Stats
8.2K Downloads
12 stars
Capabilities
Minimum system memory
Tags
Last updated
Updated on October 29byREADME
gpt-oss-safeguard-120b is a safety reasoning model by OpenAI, built-upon their original gpt-oss release. 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.
This 120b variant is designed for production, general purpose, high reasoning use cases that fits into a single H100 GPU (117B parameters with 5.1B active parameters).
This model is released under a permissive Apache 2.0 license and it features configurable reasoning effort—low, medium, or high, so users can balance output quality and latency based on their needs. The model offers full chain-of-thought visibility to support easier debugging and increased trust, though this output is not intended for end users.
This model supports a context length of 131k.
Custom Fields
Special features defined by the model author
Reasoning Effort
: select
(default=low)
Controls how much reasoning the model should perform.
Parameters
Custom configuration options included with this model
Sources
The underlying model files this model uses
Stats
8.2K Downloads
12 stars
Capabilities
Minimum system memory
Tags
Last updated
Updated on October 29byREADME
gpt-oss-safeguard-120b is a safety reasoning model by OpenAI, built-upon their original gpt-oss release. 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.
This 120b variant is designed for production, general purpose, high reasoning use cases that fits into a single H100 GPU (117B parameters with 5.1B active parameters).
This model is released under a permissive Apache 2.0 license and it features configurable reasoning effort—low, medium, or high, so users can balance output quality and latency based on their needs. The model offers full chain-of-thought visibility to support easier debugging and increased trust, though this output is not intended for end users.
This model supports a context length of 131k.
Custom Fields
Special features defined by the model author
Reasoning Effort
: select
(default=low)
Controls how much reasoning the model should perform.
Parameters
Custom configuration options included with this model
Sources
The underlying model files this model uses