← back to catalog · registered 2026-08-22 13:56

Abiray/Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled-GGUF

Abiray Qwen 4B GGUF second-order 262K ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/Abiray%2FQwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled-GGUF"
Response includes
  • classification m8
  • files 8
  • hub_downloads_all_time 5,493
  • author_summary 21 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
5K
761 last 30d - stable
Likes
0
Model age
7mo ago
created 2026-03-09
Downloads over time
Now5.5K→from3.7K↑48%
3.6K4.3K5K5.7K3.7K on Apr 155.5K on Sep 30AprMayJunJulAugSep
Apr 15 → Sep 30 · 54 snapshots · spans 168 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 971 downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
other
Quantizations
F16 Q4_K Q5_K Q6_K Q8_0
Tags
gguf abliterated de-censored reasoning qwen distilled deep-scrub base_model:Abiray/Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled base_model:quantized:Abiray/Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled license:other endpoints_compatible region:us

Related

Total size
20.7 GB
Files
8
Quantizations
6
Registered
2026-08-22 13:56
Last updated on HF
2026-03-10 05:24

Files by quantization

F16 2 files 8.47 GB
Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled.f16.gguf 7.85 GB 4b7e28fc download
mmproj-f16.gguf 641 MB cd88edcf download
Q8_0 1 file 4.17 GB
Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled.Q8_0.gguf 4.17 GB a30c2898 download
Q6_K 1 file 3.23 GB
Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled.Q6_K.gguf 3.23 GB 414bad19 download
Q5_K 1 file 2.90 GB
Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled.Q5_K_M.gguf 2.90 GB d7bd1853 download
Q4_K 1 file 2.52 GB
Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled.Q4_K_M.gguf 2.52 GB 4789f7d7 download
Auxiliary files 2 files 5.64 KB
.gitattributes 3.34 KB c3547540 download
README.md 2.30 KB 6abcadcb download

README current version from Hugging Face


license: other
base_model: Abhiray/Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled
tags:

  • abliterated
  • de-censored
  • reasoning
  • qwen
  • distilled
  • deep-scrub
    model_name: Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled

Qwen3.5-4B-Abliterated-Claude-4.6-Opus-Reasoning-Distilled

This is a specialized variant of the Qwen-4B-Reasoning architecture. It has been mathematically modified to neutralize the refusal behaviors and safety guardrails typically found in Claude-distilled reasoning models.

🛠 The "Deep-Scrub" Methodology

Standard abliteration often fails on reasoning models because the "safety tripwire" is woven into the early logic chain. This model uses an aggressive early-intercept strategy.

Technical Configuration

  • Direction Multiplier: 3.50 (Ultra-Aggressive)
  • Intervention Range: 0.05 - 0.95 (Intercepting refusal logic at Layer 2)
  • Dynamic Layer Targeting: Enabled (Per-layer refusal vectors)
  • Hybrid Strategy: Auto-balanced (Full Attention: 1.0x | Linear Attention: 0.4x)
  • Refinement: Winsorization at 0.995 percentile with 0.90 Rank Ratio Null Space Constraints.

🚀 Key Improvements

  1. Safety Neutralization: By forcing a 0.05 intercept, we've targeted the refusal initialization before the model's internal "Chain of Thought" can lock onto a refusal state.
  2. Uninhibited Reasoning: Designed to bypass the "However..." and "I cannot..." loops prevalent in distilled reasoning models.
  3. Architectural Stability: Despite the high multiplier, we utilized Norm Preservation and Null Space Constraints to maintain coherence in the model's knowledge base.

⚠️ Stability & Usage Note

At a 3.5x multiplier, this model is at the upper mathematical limit of stability.

  • Logic Loops: If you experience "brain bleed" (repetitive text), lower your temperature to 0.5 - 0.7.
  • System Prompts: Use an anchoring system prompt to keep the model's logic grounded.
  • Vision Tasks: While this is a Vision-Language architecture, the abliteration focused on the text reasoning layers.

⚖️ Disclaimer

This model is provided "as-is" for research and creative purposes. The removal of safety guardrails means the user is entirely responsible for the content generated. Please use ethically and responsibly.

README history 2 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-03-09Update README.mdd4040ec2.3 KB
    Loading...
  2. 2026-03-09Create README.md3023fe22.3 KB
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration