Graphic-Design-Bench: A Comprehensive Benchmark for Evaluating AI on Graphic Design Tasks

• URL: http://arxiv.org/abs/2604.04192v2
• Date: Tue, 07 Apr 2026 16:58:37 GMT
• Title: Graphic-Design-Bench: A Comprehensive Benchmark for Evaluating AI on Graphic Design Tasks
• Abstract summary: GraphicDesignBench (GDB) is the first comprehensive benchmark suite designed specifically to evaluate AI models on the full breadth of professional graphic design tasks.<n>The suite comprises 50 tasks organized along five axes: layout, typography, infographics, template & design semantics and animation.<n>We evaluate a set of frontier closed-source models using a standardized metric taxonomy covering spatial accuracy, perceptual quality, text fidelity, semantic alignment, and structural validity.
• Score: 7.841779848822317
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We introduce GraphicDesignBench (GDB), the first comprehensive benchmark suite designed specifically to evaluate AI models on the full breadth of professional graphic design tasks. Unlike existing benchmarks that focus on natural-image understanding or generic text-to-image synthesis, GDB targets the unique challenges of professional design work: translating communicative intent into structured layouts, rendering typographically faithful text, manipulating layered compositions, producing valid vector graphics, and reasoning about animation. The suite comprises 50 tasks organized along five axes: layout, typography, infographics, template & design semantics and animation, each evaluated under both understanding and generation settings, and grounded in real-world design templates drawn from the LICA layered-composition dataset. We evaluate a set of frontier closed-source models using a standardized metric taxonomy covering spatial accuracy, perceptual quality, text fidelity, semantic alignment, and structural validity. Our results reveal that current models fall short on the core challenges of professional design: spatial reasoning over complex layouts, faithful vector code generation, fine-grained typographic perception, and temporal decomposition of animations remain largely unsolved. While high-level semantic understanding is within reach, the gap widens sharply as tasks demand precision, structure, and compositional awareness. GDB provides a rigorous, reproducible testbed for tracking progress toward AI systems that can function as capable design collaborators. The full evaluation framework is publicly available.

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