Momix-44/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated

TEXT GENERATIONConcurrency Cost:3Model Size:35.1BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Apr 27, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Cold

The Momix-44/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated model is a 35.1 billion parameter language model based on the Qwen 3.6 architecture, specifically an uncensored version of lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled. Developed by huihui-ai, this model has undergone "abliteration" to significantly reduce safety filtering and refusals, making it suitable for research into uncensored LLM behavior. It is quantized with an imatrix derived from the Bartowski Dataset and is primarily intended for experimental use in controlled environments where sensitive or controversial outputs are acceptable.

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Model Overview

Momix-44/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated is a 35.1 billion parameter language model derived from the Qwen 3.6 architecture. Developed by huihui-ai, this model is a modified version of lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled.

Key Differentiator: Abliteration for Uncensored Output

The primary characteristic of this model is its "abliteration" process, which significantly reduces safety filtering and refusal behaviors. This was achieved using a proof-of-concept implementation to remove refusals without TransformerLens, making it an uncensored variant. The model is quantized with an imatrix derived from the Bartowski Dataset.

Usage Warnings & Recommendations

Due to its reduced safety filtering, users should be aware of the following:

  • Risk of Sensitive or Controversial Outputs: The model may generate content that is sensitive, controversial, or inappropriate.
  • Not Suitable for All Audiences: Outputs may be unsuitable for public settings, underage users, or applications requiring strict content moderation.
  • Research and Experimental Use: It is strongly recommended for research, testing, or controlled environments, rather than production or public-facing commercial applications.
  • No Default Safety Guarantees: Unlike standard models, this version has not undergone rigorous safety optimization, and users are solely responsible for its outputs.

Deployment

This model is available for use with Ollama. A direct Ollama command is provided for running the huihui_ai/qwen3.6-abliterated:35b-Claude-4.7 version.

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