Comment by danielhanchen
19 hours ago
No this is false - unsure if you saw our new blog - https://unsloth.ai/docs/models/qwen3.5/gguf-benchmarks which shows SOTA on nearly all bits, and we shared all our research as well
19 hours ago
No this is false - unsure if you saw our new blog - https://unsloth.ai/docs/models/qwen3.5/gguf-benchmarks which shows SOTA on nearly all bits, and we shared all our research as well
Yeah, I saw that yesterday. The blog post does not explain why/how the Qwen 3.5 quants uploaded on 2/27 are different from the files uploaded on 2/24.
Old 2/24 Q4_K_XL commit (pre bugfix files): https://huggingface.co/unsloth/Qwen3.5-35B-A3B-GGUF/commit/7...
Questions for a postmortem that the blog post left unanswered:
- Why the change? Is it just to improve PPL/KLD? Sure, we can assume PPL and KLD are not perfect benchmarks. If yes, then why change the quantization anyways? Or was the old 2/24 quant actually much worse performing in the real world?I presume the Q4_K_XL quant using mxfp4 was the issue? If the 2/24 files having a lower PPL is an actual issue due to low quality tensors, then why not just say that?
- What were the main tensors that had the quantizations changed from 2/24 to 2/27? Did you now quantize attention tensors differently? Or perhaps ssm? T
- What was it changed from? Was it changed from mxfp4 or q4_k to q8, or something else?
A quick sentence in the blog post saying "ok, we've confirmed that using mxfp4 (or q3 or whatever) in the attention/ssm/biases/norms/etc is a bad idea, we had that in our old models on 2/24 and our new models today are better" that would make it clear. As it's written, it's trying to both say "PPL/KLD don't actually reflect real world quality" and "we changed our quant to increase PPL/KLD" at the same time, which seems contradictory.
Explain what about that statement is false. Your original Q4_K_XL quant was broken. People noticing that it was a total outlier among other quants is what prompted this "research". Your own data proves that your new release fixes the bugs of your original, in order to match AesSedai's PPL. Fixing bugs is great. Searching for the best quant mix is helpful. I use your quants and appreciate your work. But whitewashing this situation dilutes trust and good will.