Custom Gems and Consistent Character Generation (Nano Banana)

Enhancing Character Consistency in AI-Generated Imagery: Addressing Challenges with Custom Gems

Creating a set of consistent character images using AI tools can be an exciting yet complex process. Many users aim to establish a reliable method to generate multiple images featuring the same character across various scenes, increasing the coherence and professionalism of their visual projects. However, practical experiences often reveal unexpected hurdles.

A common approach involves leveraging custom Gems—specialized AI configurations or settings—by uploading a reference image of the character into the Knowledge section. The idea is to craft instructive guidelines and trigger words to ensure the AI recognizes and replicates the character faithfully across multiple prompts.

Initial attempts might include uploading a clear, high-quality image of the character, with the intention of prompting the AI to generate scenes featuring this character in different contexts. For example, a user might request: “Create an image referencing [filename].jpg and depict a photorealistic portrait of the character in a park, sitting on a bench, reading a magazine.” In some cases, this initial request produces the desired result.

However, complications often arise. The reference image may be automatically converted to a lower quality JPG format, regardless of the original file extension, potentially impacting recognition fidelity. Furthermore, subsequent prompts—even with identical syntax and instructions—may produce entirely different characters, undermining the goal of consistency.

This behavior typically stems from the limitations of current AI image generation models and their handling of reference images within custom configurations. AI systems may rely heavily on the initial prompt context, and once the session progresses, the reference image’s influence diminishes or resets. The process does not inherently retain persistent character identity across multiple prompts unless explicitly designed to do so.

Potential Solutions and Best Practices:

1. Use of External Linking or Embedding: Instead of re-uploading images repeatedly, consider hosting reference images externally and embedding them via links, if supported by the platform.

2. Prompt Engineering: Develop highly detailed prompts that include descriptive attributes of the character, such as physical features, clothing, and signature traits, to reinforce identity.

3. Consistent Session Management: Keep all prompt interactions within a single session to maintain context and reference continuity. Some platforms may support persistent memory or character profiles, so explore their settings.

4. Iterative Refinement: Generate multiple images and select those that most accurately reflect the character. Use these as further references or training data for future prompts.

5. Custom Model Training: For advanced users, fine