Gemma4 31B QAT Uncensored HauhauCS Balanced MTP

gemma

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released June 2026context N/A31B params

A community fine-tune of Google's Gemma 4 31B that removes default safety restrictions and applies quantization-aware training for efficient deployment. The 'Balanced' tag suggests HauhauCS tuned it to avoid overcorrection in either refusal rate or output quality. Accepts both text and image inputs, distributed in GGUF format for local inference.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Factual Knowledge

Strong

Reasoning & Logic

Strong

Creative Writing

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

Gemma4 31B QAT Uncensored HauhauCS Balanced MTP

gemma

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released June 2026context N/A31B params

A community fine-tune of Google's Gemma 4 31B that removes default safety restrictions and applies quantization-aware training for efficient deployment. The 'Balanced' tag suggests HauhauCS tuned it to avoid overcorrection in either refusal rate or output quality. Accepts both text and image inputs, distributed in GGUF format for local inference.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Factual Knowledge

Strong

Reasoning & Logic

Strong

Creative Writing

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

Glossary

Community Fine-TuneA model variant created and shared by the community rather than the original model creators, often with custom modifications.Fine-TuneA model created by training an existing pre-trained model on new data to specialize it for specific tasks or behaviors.GGUFA file format for quantized models designed for efficient CPU and GPU inference with llama.cpp.GGUF FormatA file format designed for efficient storage and loading of large language and embedding models, optimized for fast inference on various hardware.InferenceThe process of running a trained model to generate predictions or outputs from new inputs.Local InferenceRunning an AI model directly on your own computer rather than sending data to a remote server, keeping data private and reducing latency.QuantizationReducing a model's numerical precision (e.g., from 16-bit to 4-bit) to shrink memory usage and speed up inference.Quantization-Aware TrainingA training technique where a model learns to maintain performance even when its weights are compressed to use less memory and compute.Safety RestrictionsBuilt-in guardrails in a model that prevent it from generating harmful, illegal, or unethical content by refusing certain requests.