Mastering Nano Banana 2 Prompt Structure for Architectural Floor Plans

Creating accurate architectural representations requires more than just describing a room; it demands strict adherence to viewing angles and spatial logic. When using Nano Banana 2, the goal is often to transform rough hand-drawn sketches into clean, professional top-down views. The primary challenge lies in avoiding perspective distortions that turn a flat layout into a three-dimensional isometric or oblique view. To achieve true orthographic projection, your prompt must explicitly define the camera angle as strictly perpendicular to the ground plane.

The core use case here involves taking a conceptual sketch—perhaps a few lines indicating walls and furniture—and refining it into a usable drafting document. This workflow relies on specific terminology to guide the AI away from artistic interpretation and toward technical accuracy. By focusing on keywords like "orthographic," "top-down," and "plan view," you signal the model to ignore depth cues that create vanishing points. This ensures the resulting image maintains consistent scale and proportion, which is critical for anyone looking to visualize spatial layouts without the confusion of perspective lines.

Essential Terminology for Orthographic Views

To prevent the AI from generating a 3D rendering, you must anchor your prompt with rigid directional constraints. The most effective approach is to combine visual descriptors with technical drafting terms. Instead of saying "draw a house," specify "generate a top-down architectural floor plan." You should explicitly state that the view is "flat" and "two-dimensional." Including phrases such as "no perspective distortion" or "zero-degree elevation" helps the model understand that depth is not required.

Furthermore, defining the line weight and style can significantly improve the output's utility. If you need a blueprint-style result, request "thin black lines on a white background" or "technical drawing style." This directs the AI to prioritize clarity over texture or lighting effects. It is important to remember that prompt instructions describe desired outcomes but do not guarantee identity or object preservation. Therefore, if your sketch contains specific labels, they may be reinterpreted by the AI unless you are using an image-to-image workflow where the input sketch is heavily weighted. For text-to-image generation, rely on clear descriptions of the layout rather than expecting exact replication of handwritten notes.

Five Distinct Prompt Strategies for Different Drafting Needs

Below are five materially different usable prompt examples tailored for various stages of architectural planning. These are labeled as examples to demonstrate potential structures. Adjustments should be made based on the complexity of the initial sketch and the desired level of detail.

1. The Minimalist Skeleton

Use Case: Best for converting very rough, abstract scribbles into a clean, basic wall layout without furniture. Prompt Example: "Generate a top-down architectural floor plan from a rough sketch. Show only thin black walls on a white background. No furniture, no shading, no perspective. Strictly orthographic view." Adjustment: If the walls appear too thick, add "hairline width" to the description. If the AI adds color, reinforce "monochrome" and "black and white."

2. The Furnished Residential Layout

Use Case: Ideal for visualizing how furniture fits within a defined space after the walls are established. Prompt Example: "Create a detailed top-down floor plan showing a living room and kitchen. Include simple geometric shapes for sofas, tables, and appliances. Maintain a flat 2D view with no shadows. Use a technical drawing style with clear boundaries." Adjustment: Specify the arrangement if the AI places items randomly, e.g., "sofa against the north wall." Note that specific object placement is not guaranteed.

3. Commercial Office Grid

Use Case: Suitable for generating repetitive office spaces with cubicles or workstations. Prompt Example: "Produce a top-down floor plan of an open-plan office. Arrange rows of desks and chairs in a grid pattern. Ensure all elements are aligned perfectly. Use a blueprint aesthetic with blue lines on white. No perspective distortion." Adjustment: If the grid looks irregular, emphasize "perfect alignment" and "symmetrical layout." Avoid complex textures that might break the grid pattern.

4. The Multi-Room Apartment

Use Case: Designed for larger projects requiring distinct zones like bedrooms, bathrooms, and hallways. Prompt Example: "Draw a complete apartment floor plan with three bedrooms, one bathroom, and a hallway. Use dashed lines for interior partitions and solid lines for exterior walls. View is strictly from above. No 3D effects." Adjustment: Clarify door swings if necessary, though the AI may simplify this. Request "clear separation between rooms" to avoid merged spaces.

5. The Renovation Overlay

Use Case: Useful when starting with an existing sketch and wanting to propose new structural changes. Prompt Example: "Transform this sketch into a modernized floor plan. Remove old walls and replace them with glass partitions. Keep the original footprint but update the interior layout. Flat top-down view with high contrast." Adjustment: Be aware that the AI may alter the original footprint. Use "preserve original dimensions" if maintaining the exact size is critical, though results vary.

Model Selection and Workflow Considerations

When executing these prompts, selecting the right model variant is crucial for balancing speed and quality. Google documents Nano Banana 2 as Gemini 3.1 Flash Image, while Nano Banana Pro corresponds to Gemini 3 Pro Image. For architectural drafting, the higher fidelity of the Pro model may yield better line consistency, whereas Nano Banana 2 Lite (Gemini 3.1 Flash Lite) is focused on speed and cost. It is important to note that Nano Banana 2 Lite is not optimized for multiple reference inputs or multi-turn sequential editing. Do not recommend it for complex workflows requiring iterative refinement of a floor plan without explaining this limitation.

Always verify the output against your design intent. Since prompt instructions do not guarantee typography preservation or exact label retention, you may need to add text annotations manually after generation. For those ready to experiment with these structures, Try Nano Banana to access the generator and test these prompt variations directly.

By mastering the language of orthographic projection and understanding the capabilities of each model tier, you can effectively leverage Nano Banana 2 to streamline the early stages of architectural drafting.