How does Grok 3's multimodal understanding benchmark compare to GPT-4o's capabilities

**Grok 3 is noted for its strong performance in multimodal tasks such as image understanding and generation, achieving high scores in benchmarks like MMMU and EgoSchema. It processes both text and images effectively, making it versatile for diverse data formats[1][3][7]. Grok 3's multimodal understanding is enhanced by its sophisticated multi-modal training process, which integrates text, code, and images[3].

**GPT-4o, on the other hand, is recognized for its robust multimodal capabilities, particularly in tasks involving visual understanding and content generation. It leads in benchmarks like MathVista, which measures mathematical reasoning and visual understanding accuracy[4]. GPT-4o is also adept at parsing documents into structured forms, showcasing its ability to handle complex content[6].

In terms of specific benchmarks, Grok 3 achieves a score of 73.2% on MMMU, while GPT-4o scores 69.1% on a similar multimodal matching accuracy metric[1][4]. This suggests that Grok 3 might have a slight edge in certain multimodal tasks, but both models are highly capable in their respective domains. Overall, Grok 3 excels in technical reasoning and STEM tasks, while GPT-4o is strong in general-purpose problem-solving and nuanced content understanding[2][5].