I ran a test on the Q5_XL version (unsloth.) I asked it to remodel a trainer (pytorch) with over 3,000 lines of code from gpt2 to a more modern architecture.

The task was completed (from gpt2 di "mistral"); the only problem was that Qwen "simplified" the code by deleting many command line arguments and then apologized.

I tested temperature 0.6 with the suggested parameters. I think with a few tweaks (prompt, settings) it might not lose context (minimax performed the same task perfectly).

What impressed me was that I had asked the same question on gpt4 reasoning high, and the improvements suggested by qwen 3.6 are objectively better in context with the trainer's goal (a small, dense, 200M-parameter model trained on an RTX 6000).