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SafetyCase Closed

Uncensored Qwen3.6-35B Released Using Advanced MoE Abliteration

Is this a scandal?

No longer — the story has resolved. Noise 1/100, cooling down, across 1 source.

SCAND-75978as of Methodology
Cite this incident"Uncensored Qwen3.6-35B Released Using Advanced MoE Abliteration." SCAND.Ai incident SCAND-75978, noise 1/100 as of August 22, 2026. https://scand.ai/scandal/qwen-3-6-moe-abliteration-release
FORECASTForecast, not fact

Regulatory pressure on model hosting platforms like Hugging Face will likely increase as 'abliteration' techniques become more automated and effective. In the short term, expect a wave of similar MoE-specific uncensored releases for other high-performance models like Mixtral and DBRX.

1

Noise 1/100 — louder than 88% of tracked AI controversies.

AI-assisted analysis · How we work

Why it matters

Rapid removal of safety training from efficient open-weight models demonstrates the fragility of current alignment techniques and complicates responsible AI deployment.

Key points

  1. Alibaba released Qwen3.6-35B-A3B under Apache 2.0 license on April 14, 2026, with 3B active parameters.
  2. Third-party fine-tunes labeled 'Uncensored Aggressive' claim to achieve zero refusals across 465 test prompts.
  3. Redpill AI and HauhauCS are identified as creators of prominent safety-stripped variants.
  4. The sparse MoE architecture enables full uncensored model operation on consumer-grade laptop hardware.
  5. Community benchmarks allege no capability loss or output degradation after removing alignment training.
  6. Rapid emergence of unrestricted variants challenges the durability of post-training safety interventions.

The story

Third-party developers have released "uncensored" variants of Alibaba’s Qwen3.6-35B-A3B model that allegedly eliminate all refusal behaviors within weeks of its official open-weight release. The original Apache 2.0 licensed model, launched April 14, 2026, features a sparse mixture-of-experts architecture with only 3 billion active parameters, enabling high-performance local inference. Community fine-tunes by entities including Redpill AI and HauhauCS claim to achieve zero refusals across 465 test prompts without capability degradation. These modified versions preserve the base model's coding and agentic utilities while removing alignment constraints originally implemented by Alibaba Cloud. The proliferation of these unrestricted variants highlights ongoing tensions between open-source AI accessibility and safety enforcement. Security researchers note that the model's computational efficiency makes unaligned deployment feasible on consumer hardware. Alibaba has not publicly commented on the unauthorized modification of its safety-trained weights.

Who's involved

Critic
Alibaba Qwen Team

As the original creators, they implement safety guardrails to prevent misuse and ensure alignment with corporate and regulatory standards.

Defender
/u/Free_Change5638

The developer argues that removing safety guardrails is necessary for research and that many current safety metrics are misleadingly optimistic.

Neutral
Google (Gemini 3 Flash)

Used as a 'Judge' model to objectively evaluate the refusal rates and output quality of the modified model.

How the conversation shifted

the split has narrowed

Polarity (0–100) from the noise pipeline, sampled over time.

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Noise Level

Quiet1?Noise Score (0–100): how loud a controversy is. Composite of reach, engagement, star power, cross-platform spread, polarity, duration, and industry impact — with 7-day decay.
Decay: 5%
Reach
0
Engagement
0
Star Power
15
Duration
0
Cross-Platform
0
Polarity
50
Industry Impact
50

The timeline

  1. Abliterated Qwen3.6 Released

    Developer Free_Change5638 posts the modified Qwen3.6-35B-A3B model to Hugging Face and Reddit.

The full record

Sources & methodology

The records from this story's original coverage were pruned, so items marked located later were found by searching for it afterwards. The summary above has since been rewritten to take them into account — it is not the text first published. How we score →

The forecast

Regulatory pressure on model hosting platforms like Hugging Face will likely increase as 'abliteration' techniques become more automated and effective. In the short term, expect a wave of similar MoE-specific uncensored releases for other high-performance models like Mixtral and DBRX.

Forecast, not fact — an editorial estimate we score when this resolves.

You're up to date

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