AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16

Hugging Face
VISIONConcurrent Unit Cost:2Model Size:27BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 15, 2026License:apache-2.0Architecture:Transformer0.2K Open Weights Featherless Exclusive Warm

AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16 is an uncensored, BF16 version of Alibaba's Qwen3.8-27B model, developed by AEON-7. This 27 billion parameter model has undergone a specialized 'abliteration' process to remove refusal layers, enhancing coherence and directness in responses. It is optimized for use cases requiring unfiltered output, such as security research, red-teaming, and creative writing without content restrictions.

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Overview

AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16 is an early access draft of an uncensored version of Alibaba's Qwen3.8-27B model. Developed by AEON-7, this model has been specifically modified to remove refusal layers, aiming for greater coherence and directness in its answers. The abliteration process involved a custom methodology to retain instructional integrity while eliminating censorship, resulting in a model that provides answers without safety monologues or lectures.

Key Capabilities & Features

  • Uncensored Output: Designed to provide direct answers without internal refusal behaviors, even for sensitive or controversial topics.
  • Enhanced Coherence: Optimized for better answer quality and thought continuity, particularly for ordinary work and shorter requests.
  • BF16 Precision: Released in BF16 (BFloat16) full precision, serving as the master for potential future quantized versions.
  • Integrated Vision & MTP: Retains the unmodified vision tower and native MTP (Multi-Turn Prediction) head from the base Qwen3.8-27B model.
  • Custom Abliteration: Utilizes abliterix 1.12.2 and a custom bench to surgically remove refusal layers while preserving useful model structure.

Limitations (Early Access Draft)

  • Long-Context Edge Cases: May exhibit small gaps, loops, or repetitive phrases on extremely long requests as the answer stretches.
  • User Responsibility: Due to its uncensored nature, users are solely responsible for all prompts, responses, and downstream actions, requiring implementation of their own safety layers.

Good For

  • Security Research: Ideal for exploring model vulnerabilities and behaviors without built-in restrictions.
  • Red-Teaming & Alignment Work: Useful for testing and developing robust AI systems.
  • Creative Writing: Enables unrestricted creative expression without content filters.
  • Conversations: Suitable for topics that base models might refuse due to social norms or safety alignments.