gpt-oss-safeguard-120b
and
gpt-oss-safeguard-20b
are safety reasoning models built-upon gpt-oss. With these models, you can classify text content based on safety policies that you provide and perform a suite of foundational safety tasks. These models are intended for safety use cases. For other applications, we recommend using
gpt-oss models
.
This model
gpt-oss-safeguard-20b
(21B parameters with 3.6B active parameters) fits into GPUs with 16GB of VRAM. Check out
gpt-oss-safeguard-120b
(117B parameters with 5.1B active parameters) for the larger model.
Both models were trained on our
harmony response format
and should only be used with the harmony format as it will not work correctly otherwise.
Highlights
Trained to reason about safety
: Trained and tuned for safety reasoning to accommodate use cases like LLM input-output filtering, online content labeling and offline labeling for Trust and Safety use cases.
Bring your own policy:
Interprets your written policy, so it generalizes across products and use cases with minimal engineering.
Reasoned decisions, not just scores:
Gain complete access to the model’s reasoning process, facilitating easier debugging and increased trust in policy decisions. Keep in mind Raw CoT is meant for developers and safety practitioners. It’s not intended for exposure to general users or use cases outside of safety contexts.
Configurable reasoning effort:
Easily adjust the reasoning effort (low, medium, high) based on your specific use case and latency needs.
Permissive Apache 2.0 license:
Build freely without copyleft restrictions or patent risk—ideal for experimentation, customization, and commercial deployment.
Inference examples
You can use gpt-oss-safeguard-120b and gpt-oss-safeguard-20b similar to gpt-oss-120b and gpt-oss-20b as described in our
respective cookbooks
. We’ve also provided a detailed
prompting guide
that provides guidelines for how to craft your policy and use it with the models.
gpt-oss-safeguard is a model partner of the
Robust Open Online Safety Tools (ROOST)
Model Community. The ROOST Model Community (RMC) is a group of safety practitioners exploring open source AI models to protect online spaces. As an RMC model partner, OpenAI is committed to incorporating user feedback and jointly iterating on future releases in pursuit of open safety. Visit the
RMC GitHub repo
to learn more about this partnership and how to get involved.
b-model huggingface.co is an AI model on huggingface.co that provides b-model's model effect (), which can be used instantly with this eugene141759 b-model model. huggingface.co supports a free trial of the b-model model, and also provides paid use of the b-model. Support call b-model model through api, including Node.js, Python, http.
b-model huggingface.co is an online trial and call api platform, which integrates b-model's modeling effects, including api services, and provides a free online trial of b-model, you can try b-model online for free by clicking the link below.
eugene141759 b-model online free url in huggingface.co:
b-model is an open source model from GitHub that offers a free installation service, and any user can find b-model on GitHub to install. At the same time, huggingface.co provides the effect of b-model install, users can directly use b-model installed effect in huggingface.co for debugging and trial. It also supports api for free installation.