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

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A Hugging Face blog 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 that replace the generic GGUF heuristics. The measured findings: token embeddings are 8-16x more sensitive to degradation than other weights, sensitivity follows a U-shape by model depth, attention projections matter and gate tensors mostly do not. Q3_K_M on Qwen3.5-4B comes out 15% smaller with quality called marginally better across the board, and the layouts were 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.