🥇 UniGenBench Leaderboard (English Long)
📚 UniGenBench is a unified benchmark for T2I generation that integrates diverse prompt themes with a comprehensive suite of fine-grained evaluation criteria.
🔧 You can use the official GitHub repo to evaluate your model on UniGenBench.
😊 We release all generated images from the T2I models evaluated in our UniGenBench on UniGenBench-Eval-Images. Feel free to use any evaluation model that is convenient and suitable for you to assess and compare the performance of your models.
📝 To add your own model to the leaderboard, please send an Email to Yibin Wang, then we will help with the evaluation and updating the leaderboard.
2025-12 | ✗ | 95.41 | 99.58 | 98.98 | 90.15 | 91.46 | 97.20 | 93.41 | 95.19 | 97.25 | 95.39 | 95.98 | 99.15 | 92.90 | 92.33 | 93.99 | 95.29 | 91.71 | 92.51 | 92.46 | 95.79 | 96.11 | 94.16 | 99.71 | 93.15 | 96.45 | 97.54 | 93.98 | 94.84 | 95.16 | 95.24 | 94.18 | 96.70 | 96.71 | 96.69 |