The Nano Banana Formula: Locking AI Character Consistency with 5 Prompt Engineering Secrets

 

 

The Consistency Conundrum 🤖 Are you struggling to make your AI-generated character look the same across multiple images? Achieving 100% character consistency in AI art, especially for detailed assets like our 'Nano Banana', requires a structured, formulaic approach. Learn the five crucial steps to lock your character's look permanently.

The rise of generative AI has made creating stunning visuals simple, but making the *same* stunning visual repeatedly is the real challenge. When tasked with generating a series of marketing shots or a story sequence, the "Nano Banana" cannot suddenly change its texture, eye size, or ripeness between frames. This is where Prompt Engineering becomes an exact science. You need a reliable, repeatable formula. This guide breaks down the five core pillars of prompt construction, transforming your inconsistent asset into a 100% reliable AI character ready for any scene. Let's build the perfect formula. 📝

 

1. The Master Character Definition Block 📜

The foundation of consistency is a fixed, hyper-detailed block of text that defines your character. This block must be placed at the beginning of *every single prompt* and should not be changed. It is the character's DNA. Avoid ambiguous terms; use measurable, descriptive language.

Anatomy of the 'Nano Banana' Master Block

For our Nano Banana, we define everything: personality, shape, texture, and style reference. The goal is to leave no room for AI interpretation. We use this block as a template, adding the specific action or scene *after* it:

A cute, anthropomorphic, miniature Nano Banana. Perfect golden yellow peel, slightly matte rubber texture, large expressive chibi-style eyes, wearing a tiny red bow tie, standing exactly 10 centimeters tall, Pixar character animation style, highly detailed.

Key Takeaway: The Master Block should be a single, cohesive unit. Never rearrange the keywords within it, as the AI's weight distribution changes based on keyword order.

 

2. Seed-Locking and the Style Reference ID 🧲

The Seed is the number that governs the initial noise pattern from which the image is generated. Using the same seed for different prompts (within the same generation model) is the most powerful technique for consistency, particularly for the character's pose and camera angle.

Leveraging `—sref` and `—stylize`

Many modern generators also support advanced consistency parameters:

• Style Reference (`—sref` or similar): If you create one *perfect* image, feed its reference code or URL back into the prompt for all subsequent images. This forces the AI to match the visual language (lighting, shading, color palette) of the original render.
• Style Control (`—stylize`): Keep your stylization level constant. Changing this value (e.g., from 500 to 1000) can wildly alter the character's fidelity, making it appear in a completely different aesthetic. Lock it down.

📌 Pro Tip: The Initial Test!
Before starting your project, generate 5-10 images using only the Master Character Definition Block, keeping all other parameters constant. Select the best image's seed and style reference as the foundation for your 100% consistent character.

  

3. Camera Angle and Lens Consistency 📸

Changing the camera perspective can drastically change a character's perceived proportions. The human eye expects a consistent lens profile. If the Nano Banana looks slightly squat in one shot (due to a 24mm wide-angle lens) and then tall in the next (due to an 85mm portrait lens), the character's integrity is broken.

Locking the Optical Look

Append your prompt with a consistent camera and lighting formula. This block ensures the *way* the camera sees the Nano Banana never changes, only *what* the Nano Banana is doing.

Consistency Element	Example Prompt Terms
Lens/Perspective	`shot on 85mm lens, cinematic close-up, high focal length`
Lighting	`studio key light, cinematic rim light, ambient softbox fill`
Depth of Field	`extremely shallow depth of field, f/1.8 aperture`

By including these optics terms, the AI's internal visual engine is forced to render the scene consistently, regardless of the foreground action.

 

4. Weighted Terminology (::) and Negative Space 🚫

Even with a master block, sometimes the AI needs a firm push. Prompt weighting allows you to assign greater importance to your core character terms. Most platforms (like Midjourney or Stable Diffusion) use a system like `::` or parentheses `()` to apply this weight.

Emphasizing the 'Nano Banana'

By assigning a high weight to your key identifier, you ensure the character takes precedence over the scene description. For example:

Example Weighting:
Nano Banana::3.0 sitting on a giant mushroom ::1.0

Simultaneously, use a robust negative prompt (e.g., `--no` or `[Negative Prompt]`) to eliminate common artifacts that hurt consistency, such as:

• `--no deformed, mutated, weird hands, multiple heads, blurry, jpeg artifacts`
• `--no low-res, split composition, oversaturated`

  

5. The Final Upscale and Detail Pass 🖼️

The final step in ensuring 100% consistency is locking down your post-generation processing. Even if the low-resolution images are consistent, an inconsistent upscaler or detail pass can destroy texture consistency.

Uniformity in Detail and Resolution

When preparing a batch of images for a series, ensure all final outputs are processed with the same parameters:

1. Fixed Upscaler: Use the same upscaler (e.g., the same version of ESRGAN, SwinIR, or your platform's native upscaler) for every image. Different upscalers can interpret and redefine small details (like the Nano Banana's eyes or bow tie texture) differently.
2. Consistent Aspect Ratio: Lock the aspect ratio (`—ar 16:9` or `—ar 4:3`) for the entire series. Changing the aspect ratio often forces the AI to recompose the scene, which can subtly alter the character's pose or scale relative to the frame.
3. Noise/Quality Settings: Keep your quality parameters (e.g., `--quality 2` or `—chaos 0`) locked to ensure a uniform level of detail and noise across the entire asset library.

 

The Ultimate Nano Banana Consistency Checklist ✅

Consistency is not a one-time fix; it's a workflow. Follow this checklist to ensure every render of your character is identical.

💡

The 5-Point Character Lock Formula

1. Definition: Create an Unchangeable Master Block with hyper-descriptive terms.

2. Foundation: Lock the visual style using the Original Image's Seed or a Style Reference ID (`—sref`).

3. Optics: Enforce Consistent Camera Terms (e.g., `85mm lens`, `f/1.8`) in every prompt.

4. Control: Use Prompt Weighting (e.g., `::3.0`) to prioritize the character's definition.

5. Post-Process: Use the Same Upscaler and Aspect Ratio for all final outputs.

The secret to consistency is structure, repetition, and locked parameters.

Frequently Asked Questions ❓ (FAQ)

Q: Does changing the prompt order affect consistency?

A: Yes, absolutely. Most AI models place higher importance on terms that appear earlier in the prompt. Even if you use the same words, moving the Master Character Block to the middle can reduce the character's fidelity. Keep it as the first item.

Q: Can I use the same seed on different AI models (e.g., Midjourney and Stable Diffusion)?

A: No. The seed value is model-specific, tied to the particular algorithm and noise pattern of that platform. A seed from Midjourney will not produce the same result in Stable Diffusion, or even in a different version of Midjourney (e.g., v5 vs v6).

Q: If I change the scene, how much can I change the prompt?

A: Only change the scene description, after the Master Character Block. For example: `[Master Block], sitting on a giant red mushroom, cinematic lighting.` Do not change any words in the Master Block itself, and keep the Camera/Lens Block constant at the end.

By treating your prompt not as a wish list, but as a rigid, controlled formula, you unlock the ability to generate perfectly consistent characters for any narrative or marketing campaign. Which character will you be locking down first? Happy prompting! ✨