If your generated images don't match expectations, start by refining your prompt with more specific details about subject, style, lighting, and composition. Vague prompts like "a cat" yield generic results, while "a tabby cat sitting on a windowsill at sunset, warm golden light, shallow depth of field" guide the model toward a precise vision. Check that your chosen aspect ratio and image size align with your intended use. If results are still inconsistent, try adjusting the prompt enhancement mode—Standard typically handles complex descriptions better than Fast. You can also lock a random seed to isolate prompt changes from generation variance. For persistent issues, compare outputs with
WAN 2.7 Pro Text to Image or
BitDance to see if a different model architecture better suits your creative direction.