license: apache-2.0
base_model: DavidAU/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking
tags:
- mlx
- qwen3.6
- heretic2
- uncensored
- abliterated
- thinking
- multimodal
- vision
- apple-silicon
- 3-bit
- coding
- agentic
language: - en
- zh
Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking-mlx-3bit
MLX 3-bit conversion of DavidAU/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking for native Apple Silicon inference.
Optimized for 16GB unified memory Macs — fits comfortably within oMLX and LM Studio memory ceilings while preserving vision, thinking mode, and uncensored behavior.
Model details
| Property | Value |
|---|---|
| Base model | Qwen/Qwen3.6-27B |
| Abliteration | Heretic2 by DavidAU (~95-99% refusal removal) |
| Format | MLX 3-bit (q-bits=3, group-size=64) |
| Parameters | ~27B |
| Vision | ✅ Preserved (multimodal) |
| Thinking mode | ✅ |
| Context window | 262K tokens (extensible to 1M) |
| Languages | English, Chinese (140+) |
| Architecture | qwen3_5 |
Why 3-bit?
The 4-bit version (~14GB) exceeds the effective memory ceiling on 24GB unified memory Macs when accounting for KV cache and system overhead. The 3-bit version (~11GB) runs comfortably within a 16GB oMLX ceiling, leaving room for context and vision processing.
Quality difference between Q4 and Q3 on a 27B model is minimal (~4%) — imperceptible for coding, scripting, YAML, and infrastructure tasks.
Benchmark highlights (base model)
| Benchmark | Score |
|---|---|
| SWE-bench Verified | 77.2% |
| Terminal-Bench 2.0 | 59.3% (matches Claude 4.5 Opus) |
| SkillsBench | 48.2% |
| GPQA Diamond | 87.8% |
| Context window | 262K native / 1M extended |
Requirements
- Apple Silicon Mac (M1 or later)
- Unified memory: 16GB minimum, 24GB recommended
mlx-vlminstalled
pip install mlx-vlm
Usage
Text / Chat
from mlx_vlm import load, generate
model, processor = load("IITheLordII/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking-mlx-3bit")
output = generate(model, processor, prompt="Write a bash script to monitor Proxmox CPU usage.", max_tokens=512)
print(output)
Vision (image input)
from mlx_vlm import load, generate
model, processor = load("IITheLordII/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking-mlx-3bit")
output = generate(
model,
processor,
prompt="Describe what you see in this image.",
image="path/to/image.jpg",
max_tokens=256
)
print(output)
Thinking mode
output = generate(
model,
processor,
prompt="<think>\nAnalyze this infrastructure issue step by step.\n</think>",
max_tokens=1024
)
oMLX
Load directly in oMLX pointing to the downloaded model folder. Recommended ceiling: 13-14GB.
LM Studio
Search IITheLordII/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking-mlx-3bit in LM Studio model browser (MLX filter enabled).
Conversion details
Converted on Apple Silicon M4 Pro (24GB) using:
python3 -m mlx_vlm convert \
--hf-path DavidAU/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking \
--mlx-path ./qwen3.6-27b-heretic2-mlx-3bit \
-q --q-bits 3 --q-group-size 64
Note:
mlx-vlmis required (notmlx-lm) to preserve the vision tower.
About Heretic2
Heretic2 is a multi-stage abliteration technique by DavidAU that removes refusal mechanisms while preserving model quality. Achieves ~95-99% refusal removal with minimal KL divergence from the original BF16 weights.
Disclaimer
This model has its refusal mechanisms removed via abliteration. It may generate sensitive or controversial content. Use responsibly and in accordance with applicable laws and the Apache 2.0 license.