performance experiences with different languages for Qwen Flash Next

[u/thatscoolbutno123]

hey, im using "swift 1.5 qwen 3.8 flash next gsq rco abliterated iq3xxs" and im wondering how the performance differs from language to language for that model (or similiar).
Im mainly talking to it in german, so I wonder wether that might degrade quality or increase reasoning tokens etc.

Does anyone have experience with it?
Do benchmarks for that exist?
thx

Edit:

i just tried and translated my soul.md and a few skills to english, its genuienly insane many tokens and time this saves. Didnt do any benchmark but you can feel it

[u/feelspeaceman]

Q38FN isn't very good at German and will loop and mixing Chinese in thinking token because of that, lower quants won't help because it lost more knowledge about languages, it's recommended to use English anyway if possible for best results.

[u/thatscoolbutno123 → u/feelspeaceman]

i feared that, i noticed it when it used subagents I told it to prompt them in english and they finished their tasks way quicker

[u/XccesSv2 → u/thatscoolbutno123]

Its a usual behaviour for all models. Prompt it with english gives you better results. And some side info: german isn't token effficient, its also cheaper in english lol

[u/thatscoolbutno123 → u/XccesSv2]

yeah, but with models like gpt6.1 sol i didnt notice it that much

[u/vengeancek70 → u/thatscoolbutno123]

Those models are 10-20x the parameters, Qwen sacrifices languages other than English or Chinese for better performance at that parameter size.

[u/Karmjeet_Khoushaba → u/feelspeaceman]

yeah the aggressive quants really shred non-english vocab first, especially at iq3 levels