Fixing Misaligned Text Overlays in Nano Banana 2 Product Mockups

When generating product mockups with Nano Banana 2, users may encounter a specific visual artifact where text labels appear distorted, warped, or completely misplaced on the surface of the product. Instead of crisp, legible copy sitting naturally on a bottle or box, the generated image might show gibberish characters, stretched letters that do not follow the object's perspective, or text floating in an illogical position relative to the item. This issue is particularly common when the prompt attempts to describe complex packaging details alongside the product itself.

It is crucial to distinguish between a tool limitation and a user error. The symptom described here involves the AI failing to render specific typographic elements as requested. While the goal is often to have a realistic mockup with perfect branding, the current behavior indicates that the model struggles to maintain strict identity preservation for text within the generation process. This does not necessarily mean the entire image is flawed; rather, the specific instruction regarding the text content has been interpreted loosely by the underlying engine.

Separating Plausible Causes from Known Facts

To effectively troubleshoot this issue, we must separate what is likely happening based on user intuition from what is technically confirmed about the system. A common assumption is that the AI simply needs a better image of the product to place the text correctly. However, verified information clarifies that the core issue lies in the fundamental design of the prompt instructions.

Known Facts:

• Prompt instructions describe desired outcomes but do not guarantee the preservation of identity, labels, objects, or typography.
• Nano Banana 2 supports text-to-image and image-to-image workflows, yet these workflows do not inherently secure text fidelity.
• The tool is designed to generate images based on descriptions, not to act as a precise graphic design editor for existing text layers.

Plausible (but unverified) Assumptions to Avoid:

• Assuming that increasing the resolution will fix the text distortion.
• Believing that using a different model version like Nano Banana 2 Lite will improve typography accuracy, especially since it is focused on speed and cost rather than multi-turn editing or complex reference inputs.
• Expecting the tool to perfectly replicate specific brand fonts or logos without external post-processing.

Understanding that the tool prioritizes visual coherence over literal text transcription helps set realistic expectations. The misalignment is often a result of the model attempting to blend the concept of "text" into the texture of the product surface, leading to warping or illegibility.

Diagnosing and Fixing Prompt Specificity

The primary diagnostic step for misaligned text overlays is to analyze the prompt structure. Since the system does not guarantee typography preservation, the most effective workaround is to adjust the specificity of the request. Instead of demanding exact text placement, users should focus on describing the presence of a label or the general aesthetic of the packaging.

For example, rather than prompting "Generate a coffee bag with the words 'Premium Roast' written clearly in white font on the front," try a description that focuses on the visual element: "A premium coffee bag with a minimalist white label area on the front, featuring abstract geometric patterns." This approach guides the AI to create a space for text without forcing it to render characters it cannot reliably control.

If you require actual readable text, the most reliable method is to generate the mockup without specific text instructions and add the typography later using standard graphic design software. This separates the image generation phase from the layout phase, ensuring the final output looks professional. Users can explore the prompt library for examples of how to describe product surfaces effectively, taking inspiration from those structures while avoiding rigid text constraints.

Verifying Results and Next Steps

After adjusting your prompts to be less prescriptive about specific text characters, regenerate the image to verify the outcome. You should observe a cleaner integration of the product surface, even if the text itself is now abstract or placeholder-like. If the text still appears distorted, it confirms the limitation that the tool does not guarantee typography preservation.

In such cases, the workflow shifts from generation to post-production. Generate the base product mockup with high fidelity to the shape and lighting, then overlay your actual text using external tools. This ensures that your branding remains sharp and aligned regardless of the AI's internal rendering capabilities.

For more advanced features or alternative models that might suit different needs, you can visit the Try Nano Banana page to explore the full range of available tools. Remember that while Nano Banana 2 is powerful for creating realistic product visuals, treating it as a generative art tool rather than a typesetting engine will yield the best results for your mockup projects.