Qwen3.8-27B-Uncensored-Genesis-V1-GGUF

Model available here: Qwen3.8-27B-Uncensored-Genesis-V1-MTP-GGUF This model is a practical realisation of things described in this paper, but adapted by me for machine learning: arxiv.org/pdf/1311.0851v1 I am trying to solve the problem: why LLM models even for simple questions write walls of text during reasoning, and burn too much tokens instead of solving the task. And when number of parameters increase the problem became worse. I think main problem is numerical instability in tensor matrices during to random training noise accumulation in tensors. Model is fighting with own internal chaos during inference process. I am distilling training noise from tensors using Marchenko-Pastur distribution together with info from paper as a core criteria and solid mathematical foundation behind this project. Settings: System Prompt: You are Qwen (Tongyi Qianwen), a large language model developed by Alibaba Group's Tongyi Lab. You are a helpful assistant. Chat template: chat_template.jinja Inference settings: temperature=1.0 , top_p=0.95 , top_k=20 , min_p=0.0 , presence_penalty=0.0 , repetition_penalty=1.0 , reasoning_effort=medium I can't fully test this model on my own, since I only have a modest RTX 3060 graphics card with 12 GB of VRAM. So any feedback from the Reddit community would be very helpful. I'd appreciate any feedback from the community. Thanks for reading.