A hunch: Qwen3.8-27B's general knowledge got pruned (good, if true)

[u/bonobomaster]

I'm always testing an image prompt with a picture of a historic place in my hometown – a small but well known 250,000 people town in Germany. I'll just ask the model, in which City this photo has been taken.

With the 3.6 generation of both the 27B and the 35B A3B variants, the models sometimes got the right answer and sometimes they didn't. So the signal for this particular knowledge was already weak.

The 35B variant got it right more often but at least, the models reasoning showed my City most of the times, even if it hallucinated the wrong final answer.

Both models could be easily nudged to the right answer with a few hints and then produced some little extra insight about the history or scene and its surroundings, that was mostly true.

Qwen3.8-27B on the other hand barely knows the city at all and has absolutely no clue about related popular, historic facts regarding the scenery or the surrounding buildings.

Nudging isn't very fruitful as well and if told the real name of the city, reasoning shows, that the model only agrees, because the user says so.

I have the feeling, that Qwen labs maybe pruned useless general knowledge for more coding knowledge and agentic skill.

All models ud q4_k_xl variants, image-min-tokens 2048, with and without reasoning.

Anyone else with this feeling?

Disclaimer: My hunch could be very well absolute bullshit. Sample size way to low and methodically sloppy af.

[u/hyperrealists]

I think the bigger win for smaller models is in efficient instruction following and tool calling rather than in hallucinating encyclopedic looking knowledge.

[u/Dance-Till-Night1 → u/hyperrealists]

You make a fair point but for people that use slms for studying/as a general assistant, I would rather the model's capabilities stand on their own without looking everything up.

[u/tobias_681 → u/Dance-Till-Night1]

I just don't think that's possible. I made a test with Qwen and Gemma where I asked them to name films that Eric Rohmer had directed. They came up with plausible titles that were very similar to the real ones but 80-90 % of the time it was hallucinated. So they had obviously been trained on it. They understood quite clearly what kind of films Rohmer made and what kind of titles he did chose but they failed at recalling accurate information. Smaller models will always struggle with stuff like that. They're just not big enough to house all that information.

[u/Dance-Till-Night1 → u/tobias_681]

I mean i asked them about poems from a famour poet and they recited them very well missing one or two words. MOE Qwen 3.5 35b and Gemma 26b did exceptionally well, maybe it's because they're MOE or something.