Humanity's Sixth Sense: Benchmarking Intuitive Visual Reasoning in Multimodal Models

Multimodal Model: AI systems capable of processing and reasoning across multiple input types like text, images, and video.
Agentic Setup: AI systems designed to take autonomous actions within an environment to achieve goals.

Humans perceive far more in a scene than what is explicitly depicted: a single glance captures past causes and future trajectories; a quick peek determines if a vehicle can fit between two parked cars; a few seconds of video reveals who holds authority in a room.

Existing visual benchmarks, however, target either deliberate expert-level analysis or low-level perception, leaving the intuitive reasoning that people perform largely untested. To bridge this gap, we introduce Humanity’s Sixth Sense (HSS), a benchmark for intuitive visual reasoning.

Humanity’s Sixth Sense (HSS) spans diverse image and video inputs, organizes items under a structured taxonomy, and pairs each with human-written prompts probing the implicit temporal, spatial, social, and abstract structure that people infer at a glance.

Frontier MLLMs fall short of human performance: participants reach 93.1% accuracy, while the strongest model, GPT-6-astra, reaches only 53.6% even at maximum reasoning effort. Despite excelling in many complex tasks that require advanced perception and knowledge, current models still struggle significantly on these visual tasks that are intuitive for humans.

We further explore agentic setup that apply dynamic visual manipulation to HSS, which narrows but does not close the gap. HSS establishes intuitive visual reasoning as a measurable axis and directs attention to a capability that scaling on current benchmarks has so far left behind.