OpenAI gpt-oss-safeguard Technical Report
OpenAI has released gpt-oss-safeguard-120b and gpt-oss-safeguard-20b, open-weight reasoning models designed to classify content according to a provided policy. These models are post-trained from the gpt-oss family and are available under the Apache 2.0 license.
Model Versions and Licensing
gpt-oss-safeguard models are available in two sizes: 120b and 20b. These models are text-only and are compatible with the Responses API. They are released under the Apache 2.0 license and OpenAI's gpt-oss usage policy.
Technical Capabilities and Customization
These models are designed for policy-based content classification. They are optimized to reason through a provided policy to determine if content should be labeled accordingly. Key technical features include:
Chain-of-Thought (CoT): The models provide full chain-of-thought reasoning, allowing users to see the internal logic used to reach a classification decision.
Reasoning Effort Levels: Users can configure the models with different reasoning efforts (low, medium, high) to balance performance and latency.
Structured Outputs: The models support Structured Outputs, ensuring that classification labels are returned in a predictable, machine-readable format.
Intended Use and Application
OpenAI recommends using gpt-oss-safeguard models as a classification layer rather than as the core user-facing functionality of an application. For general-purpose interaction, the original gpt-oss models are better suited.
Safety and Risk Assessment
Because these models are open-weight, OpenAI conducted safety evaluations to ensure they meet safety standards even if used in a chat setting, despite this not being their intended primary use case.
Regarding frontier risks, OpenAI states that the models were fine-tuned from gpt-oss without any additional biological or cybersecurity data. Consequently, the risk assessments performed during the original gpt-oss release—specifically the work on estimating worst-case scenarios—cross-apply to the gpt-oss-safeguard series.