StylisticBias introduces a controlled benchmark to evaluate attribute-level social bias in multimodal large language models. It reveals that age and body type dominate identity-level effects, while fashion style and 15 key visual attributes drive most bias, accounting for nearly 80% of variation. The benchmark highlights that model judgments are most sensitive to appearance-related cues, especially in socioeconomic and style-based contexts.