gpt-oss-safeguard is a first open weight reasoning model specifically trained for safety classification tasks to help classify text content based on customizable policies. As a fine-tuned version of gpt-oss, gpt-oss-safeguard is designed to follow explicit written policies that you provide. This enables bring-your-own-policy Trust & Safety AI, where your own taxonomy, definitions, and thresholds guide classification decisions. Well crafted policies unlock gpt-oss-safeguard's reasoning capabilities, enabling it to handle nuanced content, explain borderline decisions, and adapt to contextual factors.
Added Feb 23, 2026
Context Window
128.0K
Max Output
16.4K
Input Price (Auto)
$0.075/1M
Output Price (Auto)
$0.30/1M
Capabilities
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
24.5
Auto routing is available for this model. Explicit provider selection is not available.
Loading provider options…
Coding Index
18.5
GPQA Diamond
Graduate-level scientific reasoning
68.8%
Better than 60% of models compared
HLE
Humanity's Last Exam
9.8%
Better than 72% of models compared
IFBench
Instruction-following benchmark
65.1%
Better than 83% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
60.2%
Better than 65% of models compared
AA-LCR
Long context reasoning evaluation
30.7%
Better than 49% of models compared
SciCode
Python programming for scientific computing
34.4%
Better than 62% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
10.6%
Better than 51% of models compared
AIME 2025
American Invitational Mathematics Examination 2025
89.3%
Better than 88% of models compared
MMLU-Pro
Professional and academic subject knowledge
74.8%
Better than 48% of models compared
Last updated May 15, 2026
Artificial AnalysisLiveCodeBench
Contamination-free coding benchmark
77.7%
Better than 89% of models compared
