Nano Banana 2 Troubleshooting: Fixing Distorted Facial Features in Portraits

When generating human portraits with Nano Banana 2, users may occasionally encounter issues where facial features appear misaligned. This symptom often manifests as eyes that are uneven in size or position, mouths that are stretched or blurred, and a general lack of structural coherence in the face. These distortions can make the generated image look unnatural or unsettling. It is important to distinguish this technical artifact from artistic style choices; while some stylization is expected, fundamental geometric errors usually indicate a need for prompt refinement or model selection adjustment.

Separating Plausible Causes from Known Facts

Before attempting a fix, it is helpful to separate what is known about the tool's behavior from plausible but unverified causes. We know that Nano Banana refers to the AI image generation and editing tool, not a skincare brand or physical product. The platform supports both text-to-image and image-to-image workflows, allowing users to generate new content or edit existing images.

A primary factor in facial distortion is the nature of prompt instructions. Prompt instructions describe desired outcomes but do not guarantee identity, label, object, or typography preservation. When a prompt asks for complex combinations of features without clear spatial definitions, the model may struggle to maintain symmetry. Additionally, the underlying model architecture plays a significant role. Google documents Nano Banana 2 as Gemini 3.1 Flash Image (gemini-3.1-flash-image). While powerful, no single model guarantees perfect output in every scenario, especially when dealing with intricate details like facial geometry.

It is also crucial to note the limitations of other versions in the family. Google describes Nano Banana 2 Lite as focused on speed and cost. It is explicitly not optimized for multiple reference inputs or multi-turn sequential editing. Users should not recommend or expect Nano Banana 2 Lite to handle complex portrait corrections as effectively as the standard Nano Banana 2 version. Furthermore, the existence of a website page named Nano Banana Lite does not by itself establish support for Google Nano Banana 2 Lite features; model names and capabilities must not be presented as proof of identical features across all available interfaces.

Diagnosing the Issue Through Prompt Analysis

Diagnosing the root cause often involves analyzing the specificity of the input prompt. If the prompt relies heavily on abstract descriptors like "perfect face" or "beautiful portrait" without defining the arrangement of features, the model may hallucinate structures. To stabilize facial geometry, the prompt needs to provide concrete spatial anchors.

Users should review their prompts for conflicting instructions. For instance, asking for a specific expression while simultaneously requesting a neutral pose can confuse the generator regarding mouth placement. Another common diagnostic step is checking if the user is attempting to use multiple reference images. Since Nano Banana 2 Lite is not optimized for multiple reference inputs, using it for such tasks will likely result in failure or severe distortion. In these cases, switching to the standard Nano Banana 2 model, identified as Gemini 3.1 Flash Image, is necessary.

For those looking to refine their approach, the prompt library offers example prompts that users can copy or take into the generator. These examples serve as a baseline for understanding how to structure requests for better results. However, remember that these are examples and do not guarantee identity or exact replication of any specific person. They are designed to demonstrate effective phrasing rather than to serve as a universal solution for every unique subject.

Practical Fixes and Verification Steps

To fix distorted facial features, start by simplifying the prompt. Focus on clear, direct descriptions of the face's layout. Instead of vague adjectives, specify the relationship between features, such as "eyes aligned horizontally" or "symmetrical jawline." If you are working within an image-to-image workflow, ensure the source image has clear lighting and distinct facial landmarks to guide the generation process.

If the issue persists, consider adjusting the model context. Ensure you are not inadvertently selecting a version optimized for speed over quality, such as Nano Banana 2 Lite, unless speed is the absolute priority and feature accuracy is secondary. For high-quality portrait correction, the standard Nano Banana 2 model is generally more robust. You can explore the Try Nano Banana interface to access the full range of model options and prompt tools.

Finally, verify the results by comparing the generated output against the intended design. Check specifically for eye alignment, mouth shape consistency, and overall facial symmetry. If the features remain distorted, try iterating with slight variations in the prompt wording rather than changing the entire concept. By methodically adjusting the prompt and selecting the appropriate model version, users can significantly reduce the occurrence of facial distortions and achieve more stable, realistic portrait generations.