[kgeist]

Qwen3.5 comes in various sizes (including 27B), and judging by the posts on HN, /LocalLlama etc., it seems to be better at logic/reasoning/coding/tool calling compared to Gemma 4, while Gemma 4 is better at creative writing and world knowledge (basically nothing changed from the Qwen3 vs. Gemma3 era)

[Mil0dV]

Does this also apply to gemma's 26B-A4B vs say Qwens 35B-A3B?

I'm not sure if I can make the 35B-A3B work with my 32GB machine

[green7ea]

It should be easy with a Q4 (quantization to 4 bits per weight) and a smallish context.

You won't have much RAM left over though :-/.

At Q4, ~20 GiB

https://huggingface.co/unsloth/Qwen3.5-35B-A3B-GGUF

[rhdunn]

For llama-server (and possibly other similar applications) you can specify the number of GPU layers (e.g. `--n-gpu-layers`). By default this is set to run the entire model in VRAM, but you can set it to something like 64 or 32 to get it to use less VRAM. This trades speed as it will need to swap layers in and out of VRAM as it runs, but allows you to run a larger model, larger context, or additional models.