---

license: apache-2.0

tags:

• text-generation
• gguf
• nvfp4
• fp4
• moe
• qwen3.6
• uncensored
• vision
• multimodal
• genesis
• llama-cpp

language:

• en
• zh
• multilingual

pipeline_tag: image-text-to-text

base_model:

• HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
• LuffyTheFox/Qwen3.6-35B-A3B-Uncensored-Genesis-Final-GGUF

base_model_relation: quantized

---

Qwen3.6-35B-A3B-Uncensored-Genesis — NVFP4 GGUF

NVFP4 quantisation of

LuffyTheFox/Qwen3.6-35B-A3B-Uncensored-Genesis-Final-GGUF,

built with advanced-gguf-quantizer

(a llama.cpp fork focused on NVFP4/MXFP6 quantization).

This is the non-Hermes version — Genesis tensor repair on the

HauhauCS uncensored base, without the Hermes finetune transfer.

For the Hermes version, see

jan1k/Qwen3.6-35B-A3B-Uncensored-Genesis-Hermes-Final-NVFP4-GGUF.

Files

v4 — Recommended (inline scales, LM Studio compatible)

| File | Size | Tensors |

|---|---|---|

| Qwen3.6-35B-A3B-Uncensored-Genesis-NVFP4-v4.gguf | ~20 GB | 733 |

| mmproj-Qwen3.6-35B-A3B-Uncensored-Genesis-Final-F16.gguf | ~899 MB | vision projector |

Re-quantised 2026-09-24 from Luffy's updated Q8_K_P source.

v4 uses --nvfp4-inline-scales-only to emit native inline UE4M3 scales

without separate .scale/.input_scale tensors. This is required for

LM Studio / Pelican and other runtimes that do not support the extended

NVFP4 scale tensor contract.

Imatrix variants will follow after the plain v4 is confirmed working

in target runtimes.

Source

| | |

|---|---|

| Source GGUF | Qwen3.6-35B-A3B-Uncensored-Genesis-Final-Q8_K_P.gguf (43.6 GB, 10.06 BPW) |

| Architecture | qwen35moe (MoE), 35B total / ~3B active, 40 layers |

| Context | 262144 |

| general.file_type | 39 (LLAMA_FTYPE_MOSTLY_NVFP4) |

| MTP/NextN | none |

Two-step pipeline: Q8_K_P -> F16 intermediate -> NVFP4. The F16 step gives

the NVFP4 encoder clean data (no Q8_0 quantization noise).

Tensor mix (v4)

| type | count | notes |

|---|---|---|

| F32 | 331 | norms, ssm scalars, gate inputs |

| F16 | 175 | sensitive weights (blk.0 attn, ssm, etc.) |

| Q6_K | 1 | output.weight |

| NVFP4 | 226 | bulk weights |

| total | 733 | |

| separate .scale/.input_scale | 0 | inline UE4M3 only |

Format fix (v3/v2 -> v4)

The older v2/v3 files use the extended NVFP4 format with separate

.scale and .input_scale tensors. Runtimes like LM Studio / Pelican

only read inline UE4M3 scales and ignore the separate scale tensors,

producing garbage output.

v4 uses --nvfp4-inline-scales-only to:

• Skip writing .scale and .input_scale tensors
• Force tensor_scale=1.0 (no pre-scaling)
• Force input_scale=identity
• Make inline UE4M3 scales self-contained

Tensor protection policy

F16 singular-collapse protection:

| tensor | type |

|---|---|

| blk.0.attn_gate.weight | F16 |

| blk.0.attn_qkv.weight | F16 |

| blk.0.ffn_down_exps.weight | F16 |

| blk.13.ffn_down_exps.weight | F16 |

F32 architecture-specific protection:

| tensor | reason |

|---|---|

| blk.*.attn_norm.weight | 1D norm |

| blk.*.post_attention_norm.weight | 1D norm |

| blk.*.attn_q_norm.weight | 1D norm |

| blk.*.attn_k_norm.weight | 1D norm |

| blk.*.ssm_norm.weight | 1D norm |

| output_norm.weight | 1D norm |

| blk.*.ssm_conv1d.weight | CUDA SSM conv kernel requires F32 |

| blk.*.ssm_dt.bias | SSM scalar, kernel compatibility |

| blk.*.ssm_a | SSM scalar, kernel compatibility |

| blk.*.ffn_gate_inp_shexp.weight | shared expert gate input |

| token_embd.weight | F16 (embedding quality) |

Forced NVFP4 (do not push lower):

| tensor | type |

|---|---|

| blk.0.ssm_out.weight | NVFP4 |

| blk.1.attn_gate.weight | NVFP4 |

| blk.1.attn_qkv.weight | NVFP4 |

Usage

llama-cli -m Qwen3.6-35B-A3B-Uncensored-Genesis-NVFP4-v4.gguf \
  --mmproj mmproj-Qwen3.6-35B-A3B-Uncensored-Genesis-Final-F16.gguf \
  --jinja -c 131072 -ngl 99

• Set K cache and V cache quantization to F16
• Set GPU offload to maximum, active experts to 8
• Set number of layers for which to force MoE weights onto CPU to 40

Hardware

• Blackwell (RTX 50xx): native FP4 path, fastest
• Ampere (RTX 30xx): NVFP4 inference works via fallback kernels
• Quantisation was done CPU-only (Ampere CUDA NVFP4 encoder hangs on MoE)

Reproducibility

# Step 1: Q8_K_P -> F16 intermediate
llama-quantize --allow-requantize \
  Qwen3.6-35B-A3B-Uncensored-Genesis-Q8_K_P.gguf temp_f16.gguf F16 6

# Step 2: F16 -> NVFP4 v4 (inline scales only, CPU-only)
CUDA_VISIBLE_DEVICES="" llama-quantize \
  --allow-requantize \
  --nvfp4-inline-scales-only \
  --tensor-type-file tensor_types_protection.txt \
  temp_f16.gguf \
  Qwen3.6-35B-A3B-Uncensored-Genesis-NVFP4-v4.gguf \
  NVFP4 6

# Cleanup
rm temp_f16.gguf

Credits

• Base model: HauhauCS (0/465 refusals)
• Genesis tensor repair: LuffyTheFox
• NVFP4 quantisation: jan1k
• Quantiser: advanced-gguf-quantizer