u/Past-Chain-7377

From the feedback on my previous post here, I learned that quantization hurts MoEs way more than dense models. Now I'm wondering just how much a dense model can be quantized before a MoE becomes the better alternative. For instance, would Qwen3.8 27B Q4 perform better than Qwen3.6 35B Q8? what about Qwen3.8 27B Q3 or Q2? does quality loss increase exponentially the more a model is compressed? I am specifically interested in coding/tool use/reasoning performance, but any intel you have is appreciated

I know that "better" is very vague. I was wondering, to give you an example, if using Qwen3.6 27B Q3/Q4/Q5... would give me higher quality answers (mostly code, reasoning and tool calling) than Qwen3.6 35B A3B Q8.
I am asking because I see from various benchmarks that dense 27b is all around better than 35b a3b at full precision, but because dense models are way slower at generating tokens on my machine (~4-5t/s dense vs. ~38-40 t/s MoE) I thought I could use a dense model with higher compression if it performed better.

Unfortunately, I cannot seem to find any benchmarks or even people sharing personal experiences with these kinds of comparisons.