GPT-4.1 mini
Multimodal
Zero-eval
#2CharXiv-D
#2OpenAI-MRCR: 2 needle 1M
#2Graphwalks BFS >128k
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by OpenAI
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About
GPT-4.1 mini is a multimodal language model developed by OpenAI. The model shows competitive results across 29 benchmarks. It excels particularly in CharXiv-D (88.4%), MMLU (87.5%), IFEval (84.1%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.
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Pricing Range
Input (per 1M)$0.40 -$0.40
Output (per 1M)$1.60 -$1.60
Providers2
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Timeline
AnnouncedApr 14, 2025
ReleasedApr 14, 2025
Knowledge CutoffMay 31, 2024
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Specifications
Capabilities
Multimodal
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License & Family
License
Proprietary
Performance Overview
Performance metrics and category breakdown
Overall Performance
29 benchmarks
Average Score
49.6%
Best Score
88.4%
High Performers (80%+)
3Performance Metrics
Max Context Window
1.1MAvg Throughput
150.0 tok/sAvg Latency
5ms+
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All Benchmark Results for GPT-4.1 mini
Complete list of benchmark scores with detailed information
| CharXiv-D | multimodal | 0.88 | 88.4% | Self-reported | |
| MMLU | text | 0.88 | 87.5% | Self-reported | |
| IFEval | text | 0.84 | 84.1% | Self-reported | |
| MMMLU | text | 0.79 | 78.5% | Self-reported | |
| MathVista | multimodal | 0.73 | 73.1% | Self-reported | |
| MMMU | multimodal | 0.73 | 72.7% | Self-reported | |
| Multi-IF | text | 0.67 | 67.0% | Self-reported | |
| GPQA | text | 0.65 | 65.0% | Self-reported | |
| Graphwalks BFS <128k | text | 0.62 | 61.7% | Self-reported | |
| Graphwalks parents <128k | text | 0.60 | 60.5% | Self-reported |
Showing 1 to 10 of 29 benchmarks