Papers › Scalable Diffusion Models with Transformers
Scalable Diffusion Models with Transformers
William Peebles, Saining Xie
We explore a new class of diffusion models based on the transformer architecture. We train latent diffusion models of images, replacing the commonly-used U-Net backbone with a transformer that operates on latent patches. We analyze the scalability of our Diffusion Transformers (DiTs) through the lens of forward pass complexity as measured by Gflops. We find that DiTs with higher Gflops -- through increased transformer depth/width or increased number of input tokens -- consistently have lower FID. In addition to possessing good scalability properties, our largest DiT-XL/2 models outperform all prior diffusion models on the class-conditional ImageNet 512x512 and 256x256 benchmarks, achieving a state-of-the-art FID of 2.27 on the latter.
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Code
Syntology Ran 5 of 20 code samples harvested from 4 repositories linked to this paper; 15 have no recorded run. Of those that ran: 2 ran · honoured contract; 2 ran · our draft was wrong; 1 ran · fixture could not drive it.
By repository: community (archive-listed): 16 samples from 4 repositories, 3 ran; 4 identical to code first harvested elsewhere. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.
13 repositories listed; official and paper-mentioned ones first.
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Code Syntology ran Syntology
20 samples harvested; 5 ran; 2 honoured the contract we drafted; 15 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Image Generation | ImageNet 256x256 | DiT-XL/2 | FID | 2.27 | #54 of 94 | Archive leaderboard | report |
| Image Generation | ImageNet 512x512 | DiT-XL/2 | FID | 3.04 | #41 of 52 | Archive leaderboard | report |
| Image Generation | ImageNet 512x512 | DiT-XL/2 | Inception score | 240.82 | #41 of 52 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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