o3-mini
Zero-eval
#1MATH
#1IFEval
#1LiveBench
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by OpenAI
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About
o3-mini is a language model developed by OpenAI. The model shows competitive results across 26 benchmarks. It excels particularly in COLLIE (98.7%), MATH (97.9%), IFEval (93.9%). It supports a 300K token context window for handling large documents. The model is available through 2 API providers. Released in 2025, it represents OpenAI's latest advancement in AI technology.
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Pricing Range
Input (per 1M)$1.10 -$1.10
Output (per 1M)$4.40 -$4.40
Providers2
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Timeline
AnnouncedJan 30, 2025
ReleasedJan 30, 2025
Knowledge CutoffSep 30, 2023
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License & Family
License
Proprietary
Performance Overview
Performance metrics and category breakdown
Overall Performance
26 benchmarks
Average Score
56.9%
Best Score
98.7%
High Performers (80%+)
8Performance Metrics
Max Context Window
300.0KAvg Throughput
115.0 tok/sAvg Latency
5ms+
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All Benchmark Results for o3-mini
Complete list of benchmark scores with detailed information
| COLLIE | text | 0.99 | 98.7% | Self-reported | |
| MATH | text | 0.98 | 97.9% | Self-reported | |
| IFEval | text | 0.94 | 93.9% | Self-reported | |
| MGSM | text | 0.92 | 92.0% | Self-reported | |
| AIME 2024 | text | 0.87 | 87.3% | Self-reported | |
| MMLU | text | 0.87 | 86.9% | Self-reported | |
| LiveBench | text | 0.85 | 84.6% | Self-reported | |
| Multilingual MMLU | text | 0.81 | 80.7% | Self-reported | |
| Multi-IF | text | 0.80 | 79.5% | Self-reported | |
| GPQA | text | 0.77 | 77.2% | Self-reported |
Showing 1 to 10 of 26 benchmarks