Qwen3 30B A3B abliterated

Qwen 3

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

Released April 202541K context≈ 30,720 words30B params

A community-modified variant of Qwen3 30B A3B with abliteration applied — a technique that removes refusal behaviors from the model's weights. This means it responds without the typical safety-trained hesitations or content restrictions. It's a sparse mixture-of-experts architecture activating 3B parameters per forward pass, so it runs leaner than its 30B total parameter count suggests.

Capabilities

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

Multilingual

Moderate

Reasoning & Logic

Qwen3 30B A3B abliterated

Qwen 3

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

Released April 202541K context≈ 30,720 words30B params

A community-modified variant of Qwen3 30B A3B with abliteration applied — a technique that removes refusal behaviors from the model's weights. This means it responds without the typical safety-trained hesitations or content restrictions. It's a sparse mixture-of-experts architecture activating 3B parameters per forward pass, so it runs leaner than its 30B total parameter count suggests.

Capabilities

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

Multilingual

Moderate

Reasoning & Logic

Glossary

AbliterationA technique that removes or disables a model's built-in safety refusal mechanisms, allowing it to respond to a wider range of requests.ArchitectureThe underlying structural design of a neural network that defines how data flows through layers and components.Community-ModifiedA model that has been altered or fine-tuned by users outside the original development team, often to change its behavior or capabilities.Content RestrictionsSafety guidelines and filters built into a model to prevent it from generating harmful, illegal, or unethical content.Forward PassA single computation cycle where input data flows through the model's layers to produce an output prediction.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.WeightsThe numerical parameters inside a neural network that determine how it processes input and generates output.

Capabilities

Capabilities

Use Case Fit

Glossary