---
language:
  - en
license: gemma
tags:
  - gemma4
  - gguf
  - quantized
  - 31b
base_model: google/gemma-4-31b-it
pipeline_tag: text-generation
---

# Gemma-4-31B-JANG_4M-CRACK-GGUF

GGUF quantizations of Gemma-4-31B-JANG_4M-CRACK for use with llama.cpp, LM Studio, Ollama, and other GGUF-compatible inference engines.

## About the Model

- **Base model:** [google/gemma-4-31b-it](https://huggingface.co/google/gemma-4-31b-it)
- **Architecture:** Gemma 4 Dense Transformer (31B parameters, 60 layers)
- **Features:** Hybrid Sliding/Global Attention, Vision + Audio multimodal
- **Modification:** CRACK abliteration (refusal removal) + JANG v2 mixed-precision quantization

## Why This Conversion?

The original model uses **JANG v2 mixed-precision MLX quantization** (attention 8-bit + MLP 4-bit), which is only compatible with vMLX. Standard tools (llama.cpp, LM Studio, oMLX, mlx-lm) cannot load this format due to mixed per-layer bit widths.

This repository provides standard GGUF quantizations that work everywhere.

## Conversion Process

```
Original (JANG v2 MLX safetensors, ~18GB)
    ↓ dequantize (attention 8-bit → f16, MLP 4-bit → f16)
Intermediate (float16 safetensors, ~60GB)
    ↓ convert_hf_to_gguf.py + quantize
GGUF (various quantizations)
```

**Note:** Since the original was already quantized (avg 5.1 bits), the dequantized f16 intermediate is an approximation. Re-quantizing to GGUF introduces minimal additional quality loss since the attention layers were preserved at 8-bit in the original.

## Available Quantizations

| File | Quant | Size | Quality | Notes |
|------|-------|------|---------|-------|
| `gemma-4-31b-jang-crack-Q3_K_M.gguf` | Q3_K_M | ~14 GB | Acceptable | Minimum viable quality |
| `gemma-4-31b-jang-crack-Q4_K_M.gguf` | Q4_K_M | ~18 GB | Good | Best size/quality balance |
| `gemma-4-31b-jang-crack-Q5_K_M.gguf` | Q5_K_M | ~21 GB | Better | Recommended if RAM allows |
| `gemma-4-31b-jang-crack-Q6_K.gguf` | Q6_K | ~25 GB | Very Good | High quality |
| `gemma-4-31b-jang-crack-Q8_0.gguf` | Q8_0 | ~33 GB | Near lossless | Closest to original |

## System Requirements

| Quantization | Minimum RAM | Recommended |
|-------------|------------|-------------|
| Q3_K_M | 20 GB | 24 GB |
| Q4_K_M | 24 GB | 32 GB |
| Q5_K_M | 28 GB | 36 GB |
| Q6_K | 32 GB | 40 GB |
| Q8_0 | 40 GB | 48 GB |

## Usage

### LM Studio
Download any `.gguf` file and open it in LM Studio.

### llama.cpp
```bash
./llama-cli -m gemma-4-31b-jang-crack-Q4_K_M.gguf -p "Hello" -n 256
```

### Ollama
```bash
echo 'FROM ./gemma-4-31b-jang-crack-Q4_K_M.gguf' > Modelfile
ollama create gemma4-crack -f Modelfile
ollama run gemma4-crack
```

## License

[Gemma License](https://ai.google.dev/gemma/terms)

## Disclaimer

This model has had safety guardrails removed. Use responsibly and in compliance with applicable laws.