naw, i mean i prefer Qwen 3.6 to Gemma 90% of the time, especially the MoE with a light tune to make it's tone more claude-like, but Gemma 4 is definitely better in some cases and I think they're pretty close in general.

The difference basically boils down to Gemma 4 making more assumptions and Qwen 3.6 sticking closer to the prompt, if your prompt is bad or leaves things up to the imagination, Gemma will do a better job, if you need strict prompt adherence Qwen is better. Since local models are "dumb" i think it makes sense to prefer prompt adherence, but there are complex tasks that Gemma will complete much much faster than Qwen because it makes the right assumptions the first time and as a result even with slower inference requires way fewer turns.

My speculation is that this comes from google having a much better strategy for filtering their training data, I think this also shows up in the shape of the world knowledge of the models. Gemma's world knowledge seems deeper even though the models are of roughly equivalent size to the Qwen counterparts so it's mostly likely just concentrated in places that are more relevant to my queries.

Most notably in my testing, Gemma 4 31b is the ONLY local model that will tell me the significance of 1738 correctly. Even most flagship/cloud models answer with some hallucinatory nonsense.