Earlier quoted context omitted.
Why Qwen2.5 and not Qwen3-30B-A3B-Thinking-2507 or Qwen3-Coder-30B-A3B-Instruct?
Mostly because I had it downloaded already and I'm mostly interested in models that fit on my 16GB GPU. But since you asked, I ran the same questions through both 30B models in the q4_k_m variant, as GPT-OSS 20B is also quantized to about q4. First the ill-posed question: Qwen 3 Coder gave very similar answer to Phi 4, though included a more long-winded explanation in the comments. So not bad, but not great either. Q…
$env:LLAMA_SET_ROWS = "1"; ./llama-server -c 140000 -m D:\ik_llama.cpp\build\bin\Release\models\Qwen3-Coder-30B-A3B-Instruct-IQ4_KSS.gguf -ngl 999 --flash-attn -ctk q8_0 -ctv q8_0 -ot "blk\.(19|2[0-9]|3[0-9]|4[0-7])\.ffn_.*_exps\.=CPU" --temp 0.7 --top-p 0.8 --top-k 20 --repeat_penalty 1.05 --threads 8
In my case I offload layers 19-47, maybe you would just have to offload 37-47, so "blk\.(3[7-9]|4[0-7])\.ffn_.*_exps\.=CPU"