DiT block (diffusion transformer)
A transformer block operating on image-latent tokens, modulated by the diffusion timestep.
Introduced inDec 2022Scalable Diffusion Models with Transformers
Diffusion transformers replace the classic U-Net with a stack of transformer blocks over patchified latent tokens. Each block is conditioned on the timestep (and prompt) through adaptive layer-norm modulation. The timestep embedding shifts and scales activations inside every block. DiTs scale more predictably than U-Nets and power most recent image and video generators.
Adoption over time
Share of new models that have included DiT blocks over time.
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Comfy-Org/MiniMax-H3↓ 17.3M · ♡ 2kOpen in visualizer
coqui/XTTS-v2text-to-speech · ↓ 8.4M · ♡ 4kOpen in visualizer
MiniMaxAI/MiniMax-H3image-text-to-video · ↓ 4.0M · ♡ 4kOpen in visualizer
Comfy-Org/Krea-2↓ 2.2M · ♡ 465Open in visualizer
ResembleAI/chatterboxtext-to-speech · ↓ 2.0M · ♡ 2kOpen in visualizer
stabilityai/stable-diffusion-xl-base-1.0text-to-image · ↓ 1.6M · ♡ 8kOpen in visualizer
Lightricks/LTX-2.3image-to-video · ↓ 1.6M · ♡ 2kOpen in visualizer
stable-diffusion-v1-5/stable-diffusion-v1-5text-to-image · ↓ 1.4M · ♡ 1kOpen in visualizer
stabilityai/sdxl-turbotext-to-image · ↓ 1.1M · ♡ 3kOpen in visualizer
Qwen/Qwen2.5-Omni-3Bany-to-any · ↓ 1.0M · ♡ 346Open in visualizer
Tongyi-MAI/Z-Image-Turbotext-to-image · ↓ 794k · ♡ 5kOpen in visualizer
Lightricks/LTX-2.5image-to-video · ↓ 790k · ♡ 2kOpen in visualizer
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