QATs Q4_0 from Google have more precision than Q4_K_XL from Unsloth (at least some)

In three linesQAT quantization comparison for Gemma-4: Google's Q4_0 models contain more q6_k and f16 tensors than Unsloth's Q4_K_XL, explaining larger file sizes (5.15 GB vs 4.22 GB for E4B). Google uses mixed strategy (q6_k on 2 tensors, q4_0 on 342) while Unsloth relies mainly on q4_0 (345 tensors).

Summary generated by Claude — human-verified