TIIF-Bench (Text-to-Image Instruction Following Benchmark) is a benchmark introduced to systematically evaluate how well text-to-image (T2I) models interpret and follow detailed user instructions. The full TIIF-Bench (paper arXiv:2506.02161) organizes prompts across multiple concept pools and six compositional prompt dimensions (including new dedicated dimensions for text rendering and style control), provides concise and extended prompt variants, and proposes fine-grained evaluation metrics for alignment between textual instructions and generated images. The authors also publish the images generated by evaluated (proprietary) models on the Hugging Face Hub as A113NW3I/TIIF-Bench-Data. "TIIF-Bench mini" refers to the compact/specialized subset used by the authors for (faster) text-to-image instruction-following evaluation in their experiments (the full benchmark and released HF dataset are linked below).
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