Efficient-Large-Model / SANA1.5_1.6B_1024px

huggingface.co
Total runs: 152
24-hour runs: -2
7-day runs: -3
30-day runs: -863
Model's Last Updated: July 31 2026
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Introduction of SANA1.5_1.6B_1024px

Model Details of SANA1.5_1.6B_1024px

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🐱 Sana Model Card

Model

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We introduce SANA-1.5 ,an efficient model with scaling of training-time and inference time techniques. SANA-1.5 delivers: efficient model growth from 1.6B Sana-1.0 model to 4.8B, achieving similar or better performance than training from scratch and saving 60% training cost; efficient model depth pruning , slimming any model size as you want; powerful VLM selection based inference scaling , smaller model+inference scaling > larger model; Top-notch GenEval & DPGBench results. Detailed results are shown in the below table.

model growth performance on GenEval 8-bit optimizer

Source code is available at https://github.com/NVlabs/Sana .

Model Description
Model Sources

For research purposes, we recommend our generative-models Github repository ( https://github.com/NVlabs/Sana ), which is more suitable for both training and inference and for which most advanced diffusion sampler like Flow-DPM-Solver is integrated. MIT Han-Lab provides free Sana inference.

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Developing

Uses
Direct Use

The model is intended for research purposes only. Possible research areas and tasks include

  • Generation of artworks and use in design and other artistic processes.

  • Applications in educational or creative tools.

  • Research on generative models.

  • Safe deployment of models which have the potential to generate harmful content.

  • Probing and understanding the limitations and biases of generative models.

Excluded uses are described below.

Out-of-Scope Use

The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.

Limitations and Bias
Limitations
  • The model does not achieve perfect photorealism
  • The model cannot render complex legible text
  • fingers, .etc in general may not be generated properly.
  • The autoencoding part of the model is lossy.
Bias

While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.

Runs of Efficient-Large-Model SANA1.5_1.6B_1024px on huggingface.co

152
Total runs
-2
24-hour runs
0
3-day runs
-3
7-day runs
-863
30-day runs

More Information About SANA1.5_1.6B_1024px huggingface.co Model

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SANA1.5_1.6B_1024px huggingface.co

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https://huggingface.co/Efficient-Large-Model/SANA1.5_1.6B_1024px

SANA1.5_1.6B_1024px install

SANA1.5_1.6B_1024px is an open source model from GitHub that offers a free installation service, and any user can find SANA1.5_1.6B_1024px on GitHub to install. At the same time, huggingface.co provides the effect of SANA1.5_1.6B_1024px install, users can directly use SANA1.5_1.6B_1024px installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

SANA1.5_1.6B_1024px install url in huggingface.co:

https://huggingface.co/Efficient-Large-Model/SANA1.5_1.6B_1024px

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