I tested every Unsloth quant of Qwen3.8 27B on canvas coding, and Q8 was NOT the winner 👀
Setup: 2 prompts:
> growing tree animation
> paper slicing)
3 runs each, across BF16 (Original) / UD-Q2_K_XL / UD-Q3_K_XL / UD-Q4_K_XL / UD-Q6_K_XL / UD-Q8_K_XL.
🌳 Growing tree test (successes out of 3):
> BF16 — 3/3
> Q2 — 1/3
> Q3 — 3/3
> Q4 — 3/3
> Q6 — 3/3
> Q8 — 2/3
📄 Paper slice test (successes out of 3):
> BF16 — 1/3
> Q2 — 0/3
> Q3 — 2/3
> Q4 — 2/3
> Q6 — 2/3
> Q8 — 1/3
Takeaway: "bigger quant = better" didn't hold here, Q8 underperformed Q4 and Q6 on both tests.
If you're running this model locally, Q6/Q4 looks like the sweet spot: near-full quality at a fraction of the VRAM.