Mastering Text Replacement in Nano Banana 2: A Prompt Structure Guide

Replacing text within an existing image is a common request for designers, marketers, and content creators who need to update labels, signs, or captions without recreating the entire scene. Nano Banana 2 offers an image-to-image workflow designed to handle these edits. However, achieving a seamless result where the new copy matches the original font style, weight, and lighting conditions requires a precise approach. It is important to note that typography preservation is not guaranteed by default; the AI interprets your instructions based on the visual context provided.

This guide outlines a practical method for constructing prompts that maximize your chances of success when swapping text. We will focus on the structural elements of your input rather than relying on vague descriptions. By following these steps, you can better control the output of the tool, which operates under the Gemini 3.1 Flash Image model architecture.

Understanding the Core Prompt Structure

The foundation of any successful edit in Nano Banana lies in how you describe the relationship between the old text and the new text. Unlike simple text-to-image generation, image-to-image editing relies heavily on the prompt's ability to distinguish between what should remain static (the background, lighting, texture) and what must change (the specific characters).

When drafting your instruction, avoid generic phrases like "change the text." Instead, be explicit about the action. A robust structure typically follows this pattern: identify the target area, specify the removal of the old content, and define the insertion of the new content with stylistic constraints. For example, you might state, "Replace the word 'Sale' with 'New Arrival' using the same bold sans-serif font and shadow effect." This level of detail helps the model understand that the goal is replication of style, not just placement of letters.

Remember that prompt instructions describe desired outcomes but do not guarantee identity, label, object, or typography preservation. The AI may interpret "same font" differently depending on the complexity of the original image. Therefore, it is best to treat your prompt as a strong suggestion rather than a command that forces the pixel-perfect alignment of every glyph.

Step-by-Step Workflow for Text Swapping

To execute a text replacement effectively, follow this numbered sequence to prepare your inputs and generate the result.

1. Upload Your Source Image: Begin by selecting the image containing the text you wish to modify. Ensure the image is clear and the text is legible, as the model needs visual cues to determine the correct font characteristics.
2. Select the Image-to-Image Mode: Navigate to the appropriate editor interface within Nano Banana 2. This mode allows the system to use your uploaded image as a reference for composition and lighting while applying changes based on your text prompt.
3. Construct Your Specific Prompt: Write a detailed instruction that explicitly names the old text and the new text. Include descriptors for the font style (e.g., "serif," "handwritten," "blocky") and environmental factors (e.g., "curved surface," "metallic sheen," "soft shadow").
4. Generate and Review: Submit the prompt and review the generated variations. Since the model does not guarantee perfect typography, you may need to iterate several times to find a version where the new text blends naturally with the scene.
5. Refine if Necessary: If the first attempt fails to match the lighting or font weight, adjust your prompt to be more descriptive about those specific attributes rather than changing the core text.

Evaluating Results and Troubleshooting Common Issues

Judging the quality of the output requires a critical eye. Look specifically at the edges of the new letters to see if they blend into the background or if they appear pasted on top. Check the curvature of the text; if the original sign was curved, the new text should follow that arc. Lighting consistency is another key factor; shadows cast by the letters should match the direction and intensity of light in the rest of the image.

If the text appears distorted or the wrong font style is used, consider the following fixes:

• Clarify the Font Description: If the model chose a serif font when you wanted sans-serif, add more specific adjectives to your prompt, such as "clean lines" or "no decorative feet."
• Adjust Contrast: Sometimes the new text clashes with the background brightness. Explicitly mention "high contrast" or "subtle blending" in your instructions.
• Simplify the Request: If the image contains multiple elements, the model might get confused. Try focusing the prompt solely on the text region, describing the surrounding area only as necessary for context.

It is crucial to remember that untested prompt examples are just examples. While the structure above provides a logical framework, results vary based on the complexity of the source image. Do not expect the tool to perform perfectly on every single attempt, especially with complex backgrounds or unusual lighting angles.

For users looking to explore different capabilities, you can Try Nano Banana to access the full range of image editing features. Whether you are updating a product label or correcting a typo in a photograph, mastering the art of the prompt is the key to unlocking the potential of this AI tool.

By understanding the limitations and leveraging a structured approach, you can significantly improve the likelihood of achieving a professional-looking text replacement. Always verify the final output against your design requirements before considering the task complete.