the actual prompt I used was pretty long (844 words), and ... generated by GPT-5.6 Sol (lol), with the intent of "benchmarking" model performance in being able to write stories where the model avoids explicitly stating every detail in the prompt.

I wonder if the GPT-produced stream could steer the generation into GPT-think territory. That's all I've got, though.

Then there's the actual geometry problem from the stolen thoughts paper:

  Let ABCDE be a convex pentagon with AB=14, BC=7, CD=24, DE=13, EA=26, and ∠B=∠E=60◦. For f(X)=AX+BX+CX+DX+EX, the least value of f(X) is m+n√p (p squarefree). Find m+n+p.

▲ bytkim an hour ago | parent | prev [-]

The person evaluating and noticing similar reasoning traces to gpt is because they are using a coding harness which probably has a different system prompt to llama webui which primarly serves as a chat interface

	▲	stymaar 22 minutes ago \| parent [-]
		They said literally the opposite in their message above. In their experience, the caveman speech occurs in chat ui, not in coding harness.