If outputs don't align with your prompt, first increase prompt specificity. Add details about composition (foreground/background), lighting direction (backlit, side-lit), color palette (warm tones, cool blues), and style keywords (photorealistic, cinematic, 8k resolution). Avoid vague terms like 'beautiful' or 'nice'—use concrete descriptors instead. Second, check that your image_size setting matches your intended composition; portrait prompts work better with portrait ratios. Third, try adjusting the seed value or running multiple generations with num_images set to 3-4 to explore variations. If results remain inconsistent, the model may struggle with highly abstract or complex multi-object scenes. In such cases, break your concept into simpler prompts or try
WAN 2.7 Pro, which excels at compositional accuracy for complex scenes.