Adding tool access and persistent multimodal memory to vision-language models dramatically improves performance on real-world tasks that require grounded perception and numerical reasoning, while actually reducing computational cost compared to scaling inference alone.
OpenVLHarness is a system that helps multimodal AI models solve complex visual reasoning tasks by combining external tools, persistent memory, and code execution.