Fixing Text Overlay Cropping in Nano Banana 2: A Complete Guide

Users frequently encounter a specific visual error when generating images with embedded text using Nano Banana 2. The symptom manifests as words, phrases, or entire lines of typography being sliced off at the very edges of the output frame. This issue is particularly common when working with square or portrait aspect ratios where the available canvas space is limited. Instead of seeing a complete message centered or positioned within the image, the viewer sees fragmented letters or truncated sentences that ruin the intended design.

This problem often confuses users who believe the AI has failed to render the text correctly. However, the underlying cause is rarely a failure of the model itself but rather a limitation in how the generation space is allocated relative to the requested content. When the prompt asks for text without specifying spatial boundaries, the model may prioritize fitting the subject matter into the frame, pushing the typography toward the margins until it hits the edge and gets cropped.

Distinguishing Plausible Causes from Known Facts

It is crucial to separate user assumptions from the verified capabilities of the tool. A common misconception is that the AI automatically adds safe zones or padding around text elements to prevent them from touching the border. There is no evidence to support the claim that Nano Banana 2 inherently guarantees this behavior without explicit instruction.

The known facts regarding the system indicate that prompt instructions describe desired outcomes but do not guarantee identity, label, object, or typography preservation. This means that while you can ask for text, the system does not promise to keep that text fully visible if the composition conflicts with the image boundaries. Furthermore, Google documents Nano Banana 2 as Gemini 3.1 Flash Image. While powerful, this model follows the rules set by the prompt strictly. If the prompt implies a tight composition, the model will likely comply, resulting in the cut-off effect.

Another factor to consider is the distinction between different product tiers. While Nano Banana 2 Lite focuses on speed and cost, it is not optimized for complex multi-turn editing or multiple reference inputs. However, the primary issue of text cropping is generally related to the fundamental prompt engineering required for any version of the image generator, rather than a specific hardware limitation of the Lite version. Users should not assume that switching models will automatically fix layout issues if the core prompt remains unchanged.

Diagnosing the Root Cause Through Prompt Analysis

To diagnose why your text is being cut off, review the phrasing of your input. The root cause is almost always a lack of explicit spatial constraints in the prompt. If you simply request "a logo with the word 'Summer' inside," the model interprets this as a creative task where the text might be placed anywhere, including right up against the edge. Without a directive to leave empty space, the AI fills the frame efficiently, often sacrificing the integrity of the text.

The diagnosis involves checking if your prompt includes keywords related to spacing, margins, or safety buffers. If your prompt lacks terms like "padding," "white space," "margin," or "centered with room," the likelihood of cropping increases significantly. Additionally, the aspect ratio plays a role; portrait images have less horizontal width, making vertical text more prone to side cropping if not carefully managed.

Step-by-Step Fix: Adjusting Prompts for Safe Padding

The most effective solution is to modify your prompt to explicitly request padding around all typography. You must treat the text as an element that needs breathing room. Instead of vague descriptions, use precise language that defines the relationship between the text and the image borders.

For example, change a generic prompt like "Generate an image with the text 'Sale'" to "Generate a square image with the text 'Sale' centered, surrounded by significant white padding on all sides to ensure no text is cut off." By explicitly stating the need for padding, you guide the model to allocate space away from the edges. You can also specify the position more rigidly, such as "keep the text at least 10% away from the top, bottom, left, and right edges."

If you are using the prompt library provided on the website, look for examples that demonstrate successful text placement. Use these as a baseline and adapt them to your specific needs. Remember that prompt instructions describe desired outcomes; they do not guarantee identity or typography preservation, so iterative testing is necessary. Try adding variations of "safe zone" or "margins" to your request. If the text still appears too close to the edge, increase the requested padding in your next attempt.

Verifying Your Solution and Next Steps

After applying the adjusted prompt, generate the image and verify the result. Check the corners and edges of the output to ensure the full text is visible and no characters are missing. If the text is still partially obscured, try increasing the padding request further or simplifying the text length to fit more comfortably within the designated safe zone.

It is important to manage expectations; while these adjustments significantly reduce the risk of cropping, the AI generates images based on probability, so minor variations may occur. For users seeking advanced features or specific workflow optimizations, exploring the Nano Banana Pro page at /nanobananapro might offer additional context, though the core principle of explicit prompting remains universal.

By understanding that the tool requires clear spatial directives, you can consistently produce high-quality images with intact typography. Start refining your prompts today to eliminate cropping errors. Try Nano Banana to experiment with these new phrasing techniques and see the difference in your generated outputs.