bartowski measured which tensors actually break under quantization, and Q3_K_M got 15% smaller.

A Hugging Face post dated September 10 documents 96+ hours across 1,000+ quantization configurations on Qwen 3.5 0.8B and 4B, producing per-tensor layout maps replacing the generic GGUF heuristics. Findings: token embeddings are 8-16x more sensitive to degradation than other weights, sensitivity follows a U-shape by model depth, attention projections matter, gate tensors mostly don't. Q3_K_M on Qwen3.5-4B comes out 15% smaller with quality called marginally better across the board, validated against Gemma, Granite and DeepSeek with a canary test for generalization. r/LocalLLaMA picked it up at 213 upvotes when bartowski re-uploaded the Qwen3.8-27B GGUFs under the new layout. Measure-then-quantize beating a heuristic is unsurprising; the size win at equal quality is what makes it worth re-downloading.