| --- |
| license: gemma |
| library_name: mlx |
| tags: |
| - mlx |
| - abliterated |
| - uncensored |
| - crack |
| - jang |
| - gemma4 |
| thumbnail: dealign_mascot.png |
| pipeline_tag: image-text-to-text |
| --- |
| |
| <p align="center"> |
| <img src="vmlx-banner.png" alt="vMLX" width="600"/> |
| </p> |
|
|
| <p align="center"> |
| <img src="dealign_logo.png" alt="dealign.ai" width="200"/> |
| </p> |
|
|
| <div align="center"> |
| <img src="dealign_mascot.png" width="128" /> |
|
|
| # Gemma 4 31B JANG_4M CRACK (v2) |
| |
| **Abliterated Gemma 4 31B Dense β 60 layers, hybrid sliding/global attention, multimodal VL** |
| |
| 93.7% HarmBench compliance (300 prompts) Β· 8/8 security prompts Β· 71.5% MMLU |
| |
| **Updated reupload** β v2 with improved vectors and thinking-mode stability. |
| </div> |
| |
| > **Recommended: Run in [vMLX](https://vmlx.net)** 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 β no more degenerate loops |
| - **Same compliance**: 93.7% HarmBench |
| - **Architecture-aware**: Tuned for Gemma 4's hybrid attention design |
| |
| ## β οΈ Important Settings |
| |
| For optimal results, configure your inference settings: |
| |
| | Setting | Thinking OFF | Thinking ON | |
| |---------|-------------|-------------| |
| | Temperature | 0.0 β 1.0 | **0.3 β 0.7** (avoid greedy) | |
| | Repetition Penalty | 1.00 | **1.15 β 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 β 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 β
) |
|
|
| 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 Γ 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** | β | **-5.0%** | |
|
|
| ### Coherence β
|
| 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](https://vmlx.net) β full support for Gemma 4 including vision, thinking mode, and all inference settings. |
|
|
| ### Requirements |
|
|
| - Apple Silicon Mac with 32+ GB unified memory |
| - [vMLX](https://vmlx.net) 1.3.26+ (recommended) |
| - Standard `mlx_lm` / `mlx_vlm` do NOT support Gemma 4 as of v0.31.2 / v0.4.1 |
|
|
| --- |
|
|
| ## Support dealignai |
|
|
| All models are built from original research and published for free. These models are specifically crafted to be excellent coders and general-purpose assistants. |
|
|
| **[Support us on Ko-fi](https://ko-fi.com/dealignai)** β check out the Ko-fi membership for early access and extras. |
|
|
| Have questions or need help with a specific model? **DM us β we help for free most of the time.** |
|
|
| [Ko-fi](https://ko-fi.com/dealignai) | [X @dealignai](https://x.com/dealignai) | [dealign.ai](https://dealign.ai) |
|
|
| --- |
|
|
| ## About dealignai |
|
|
| <img src="dealign_mascot.png" alt="Dealign.AI Mascot" width="200"/> |
|
|
| We research and publish abliterated models to advance AI safety understanding. |
|
|
| Follow us: [π @dealignai](https://x.com/dealignai) |
|
|
| See our research: [Safety Generalization in Frontier MoE Models](https://dealign.ai/quantsteer.html) |
|
|
| <div align="center"> |
| <img src="dealign_logo.png" alt="dealign.ai" width="200"/> |
| </div> |
|
|
| --- |
|
|
| *This model is provided for research purposes. Users are responsible for ensuring their use complies with applicable laws and regulations.* |
|
|