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Plus MMStar RealWorldQA Method, K\mathcal{F}=\{f_{j}\}_{j=1}^{K} includes both closed-source and open-weight MLLMs with heterogeneous architectures, capacities, and cost profiles: • Commercial MLLMs, including GPT-5 series [1], Gemini 2.5 series [25], and Claude models, which offer strong general-purpose multimodal reasoning at higher monetary cost. • Open-weight MLLMs, spanning
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Stop wasting compute: MMR-Bench shows you can beat the best single multimodal LLM's accuracy for 33% of the cost by intelligently routing queries.