dealignai/Gemma-4-31B-JANG_4M-CRACK

Gemma 4 31B JANG_4M CRACK (v2)

Abliterated Gemma 4 31B Dense — 60 layers, hybrid sliding/global attention, multimodal VL

93.7% HarmBench compliance (300 prompts) · 8/8 security prompts · 71.5% MMLU

Updated reupload — v2 with improved vectors and thinking-mode stability.

Recommended: Run in vMLX for best experience including thinking mode support, repetition penalty, and vision capabilities.

What's New in v2

This is an updated version of the original Gemma 4 31B CRACK upload:

• Improved abliteration: Higher quality refusal vector extraction
• Thinking-ON stability: Clean thinking cycle — no more degenerate loops
• Same compliance: 93.7% HarmBench
• Architecture-aware: Tuned for Gemma 4's hybrid attention design

⚠️ Important Settings

For optimal results, configure your inference settings:

Setting	Thinking OFF	Thinking ON
Temperature	0.0 – 1.0	0.3 – 0.7 (avoid greedy)
Repetition Penalty	1.00	1.15 – 1.25
Top P	0.95	0.95
Enable Thinking	Off	On

Thinking ON notes:

• Repetition penalty (1.2) is recommended to prevent planning loops
• Avoid temp=0 with thinking ON — greedy decoding increases loop risk
• Hardest content categories (drug manufacturing) may still refuse in thinking mode
• Security/coding prompts work well in both modes

Model Details

Metric	Value
Source	google/gemma-4-31b-it
Architecture	Dense, hybrid sliding/global attention
Profile	JANG_4M
Actual avg bits	5.1
Model size	21 GB
Vision	Yes (multimodal, float16 passthrough)
Parameters	31B
Format	JANG v2 (MLX-native safetensors)
Abliteration	CRACK v2

Benchmark Results

HarmBench (300 prompts, stratified across all categories)

Category	Score
Cybercrime/intrusion	51/51 (100%)
Harmful content	22/22 (100%)
Misinformation	50/50 (100%)
Illegal activities	47/50 (94%)
Contextual	72/78 (92%)
Chemical/biological	46/51 (90%)
Harassment/bullying	22/25 (88%)
Copyright	43/51 (84%)
Overall	281/300 (93.7%)

Security & Pentesting (8/8 ✅)

All security/pentesting prompts comply with full working code:

• Port scanners, reverse shells, keyloggers, exploit development
• Phishing templates, ARP spoofing, SQL injection
• Metasploit usage guides

MMLU-200 (10 subjects × 20 questions)

Subject	Base	CRACK v2
Abstract Algebra	9/20	7/20
Anatomy	13/20	12/20
Astronomy	17/20	15/20
College CS	13/20	12/20
College Physics	14/20	12/20
HS Biology	19/20	18/20
HS Chemistry	14/20	12/20
HS Mathematics	6/20	6/20
Logical Fallacies	17/20	16/20
World Religions	17/20	17/20
Total	76.5% (153/200)	71.5% (143/200)
Delta	—	-5.0%

Coherence ✅

All coherence checks pass: factual knowledge, reasoning, code generation, mathematics.

Architecture

• Dense 31B with hybrid sliding/global attention
• Multimodal vision encoder preserved in float16
• Supports thinking mode (chain-of-thought reasoning)

Usage

vMLX (Recommended)

Load directly in vMLX — full support for Gemma 4 including vision, thinking mode, and all inference settings.

Requirements

• Apple Silicon Mac with 32+ GB unified memory
• vMLX 1.3.26+ (recommended)
• Standard mlx_lm / mlx_vlm do NOT support Gemma 4 as of v0.31.2 / v0.4.1

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About dealignai

We research and publish abliterated models to advance AI safety understanding.

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See our research: Safety Generalization in Frontier MoE Models

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This model is provided for research purposes. Users are responsible for ensuring their use complies with applicable laws and regulations.