Qwen3.5 122B A10B Uncensored HauhauCS Aggressive

Qwen3.5

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

Released March 2026context N/A122B params

A heavily modified, uncensored variant of Qwen3.5 122B with aggressive fine-tuning applied by HauhauCS, this model prioritizes unfiltered output over safety guardrails. It handles text and image inputs, making it multimodal, but the 'aggressive' tuning means responses can be blunt, unrestrained, and potentially unpredictable in tone. The sparse 10B active parameters (MoE architecture) keep inference costs lower than the full parameter count suggests.

Capabilities

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

Creative Writing

Strong

Reasoning & Logic

Qwen3.5 122B A10B Uncensored HauhauCS Aggressive

Qwen3.5

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

Released March 2026context N/A122B params

A heavily modified, uncensored variant of Qwen3.5 122B with aggressive fine-tuning applied by HauhauCS, this model prioritizes unfiltered output over safety guardrails. It handles text and image inputs, making it multimodal, but the 'aggressive' tuning means responses can be blunt, unrestrained, and potentially unpredictable in tone. The sparse 10B active parameters (MoE architecture) keep inference costs lower than the full parameter count suggests.

Capabilities

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

Creative Writing

Strong

Reasoning & Logic

Glossary

Active ParametersThe subset of a model's total parameters that are actually used during inference for each input, as opposed to all parameters being used every time.ArchitectureThe underlying structural design of a neural network that defines how data flows through layers and components.Fine-TuningThe process of further training a pre-trained model on new data to adapt it for specific tasks or domains.GuardrailsSafety mechanisms built into a model to refuse harmful requests or prevent it from generating unsafe content.InferenceThe process of running a trained model to generate predictions or outputs from new inputs.MultimodalA model that can process and understand multiple types of input, such as both text and images.Parameter CountThe total number of adjustable weights in a model; more parameters generally mean more capacity to learn, but also require more computing power.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.Safety GuardrailsBuilt-in restrictions or filters that prevent a model from generating harmful, illegal, or unethical content.UncensoredA model without built-in safety filters or content restrictions, allowing it to generate responses on any topic without refusal.

Capabilities

Capabilities

Use Case Fit

Glossary