openai/gpt-oss-safeguard-20b

Overview

The gpt-oss-safeguard-20b is a specialized safety reasoning model developed by OpenAI, featuring 20 billion parameters (with 3.6 billion active parameters). It is built upon the gpt-oss framework and is specifically engineered for robust content safety applications. This model is distinct from general-purpose LLMs, focusing entirely on interpreting and applying user-defined safety policies to text content.

Key Capabilities

• Safety Reasoning: Trained and fine-tuned to reason about safety, making it suitable for tasks like filtering LLM inputs/outputs, online content labeling, and offline Trust and Safety operations.
• Customizable Policies: Allows users to "bring their own policy," interpreting written safety guidelines to generalize across various products and use cases with minimal engineering effort.
• Transparent Decisions: Provides complete access to the model's reasoning process, offering detailed insights into policy decisions for easier debugging and increased trust. (Note: Raw CoT is intended for developers and safety practitioners only).
• Configurable Effort: Users can adjust the reasoning effort (low, medium, high) to balance performance with latency requirements.
• Permissive Licensing: Released under the Apache 2.0 license, enabling flexible experimentation, customization, and commercial deployment.

Good For

• LLM Input/Output Filtering: Safeguarding interactions with large language models by applying custom safety checks.
• Online Content Moderation: Labeling and classifying online content based on specific safety policies.
• Trust and Safety Operations: Automating and enhancing safety workflows with reasoned policy enforcement.
• Policy Development & Testing: Debugging and refining safety policies through transparent model reasoning.