Qwen3.5 9B abliterated GGUF EU AI Act Compliance Profile

Qwen3.5-9B-abliterated-GGUF

GGUF quantized versions of lukey03/Qwen3.5-9B-abliterated for use with Ollama, llama.cpp, and other GGUF-compatible inference engines.

Quick Start

Text-only

ollama run lukey03/qwen3.5-9b-abliterated

With Vision

ollama run lukey03/qwen3.5-9b-abliterated-vision

Requires Ollama 0.17.1+.

Available Files

| File | Quant | Size | Description | |------|-------|------|-------------| | Qwen3.5-9B-abliterated-vision-Q4_K_M.gguf | Q4_K_M | ~6.1 GB | Vision + Text — abliterated text weights merged into official Qwen3.5-9B with full vision encoder | | Qwen3.5-9B-abliterated-Q4_K_M.gguf | Q4_K_M | ~5.2 GB | Text-only — no vision support | | Qwen3.5-9B-abliterated-F16.gguf | F16 | ~17 GB | Text-only, full precision |

Vision Model Details

Qwen3.5 is natively multimodal — vision is built into every Qwen3.5 model via early fusion training. There is no separate "VL" variant. The vision GGUF was created by:

1. Starting with the official Qwen/Qwen3.5-9B GGUF (883 tensors: 427 text + 441 vision + 15 MTP)
2. Replacing 400 text model tensors with abliterated weights (the remaining 27 text tensors use different quantization types and are not affected by abliteration — they target attn_qkv and attn_v, while abliteration only modifies o_proj/output_proj and down_proj)
3. Keeping all 441 vision encoder tensors and 15 MTP (multi-token prediction) tensors from the official model

About

This is a fully uncensored version of Qwen3.5-9B with all refusal behavior removed using a two-stage approach: 3 iterative passes of orthogonal projection (Arditi et al., 2024) followed by LoRA fine-tuning on stubborn refusal categories.

• Abliteration rate: 100% (18/18 test prompts answered vs 0/18 for base model)
• Stage 1: Ortho

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Base Model