prunaai/z-image 🔢📝❓ → 🖼️
About
An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer
Example Output
Prompt:
"A hyper-realistic, close-up portrait of a tribal elder from the Omo Valley, painted with intricate white chalk patterns and adorned with a headdress made of dried flowers, seed pods, and rusted bottle caps. The focus is razor-sharp on the texture of the skin, showing every pore, wrinkle, and scar that tells a story of survival. The background is a blurred, smoky hut interior, with the warm glow of a cooking fire reflecting in the subject's dark, soulful eyes. Shot on a Leica M6 with Kodak Portra 400 film grain aesthetic."
Output
Performance Metrics
11.26s
Prediction Time
11.27s
Total Time
All Input Parameters
{
"width": 1024,
"height": 1024,
"prompt": "A hyper-realistic, close-up portrait of a tribal elder from the Omo Valley, painted with intricate white chalk patterns and adorned with a headdress made of dried flowers, seed pods, and rusted bottle caps. The focus is razor-sharp on the texture of the skin, showing every pore, wrinkle, and scar that tells a story of survival. The background is a blurred, smoky hut interior, with the warm glow of a cooking fire reflecting in the subject's dark, soulful eyes. Shot on a Leica M6 with Kodak Portra 400 film grain aesthetic.",
"output_format": "jpg",
"guidance_scale": 3,
"output_quality": 90,
"negative_prompt": "",
"num_inference_steps": 28
}
Input Parameters
- seed
- Random seed. Set for reproducible generation
- width
- Width of the generated image
- height
- Height of the generated image
- prompt (required)
- Text prompt for image generation
- output_format
- Format of the output images
- guidance_scale
- Guidance scale for classifier-free guidance. Recommended range: 3.0-5.0
- output_quality
- Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
- negative_prompt
- Negative prompt to specify what you don't want in the image
- num_inference_steps
- Number of inference steps. Recommended range: 28-50
Output Schema
Output
Example Execution Logs
Using seed: 308608975 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:10, 2.52it/s] 7%|▋ | 2/28 [00:00<00:08, 3.22it/s] 11%|█ | 3/28 [00:01<00:08, 2.86it/s] 14%|█▍ | 4/28 [00:01<00:08, 2.72it/s] 18%|█▊ | 5/28 [00:01<00:08, 2.64it/s] 21%|██▏ | 6/28 [00:02<00:08, 2.60it/s] 25%|██▌ | 7/28 [00:02<00:08, 2.57it/s] 29%|██▊ | 8/28 [00:03<00:07, 2.56it/s] 32%|███▏ | 9/28 [00:03<00:07, 2.55it/s] 36%|███▌ | 10/28 [00:03<00:07, 2.54it/s] 39%|███▉ | 11/28 [00:04<00:06, 2.54it/s] 43%|████▎ | 12/28 [00:04<00:06, 2.53it/s] 46%|████▋ | 13/28 [00:05<00:05, 2.53it/s] 50%|█████ | 14/28 [00:05<00:05, 2.53it/s] 54%|█████▎ | 15/28 [00:05<00:05, 2.53it/s] 57%|█████▋ | 16/28 [00:06<00:04, 2.53it/s] 61%|██████ | 17/28 [00:06<00:04, 2.52it/s] 64%|██████▍ | 18/28 [00:06<00:03, 2.53it/s] 68%|██████▊ | 19/28 [00:07<00:03, 2.53it/s] 71%|███████▏ | 20/28 [00:07<00:03, 2.53it/s] 75%|███████▌ | 21/28 [00:08<00:02, 2.53it/s] 79%|███████▊ | 22/28 [00:08<00:02, 2.53it/s] 82%|████████▏ | 23/28 [00:08<00:01, 2.52it/s] 86%|████████▌ | 24/28 [00:09<00:01, 2.53it/s] 89%|████████▉ | 25/28 [00:09<00:01, 2.53it/s] 93%|█████████▎| 26/28 [00:10<00:00, 2.53it/s] 96%|█████████▋| 27/28 [00:10<00:00, 2.52it/s] 100%|██████████| 28/28 [00:10<00:00, 2.52it/s] 100%|██████████| 28/28 [00:10<00:00, 2.56it/s]
Version Details
- Version ID
eb865cc448032613678cd0e4e99548671cdff1286bc04f0f605b3fc10fffe3aa- Version Created
- January 27, 2026