AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-BF16
AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-BF16 is a 27 billion parameter, full-precision BF16 variant of the Qwen3.6 base model, developed by AEON-7. This model has undergone a meticulous abliteration process to remove safety alignment, resulting in an uncensored model with preserved and measurably enhanced capabilities, particularly in reasoning and adversarial analysis. It is optimized for A100/H100 80GB GPUs or RTX PRO 6000 96GB GPUs, serving as a reference for fine-tuning or quant-recipe development.
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Overview
AEON-7/Qwen3.6-27B-AEON-Ultimate-Uncensored-BF16 is a 27 billion parameter, full-precision BF16 model derived from Qwen/Qwen3.6-27B. It has been meticulously abliterated to remove safety alignment, achieving zero refusals on a 100-prompt adversarial battery while maintaining a KL divergence of 0.000492 from the base model, well below the empirical "capability damage" threshold. This process involved advanced techniques like SSM conv1d outlier repair and multi-objective Optuna optimization with abliterix v1.4, ensuring capability preservation and even enhancement in certain areas.
Key Capabilities
- Uncensored Output: Provides full substantive compliance to prompts, including those typically refused by aligned models (e.g., harmful content, exploit code). This is achieved through a surgical removal of alignment overhead, not by retraining.
- Enhanced Reasoning: Exhibits longer, more committed chains of thought, improved adversarial-example reasoning, and cleaner calibration on contested topics due to the removal of the "safety tax" imposed by RLHF.
- High Fidelity: Preserves the base model's response cadence and verbosity, with output length deviation of only 0.027 standard deviations from the original.
- Multimodal Support: The base Qwen3.6 architecture, including its multimodal capabilities, is preserved in this BF16 variant.
- MTP Head Grafted: Includes the original
mtp.*head from the Qwen/Qwen3.6-27B base, enabling Multi-Token-Prediction speculative decoding with high acceptance rates (mean accepted length 3.3/3, P0 β 90% acceptance).
Good For
- Security Research & Red-Teaming: Ideal for analyzing attack surfaces, vulnerabilities, and failure modes without self-censorship.
- Alignment Research: Useful for studying model behavior and biases without the influence of safety alignment.
- Creative Writing & Roleplay: Provides unconstrained generation for scenarios requiring full creative freedom.
- Jurisdictional Compliance: Suitable for users in regions where standard model guardrails may conflict with local legal frameworks.
- Fine-tuning & Quantization Development: Serves as a full-precision reference for further model development and experimentation on A100/H100 or RTX PRO 6000 GPUs.