license: apache-2.0
tags:

• text-generation
• gguf
• nvfp4
• fp4
• moe
• qwen3.6
• hermes
• uncensored
• vision
• multimodal
• genesis
• agentic
• llama-cpp
  language:
• en
• zh
• multilingual
  datasets:
• NousResearch/hermes-function-calling-v1
  pipeline_tag: image-text-to-text
  base_model:
• HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
• LuffyTheFox/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-GGUF
  base_model_relation: quantized

🌟 Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4-GGUF

This repository contains the NVFP4 (NVIDIA 4-bit Floating Point) quantized GGUF release of LuffyTheFox's latest updated Hermes model: LuffyTheFox/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-GGUF.

• Original Model & Genesis Tensor Repair: LuffyTheFox — Original Model Repo
• NVFP4 Quantization: jan1k
• Base Model: HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive (0/465 refusals)
• Hermes Finetune: DJLougen/hermes-qwen3.5-35b-a3b-GGUF (Transferred data from finetune on Hermes dataset — around 2k blocks from two FFN expert tensors to HauhauCS uncensored base)
• Quantization Format: NVFP4 (NVIDIA FP4) GGUF (optimized for NVIDIA Ada Lovelace / Blackwell / Ampere GPUs)
• Architecture: Mixture of Experts (MoE) — 35B total parameters / ~3B active per token (8 routed experts + 1 shared)
• Multimodal (Vision): Supported via mmproj-Hermes3.6-35B-A3B-Uncensored-Genesis-Final-F16.gguf

⚡ Provided Files

⚡ What is Genesis?

Genesis is a post-training data regeneration and calibration algorithm for neural networks (LLM) in GGUF format developed by LuffyTheFox over almost half a year of development with AI assistance. It is optimized, architecture-independent, works with any model in GGUF format, and is based on mathematical statistics.

LLM models often suffer from:

• Saturated weights: activations get stuck, gradients vanish, outputs degrade.
• Scale mismatches: one layer's weights are 10× larger than peers for no valid reason.
• Mean drift: weight distributions shifted positive or negative, breaking symmetry assumptions.
• Zero blocks: zero blocks corrupt the signal, turning training into noise amplification.
• Training noise: increases randomness and ruins output quality.

Genesis fixes all of that without retraining — pure numerical surgery on the raw bytes of the file:

1. Stage 1: Scans ssm_conv1d tensors (handling long-context memory) and repairs balance between heads.
2. Stage 2: Scans blocks in chunks (via 3 parameters) and picks the best fit to weight distribution in the tensor, replacing zero blocks without touching learned structure.
3. Stage 3: Scans for noise via custom SVD (excluding token_embd.weight, output.weight, 1D tensors, bias, and norms). Reduces training noise based on the Marchenko–Pastur law while preserving 99% of signal and learned gradient.

⚡ Recommended Settings & Prompts

Chat template: Use chat_template.jinja with --jinja flag in llama.cpp / LM Studio.

• Set K Cache Quantization Type and V Cache Quantization Type to F16.
• Set GPU offload to maximum. Set number of active experts to 8.

System Prompts

For best stability and first experience, start with:

You are Qwen (Tongyi Qianwen), a large language model developed by Alibaba Group's Tongyi Lab. You are a helpful assistant.

For agentic / function calling tasks:

You are Qwen (Tongyi Qianwen), a large language model developed by Alibaba Group's Tongyi Lab. You are a helpful assistant that answers in JSON. Here's the json schema you must adhere to:
<schema>
{schema}
</schema>

Sampling Parameters

Thinking mode (coding / precision):

• Hermes agent: temperature=0.6, top_p=disabled, top_k=20, min_p=disabled, seed=42, presence_penalty=disabled, repeat_penalty=1.05
• Coding / precise tasks: temperature=0.6, top_p=disabled, top_k=20, min_p=disabled, seed=42, presence_penalty=disabled, repeat_penalty=disabled
• General: temperature=0.95, top_p=disabled, top_k=20, min_p=disabled, seed=42, presence_penalty=disabled, repeat_penalty=disabled

Non Thinking mode (creative):

• General: temperature=0.95, top_p=disabled, top_k=20, min_p=disabled, seed=42, presence_penalty=disabled, repeat_penalty=disabled
• Deterministic: temperature=0.0, top_p=disabled, top_k=20, min_p=disabled, seed=42, presence_penalty=disabled, repeat_penalty=disabled

⚡ Specs

• Total parameters: 35B (~3B active per forward pass MoE)
• Experts: 256 experts, 8 routed + 1 shared per token
• Architecture: Hybrid Gated DeltaNet linear attention + full softmax attention (3:1 ratio)
• Layers: 40 layers, pattern: 10 × (3 × DeltaNet-MoE + 1 × Attention-MoE)
• Context: 262K native context (extendable to 1M with YaRN)
• Multimodal: Natively multimodal (text, image, video) with mmproj
• Vocabulary: 248K vocabulary, 201 languages

⚡ Compatibility & Usage

Works seamlessly with llama.cpp, LM Studio, koboldcpp, and any NVFP4 / GGUF compatible runtime.

llama-cli -m Hermes3.6-35B-A3B-Uncensored-Genesis-Final-NVFP4.gguf \
  --mmproj mmproj-Hermes3.6-35B-A3B-Uncensored-Genesis-Final-F16.gguf \
  --jinja -c 131072 -ngl 99

⚡ Credits & Acknowledgments

• LuffyTheFox — Creator of the Genesis algorithm and model repair.
• HauhauCS — Base uncensored model.
• NousResearch — Hermes function calling dataset.
• jan1k — NVFP4 quantizations.