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Efficient-Large-Model / SANA-Video_2B_720p
Model's Last Updated: July 31 2026
text-to-video
Introduction of SANA-Video_2B_720p
Model Details of SANA-Video_2B_720p
🐱 SANA-Video Model Card
SANA-Video is a small, ultra-efficient diffusion model designed for rapid generation of high-quality, minute-long videos at resolutions up to 720×1280.
Key innovations and efficiency drivers include:
(1) Linear DiT : Leverages linear attention as the core operation, offering significantly more efficiency than vanilla attention when processing the massive number of tokens required for video generation.
(2) Constant-Memory KV Cache for Block Linear Attention : Implements a block-wise autoregressive approach that uses the cumulative properties of linear attention to maintain global context at a fixed memory cost, eliminating the traditional KV cache bottleneck and enabling efficient, minute-long video synthesis.
SANA-Video achieves exceptional efficiency and cost savings: its training cost is only 1% of MovieGen's ( 12 days on 64 H100 GPUs ). Compared to modern state-of-the-art small diffusion models (e.g., Wan 2.1 and SkyReel-V2), SANA-Video maintains competitive performance while being 16× faster in measured latency. SANA-Video is deployable on RTX 5090 GPUs, accelerating the inference speed for a 5-second 720p video from 71s down to 29s (2.4× speedup), setting a new standard for low-cost, high-quality video generation.
Source code is available at https://github.com/NVlabs/Sana .
🐱 How to Inference
Refer to: https://github.com/NVlabs/Sana/blob/main/asset/docs/sana_video.md#1-inference-with-txt-file
diffusers pipeline
refer to: https://huggingface.co/Efficient-Large-Model/SANA-Video_2B_720p_diffusers
Model Description
- Developed by: NVIDIA, Sana
- Model type: Efficient Video Generation with Block Linear Diffusion Transformer
- Model size: 2B parameters
- Model precision: torch.bfloat16 (BF16)
- Model resolution: This model is developed to generate 720p resolution 81(5s) frames videos with multi-scale heigh and width.
- Model Description: This is a model that can be used to generate and modify videos based on text prompts. It is a Linear Diffusion Transformer that uses LTX2-vae one 32x32x8 spatial-temporal-compressed latent feature encoder ( LTX2 ).
- Resources for more information: Check out our GitHub Repository and the SANA-Video report on arXiv .
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
- Repository: https://github.com/NVlabs/Sana
- Guidance: https://github.com/NVlabs/Sana/asset/docs/sana_video.md
License/Terms of Use
GOVERNING TERMS: This trial service is governed by the NVIDIA API Trial Terms of Service . Use of this model is governed by the NVIDIA Open Model License Agreement .
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 video generation models are impressive, they can also reinforce or exacerbate social biases.
Runs of Efficient-Large-Model SANA-Video_2B_720p on huggingface.co
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More Information About SANA-Video_2B_720p huggingface.co Model
Url of SANA-Video_2B_720p
SANA-Video_2B_720p huggingface.co Url
Provider of SANA-Video_2B_720p huggingface.co
Other API from Efficient-Large-Model
Updated:December 13 2024
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