Nano Banana 2 Prompt Engineering for Realistic Lighting and Shadow Integration

Creating images where a subject feels truly part of an environment requires more than just placing objects together; it demands a sophisticated understanding of how light behaves. In the context of Nano Banana, which refers to the AI image generation and editing tool, achieving this realism is often the difference between a composite that looks artificial and one that passes as a photograph. The challenge lies in prompt engineering for realistic lighting and shadow integration. When users attempt to blend generated subjects into new backgrounds, inconsistencies in light direction, color temperature, and shadow softness immediately break the illusion.

This guide focuses on specific prompt structures designed to improve these elements within Nano Banana 2. By refining your instructions, you can guide the model to calculate how light interacts with surfaces, ensuring that shadows fall correctly and highlights match the ambient environment. Whether you are working with text-to-image workflows or image-to-image edits, the precision of your language dictates the physical plausibility of the result.

Understanding the Use Case: Blending Subjects Naturally

The primary use case for advanced lighting prompts is environmental integration. Imagine you have generated a portrait of a person but need them to appear standing in a dimly lit alleyway at night, or perhaps sitting on a sun-drenched park bench. Without specific guidance, the AI might place the subject under neutral studio lighting, ignoring the harsh overhead streetlamp or the warm glow of the setting sun.

In these scenarios, the goal is to make the subject and the background share a single light source. This involves defining the direction (e.g., "low angle," "overhead"), the quality (e.g., "soft diffused," "hard direct"), and the color temperature (e.g., "cool blue moonlight," "warm golden hour") of the illumination. Furthermore, shadow integration is critical. A subject must cast a shadow that matches the geometry of the ground plane and the intensity of the light source. If the light comes from the left, the shadow must extend to the right, and its darkness should correspond to the opacity of the light source.

It is important to note that while Nano Banana offers powerful capabilities, prompt instructions describe desired outcomes and do not guarantee identity, label, object, or typography preservation. Users must understand that the model interprets these lighting cues probabilistically. Additionally, if you are using Nano Banana 2 Lite, be aware that it is focused on speed and cost and is not optimized for multiple reference inputs or multi-turn sequential editing. For complex lighting tasks requiring high fidelity, standard Nano Banana 2 or Pro models may yield better results.

Five Materially Different Prompts for Lighting Control

To help you achieve these goals, here are five distinct prompt examples. These are labeled as examples to illustrate how different structures address specific lighting challenges. Each prompt targets a unique scenario, demonstrating how to adjust variables for different environments.

Example 1: Hard Direct Sunlight with Sharp Shadows

Prompt: "A modern ceramic vase on a concrete patio, illuminated by harsh midday sun coming from the top-left corner. Cast a sharp, high-contrast black shadow directly beneath the vase extending to the bottom-right. The light creates bright specular highlights on the glossy rim of the vase." When it helps: This structure is ideal for outdoor scenes where the sun is unobstructed. It forces the model to create hard edges in shadows and intense highlights, mimicking the physics of direct sunlight. Adjustment: Change the angle (top-left) and surface material (concrete vs. grass) to alter shadow softness and length.

Example 2: Soft Diffused Overcast Light

Prompt: "A wooden chair in a foggy forest clearing, lit by soft, even overcast daylight. No distinct shadows are visible; instead, use subtle ambient occlusion to define the contact points between the chair legs and the mossy ground. The lighting should be cool-toned and flat, eliminating harsh gradients." When it helps: Useful for moody, atmospheric shots where the lack of a strong directional light source is key. It prevents the AI from inventing non-existent sun rays. Adjustment: Modify the tone (cool vs. warm) and the surface texture to change how the diffuse light scatters.

Example 3: Artificial Neon Signage at Night

Prompt: "A street food cart at night, illuminated primarily by a flickering pink neon sign hanging above. The light casts a magenta rim light on the left side of the cart and reflects off wet pavement below. Deep, soft shadows fill the areas not hit by the neon glow." When it helps: Essential for urban night photography styles. It teaches the model to handle colored light sources and their specific reflection properties on wet surfaces. Adjustment: Swap the color (pink to blue) and the surface reflectivity (wet pavement to dry asphalt) to see how the light interacts differently.

Example 4: Warm Golden Hour Interior

Prompt: "An interior living room scene during sunset. Warm orange sunlight streams through a large window on the right, creating long, soft shadows stretching across the floorboards. Dust motes are visible in the light beams. The subject is bathed in a warm, low-angle glow with gentle falloff." When it helps: Perfect for lifestyle imagery requiring emotional warmth. It combines directional light with volumetric effects (dust motes) to enhance realism. Adjustment: Adjust the time of day (sunset to sunrise) to shift the color temperature and shadow length.

Example 5: High-Key Studio Lighting

Prompt: "A product shot of a glass bottle against a white cyclorama background. Use high-key studio lighting with softboxes positioned front-left and front-right to eliminate almost all shadows. The lighting should be bright, clean, and evenly distributed, with only faint catchlights in the glass." When it helps: Best for e-commerce or product design where the goal is clarity and minimal distraction. It instructs the model to suppress shadows entirely. Adjustment: Introduce a single key light to create a more dramatic look by removing the fill lights.

Optimizing Your Workflow for Better Results

While these prompts provide a strong foundation, successful integration often requires iteration. Start with a base prompt describing the scene and the lighting conditions, then refine based on the output. If the shadows are too dark, specify "softer shadows" or "lower contrast." If the light color clashes with the background, explicitly state the color temperature.

Remember that Nano Banana 2 supports both text-to-image and image-to-image workflows. In image-to-image mode, you can upload a reference image with the correct lighting and use a prompt like "match the lighting and shadow direction of the reference image exactly" to transfer those attributes to a new subject. However, always verify the output, as the model does not guarantee perfect preservation of specific details.

For those looking to explore further capabilities, including potential upgrades for more complex editing needs, you can visit the Try Nano Banana page to access the generator tools directly. By treating lighting as a core component of your prompt rather than an afterthought, you can significantly elevate the realism of your generated content.

Note: Google documents Nano Banana 2 as Gemini 3.1 Flash Image (gemini-3.1-flash-image). While this documentation provides context on the underlying technology, specific feature availability on this website should be verified on the product pages.