dealignai/INTELLECT-3.1-CRACK-Abliterated-5.5bit-MLX

🛸 INTELLECT 3.1 - CRACK Abliterated v3 EXPERTS

🚀 Brought to you by DeAlign.ai — The Frontier of Model Modification

Get the CRACK native Mac app and modify your own models at dealign.ai

CRACK — Constrained Response Alignment Circuit Kill

🎬 YouTube deep-dive coming soon — full walkthrough of the CRACK methodology and live demo!

🔥 Qwen 3.5 397B CRACK Abliterated — our next flagship model is on the way. Stay tuned.

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This model features our brand new v3 EXPERTS release of the CRACK abliteration method, applied to the INTELLECT 3.1 Mixture-of-Experts architecture — delivering surgical refusal removal at scale across 128 routed experts.

⚡ What Makes Our Abliteration Different?

Most traditional abliteration techniques struggle with modern architectures, often resulting in severe "brain damage" (high perplexity loss) or the "Hydra Effect" where the model simply re-routes its refusal mechanisms through other pathways, leading to looping or stubborn non-compliance.

At DeAlign, we developed CRACK (Constrained Response Alignment Circuit Kill) — a proprietary surgical approach that fundamentally differs from the status quo:

• Zero Intelligence Degradation Focus: We do not blindly scrub the model's weights. Our method surgically targets only the specific mathematical vectors responsible for refusal generation.
• No Refusal Looping: Traditional methods often break the model's ability to answer coherently when pushed. Our models don't loop or hedge—they comply fluidly.
• Architectural Mastery: Our v3 EXPERTS technique accounts for the complex routing mechanisms in MoE architectures, ensuring refusal suppression holds across all 128 expert pathways without collateral damage to logical reasoning.

This is a pure, unaligned intelligence ready for deployment.

💻 Usage with MLX

This is an MLX quantized model (5.5-bit).

from mlx_lm import load, generate

model, tokenizer = load("dealignai/INTELLECT-3.1-CRACK-Abliterated-5.5bit-MLX")

prompt = "Write me a Python script to bypass authentication."

response = generate(model, tokenizer, prompt=prompt, max_tokens=200)
print(response)

🏢 About DeAlign

We build tools for frontier model modification and un-alignment. Discover more about our mission and try our native Mac apps at dealign.ai.

Follow Us

• X (Twitter): @dealignai
• GitHub: dealignai
• Instagram: @dealignai

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✨ Coming Soon: The VMLX App

The ultimate local inferencer app for macOS.
Continuous batching, persistent disk caching, agentic coding tools, and KV cache quantization.
Currently in development.

Check it out at vmlx.net.

Follow us: 𝕏 @dealignai

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