Model reference · open weights
URSA-IBQ512 is an open-weight image model from BAAI. URSA-1.7B-IBQ512 (FP16) weighs 5.4 GB; the smallest configuration that runs it is RTX 3060 12 GB.
Summary of the BAAI/URSA-1.7B-IBQ512 model card, 2026-10-01
What it is
| Released by | BAAI |
|---|---|
| Released | 2026-04-10 |
| Parameters | 2.3B |
| VRAM | 5.4 GB for the weights |
What it runs on
| Card | One image | Memory |
|---|---|---|
| RTX 3060 12 GB | tight | 11.6 GB |
| RTX 4060 Ti 16 GB | fits | 15.4 GB |
| RTX 3090 24 GB | fits | 23.4 GB |
| RTX 4090 24 GB | fits | 23.4 GB |
| RTX 5090 32 GB | fits | 31.0 GB |
| L40S 48 GB | fits | 44.0 GB |
| A100 80 GB | fits | 78.2 GB |
| H100 80 GB | fits | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | fits | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | fits | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
From the model card
Using the 🤗's Diffusers library to run URSA in a simple and efficient manner.
pip install diffusers transformers accelerate imageio[ffmpeg]
pip install git+ssh://git@github.com/baaivision/URSA.git
Running the pipeline:
import torch
from diffnext.pipelines import URSAPipeline
model_id, height, width = "BAAI/URSA-1.7B-IBQ512", 512, 512
model_args = {"torch_dtype": torch.float16, "trust_remote_code": True}
pipe = URSAPipeline.from_pretrained(model_id, **model_args)
pipe = pipe.to(torch.device("cuda"))
prompt = "The bear, calm and still, gazes upward as if lost in contemplation of the cosmos."
negative_prompt = "worst quality, low quality, inconsistent motion, static, still, blurry, jittery, distorted, ugly"
image = pipe(**locals()).frames[0]
image.save("ursa.jpg")
The model is intended for research purposes only. Possible research areas and tasks include
Excluded uses are described below.
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.
Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:
While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.
Running it yourself
Rent a machine by the hour. How to run this model is on its model card.