OpenAI: gpt-oss-safeguard-20b
OpenAI's gpt-oss-safeguard-20b is a specialised safety-focused model with tool and function calling support, but without any benchmark data available it cannot be scored above the conservative range — its niche use case limits broad business applicability.
Assessment date: March 12, 2026
Our methodology takes into account a range of factors including pricing, functionality, capabilities, benchmark performance, and real-world applicability. Rankings are reviewed and updated regularly as new models are released. Issues with our rankings? Contact us
gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model offers lower latency for safety tasks like content classification, LLM filtering, and trust & safety labeling. Learn more about this model in OpenAI's gpt-oss-safeguard user guide.
Capabilities
Architecture
| Modality | Text → Text |
| Tokenizer | GPT |
| Parameters | 20B |
Model Information
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.08 | $0.000075 |
| Output | $0.30 | $0.000300 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
