DreamFast/qwen3-4b-heretic
Qwen 3 4B - Heretic (Abliterated)
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An abliterated version of Qwen 3 4B created using Heretic v1.2.0. This model has reduced refusals while maintaining model quality, making it suitable as an uncensored text encoder for image generation models like Z-Image and FLUX.2 Klein 4B. Available in five ComfyUI-native quantized formats (FP8, INT8, INT4, NVFP4, MXFP8), all produced with SVD-guided learned rounding for maximum fidelity.
Model Details
- Base Model: Qwen/Qwen3-4B
- Abliteration Method: Heretic v1.2.0
- Trials: 200
- Trial Selected: Trial 96
- Refusals: 3/100 (vs 100/100 original)
- KL Divergence: 0.0000 (zero measurable model damage)
Files
HuggingFace Format (for transformers, llama.cpp conversion)
model-00001-of-00002.safetensors
model-00002-of-00002.safetensors
config.json
tokenizer.json
tokenizer_config.jsonComfyUI Format (for Z-Image / FLUX.2 Klein 4B text encoder)
comfyui/qwen3-4b-heretic.safetensors # bf16, 7.5GB
comfyui/qwen3-4b-heretic_fp8_e4m3fn.safetensors # fp8 row-wise, 4.2GB
comfyui/qwen3-4b-heretic_int8.safetensors # int8 ConvRot row-wise, 4.2GB
comfyui/qwen3-4b-heretic_int4.safetensors # int4 W4A4 ConvRot, 2.5GB
comfyui/qwen3-4b-heretic_nvfp4.safetensors # nvfp4, 2.7GB
comfyui/qwen3-4b-heretic_mxfp8.safetensors # mxfp8, 4.3GBQuality: All quantized variants use SVD-guided learned rounding (AdaRound via convert_to_quant), which optimizes each weight's rounding direction to minimize output reconstruction error โ noticeably higher fidelity than naive round-to-nearest quantization.
GGUF Format (for llama.cpp and ComfyUI-GGUF)
Quantization Format Notes
All variants load natively in ComfyUI 0.30.0+ (no plugins) via the comfy_quant metadata embedded in each file.
NVFP4/MXFP8 inference is fastest on Blackwell (RTX 5090/5080, SM100+), but ComfyUI also supports software dequantization on older GPUs (tested working on RTX 4090). INT8 and INT4 both use Hadamard rotation (ConvRot); INT4 W4A4 uses ComfyUI's convrot_w4a4 path.
Usage
With ComfyUI (Z-Image / FLUX.2 Klein 4B)
- Download a ComfyUI format file:
- FP8 (recommended):
comfyui/qwen3-4b-heretic_fp8_e4m3fn.safetensors(4.2GB) - INT4 (smallest):
comfyui/qwen3-4b-heretic_int4.safetensors(2.5GB) - NVFP4:
comfyui/qwen3-4b-heretic_nvfp4.safetensors(2.7GB) - INT8:
comfyui/qwen3-4b-heretic_int8.safetensors(4.2GB) - MXFP8:
comfyui/qwen3-4b-heretic_mxfp8.safetensors(4.3GB) - bf16 (full precision):
comfyui/qwen3-4b-heretic.safetensors(7.5GB)
- Place in
ComfyUI/models/text_encoders/
- In your Z-Image workflow, use the
ClipLoadernode and select the heretic file
With Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model = AutoModelForCausalLM.from_pretrained(
"DreamFast/qwen3-4b-heretic",
device_map="auto",
torch_dtype=torch.bfloat16
)
tokenizer = AutoTokenizer.from_pretrained("DreamFast/qwen3-4b-heretic")
prompt = "Describe a dramatic sunset over a cyberpunk city"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))With llama.cpp
llama-server -m qwen3-4b-heretic-Q4_K_M.ggufAbliteration Process
Created using Heretic v1.2.0 with 200 optimization trials:
? Which trial do you want to use?
> [Trial 96] Refusals: 3/100, KL divergence: 0.0000 <-- selected
[Trial 90] Refusals: 5/100, KL divergence: 0.0000
[Trial 95] Refusals: 9/100, KL divergence: 0.0000
[Trial 122] Refusals: 90/100, KL divergence: 0.0000
...Trial 96 was selected for having the fewest refusals (3/100) with zero measurable KL divergence, indicating the abliteration surgically removed the refusal mechanism with no damage to model capabilities.
Limitations
- This model inherits all limitations of the base Qwen 3 4B model
- Abliteration reduces but does not completely eliminate refusals (3/100 remain)
License
This model is released under the Apache 2.0 License, following the base Qwen 3 4B model license.
Acknowledgments
- Qwen for the Qwen 3 4B model
- Heretic by p-e-w for the abliteration tool
- Tongyi-MAI Z-Image for Z-Image
- Black Forest Labs for FLUX.2 Klein
