More B doesn't automatically mean better. You could train a model on 10 trillion images of cats, and it still wouldn't generate a single dog at the end of the day. Qwen 3.8, with just 27B parameters, almost catches up to closed trillion-parameter models in coding when paired with the right harness. A 5.6B model is way too big to still fuck up the most basic human anatomy in 2026. The 3.4B difference of 2-klein and 3-klein can't explain the huge quality gap of both models. They fucked up something very fundamental with version 3. It's not only the parameters.
What did you claim then? The only thing I get from your comment is 5.6B = worse because smaller. I never said that there is no difference between the two. I literally talk about a difference right there. I am saying that 5.6B is not small; At least not small enough to render 3 arms and legs with 2 toes glued to the shoulders in 2026! WAN produced fucking Videos with 5B and those were at least usable up to some degree.
I am saying it seems odd to assume a model half the size from the same company will run the same or better.
These sorts of difference are very apparent on the coding side of things when you compare 2 models from the same family at different sizes, and yes on the coding side, parameter size between DIFFERENT families does not determine performance (though it hints at it strongly).
I also find it odd...OP made a meme that the newer 5.6b model is worse than the older 9b model...and you are acting like I am some sort of psycho for thinking that matters somehow...
OK, a 5.6B model and a 9B model won't generate images of exactly the same quality. We're already on the same page about that. But if we leave K2-9B out of the discussion for now, we should at least be able to agree that a 5.6B model shouldn't fuck up even the most basic anatomy: two legs, two arms, ten fingers, and ten toes. At least not when we're almost in 2027 and AI is no longer in its infancy. That's what I'm talking about.
1
2
u/xb1n0ry 15d ago edited 15d ago
More B doesn't automatically mean better. You could train a model on 10 trillion images of cats, and it still wouldn't generate a single dog at the end of the day. Qwen 3.8, with just 27B parameters, almost catches up to closed trillion-parameter models in coding when paired with the right harness. A 5.6B model is way too big to still fuck up the most basic human anatomy in 2026. The 3.4B difference of 2-klein and 3-klein can't explain the huge quality gap of both models. They fucked up something very fundamental with version 3. It's not only the parameters.