ByteDance
We propose a diffusion distillation method that achieves new state-of-the-art in one-step/few-step 1024px text-to-image generation based on SDXL. Our method combines progressive and adversarial distillation to achieve a balance between quality and mode coverage.
Running this yourself: can likely run on your own machine.
We propose a diffusion distillation method that achieves new state-of-the-art in one-step/few-step 1024px text-to-image generation based on SDXL.
Live access is not confirmed for this model. No current purchase price is advertised.
No current subscription pricing is tracked for this model.
Confirm this specific model, usage limits, and billing terms with the provider. A subscription does not automatically include API credits.
No login needed to compare. Prices are in USD; provider charges are separate from AI Market Cap plans. Context length, caching, tools, taxes, and regional terms can change the final cost. Open weights do not mean free hosting.
---
Quality Score
---
Arena ELO
Unknown
Parameters
---
Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
12 of 22 public signals
Sign in to join the discussion
95.1K
Downloads
2.2K
Likes
Feb 2024
Released
3/5 signals
0/4 signals
3/5 signals
3/4 signals
3/4 signals
Parameters
—
Training compute
Not reported
Dataset scale
Not reported
Base model
Stable Diffusion XL (SDXL)
Source-reported access: Open weights (restricted use) · Unknown confidence
Gaps we are still tracking