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DiffusionBench: Towards Unified Evaluation of Generative Diffusion Transformers

·2026.06.24 11:12

Key point

A framework has been released for unified evaluation of Diffusion Transformer model performance, spanning from ImageNet to T2I.

Details

DiffusionBench, a unified evaluation framework for measuring the performance of Generative Diffusion Transformers from multiple angles beyond what ImageNet evaluation alone can offer, has been released.

This project provides the following key features:

  • Unified codebase: Supports various generation tasks such as ImageNet and Text-to-Image (T2I) through a single interface.
  • Staged training support: Provides a reproducible workflow from RAE Tokenizer training (Stage 1) through model training (Stage 2).
  • Support for diverse tasks: Aims to evaluate a wide range of generative models, including not only simple image generation but also text-conditional generation.

Users can install dependencies via the uv package manager and download pretrained models to start experimenting immediately.

open-sourcegenerative-aimodel-evaluationdiffusion-modeldiffusion-transformer
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