gpt-4o-mini
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About this model
GPT-4o mini surpasses GPT-3.5 Turbo and other small models on academic benchmarks across both textual intelligence and multimodal reasoning, and supports the same range of languages as GPT-4o. It also demonstrates strong performance in function calling, which can enable developers to build applications that fetch data or take actions with external systems, and improved long-context performance compared to GPT-3.5 Turbo.
Key model capabilities
GPT-4o mini has been evaluated across several key benchmarks.
Reasoning tasks: GPT-4o mini is better than other small models at reasoning tasks involving both text and vision, scoring 82.0% on MMLU, a textual intelligence and reasoning benchmark, as compared to 77.9% for Gemini Flash and 73.8% for Claude Haiku.
Math and coding proficiency: GPT-4o mini excels in mathematical reasoning and coding tasks, outperforming previous small models on the market. On MGSM, measuring math reasoning, GPT-4o mini scored 87.0%, compared to 75.5% for Gemini Flash and 71.7% for Claude Haiku. GPT-4o mini scored 87.2% on HumanEval, which measures coding performance, compared to 71.5% for Gemini Flash and 75.9% for Claude Haiku.
Multimodal reasoning: GPT-4o mini also shows strong performance on MMMU, a multimodal reasoning eval, scoring 59.4% compared to 56.1% for Gemini Flash and 50.2% for Claude Haiku.
| Task | GPT-4o mini Score | Gemini Flash Score | Claude Haiku Score |
|---|---|---|---|
| MMLU (Reasoning Text and Vision) | 82.0% | 77.9% | 73.8% |
| MGSM (Math Reasoning) | 87.0% | 75.5% | 71.7% |
| HumanEval (Coding Performance) | 87.2% | 71.5% | 75.9% |
| MMMU (Multimodal Reasoning) | 59.4% | 56.1% | 50.2% |