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Qwen3.6-35B-A3B-Uncensored-Wasserstein-GGUF

Reddit r/LocalLLaMA / 4/19/2026

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Key Points

  • The author claims to have fixed a specific tensor drift problem in quantized GGUF models’ <em>ssm_conv1d</em> layers by using a Wasserstein metric (W1) to detect numerical instability more reliably than Kullback–Leibler divergence.
  • The drift issue appears confined to three <code>ssm_conv1d.weight</code> layers (blk.36–blk.38), where W1 values reportedly drop significantly after applying the fix.
  • The write-up notes that other tensors in the model remain healthy, suggesting the problem is localized rather than systemic.
  • A corrected model checkpoint has been published on Hugging Face, and the author provides links to related base models, system prompt, chat template, and recommended quantization/settings (e.g., Q4_K_P) for LM Studio.

Hello everyone. Finally I found a way to fix ssm_conv1d tensor drift in quantized GGUF models via Wasserstein metric (W1). It's a lot better than Kullback Leibler for detecting numerical instability and drift in tensors.

All three are ssm_conv1d.weight layers – recurrent state transition layers responsible for long‑context memory. It appears the Qwen team may not be aware of this specific drift issue in the SSM layers. I found the same bug in quants from Unsloth.

Tensor α D (log‑ratio) W1 before W1 after
blk.36.ssm_conv1d.weight 0.5765 0.553 0.0038 0.0009
blk.37.ssm_conv1d.weight 0.5768 0.725 0.0040 0.0009
blk.38.ssm_conv1d.weight 0.6533 0.649 0.0026 0.0006

Other tensors in model are healthy.

Here fixed model: https://huggingface.co/LuffyTheFox/Qwen3.6-35B-A3B-Uncensored-Wasserstein-GGUF

Model is based on this one: https://huggingface.co/HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive . Thanks to HauhauCS for amazing job.

System prompt: https://pastebin.com/pU25DVnB

Chat template: https://pastebin.com/Dy2fmmpN

Reccomended quant: Q4_K_P

Recommended Settings (LM Studio):

Parameter Value
Temperature 0.7
Top K Sampling 20
Presence Penalty 1.5
Repeat Penalty Disabled
Top P Sampling 0.8
Min P Sampling 0
Seed 42

Model features:

  1. It talks almost like human. Short and consize.
  2. Fully uncensored.
  3. Programming works fine.

I tested long context window in model via roleplay with my System Prompt. According to my taste I didn't find any problems in following character.

Enjoy ^_^

submitted by /u/EvilEnginer
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