ViGoR-Bench: How Far Are Visual Generative Models
From Zero-Shot Visual Reasoners?

Beneath the stunning visual fidelity of modern AIGC models lies a ‘logical desert’, where systems fail tasks that require physical, causal, or complex spatial reasoning. Current evaluations largely rely on superficial metrics or fragmented benchmarks, creating a ‘performance mirage’ that overlooks the generative process. To address this, we introduce ViGoR (Vision-Generative Reasoning-centric Benchmark), a unified framework designed to dismantle this mirage. ViGoR distinguishes itself through four key innovations: 1) holistic cross-modal coverage bridging Image-to-Image and Video tasks; 2) a dual-track mechanism evaluating both intermediate processes and final results; 3) an evidence-grounded automated judge ensuring high human alignment; and 4) granular diagnostic analysis that decomposes performance into fine-grained cognitive dimensions. Experiments on over 20 leading models reveal that even state-of-the-art systems harbor significant reasoning deficits, establishing ViGoR as a critical ‘stress test’ for the next generation of intelligent vision models.