Fixing Distorted Pump Mechanisms in Nano Banana 2 Image Edits

When performing image-to-image edits with Nano Banana 2, users often encounter a specific type of geometric distortion where the AI generates non-functional or misaligned pump heads on cosmetic bottles. This issue is particularly prevalent during iterative editing workflows where the model attempts to refine details based on previous generations. The resulting images may show pump mechanisms that are fused to the bottle neck, floating above the surface, or possessing impossible mechanical structures. It is crucial to understand that Nano Banana refers to the AI image generation and editing tool itself; it is not a skincare brand, bottle, jar, or physical subject. These artifacts are digital hallucinations rather than reflections of real-world product flaws.

Distinguishing Symptoms from Plausible Causes

To effectively resolve these issues, one must first separate the observable symptoms from the underlying causes. The primary symptom is the visual failure of the pump mechanism to maintain structural integrity. You might see a nozzle that lacks a stem, a cap that merges seamlessly into the plastic body without a hinge, or a spray head that appears to be made of liquid rather than rigid material. These are clear indicators of geometric instability within the generated output.

Plausible causes for this behavior include the complexity of the prompt instructions and the limitations of the specific model version being used. Prompt instructions describe desired outcomes but do not guarantee identity, label, object, or typography preservation. If the prompt is too vague regarding the mechanical nature of the pump, the model may prioritize texture over form. Furthermore, while Google documents Nano Banana 2 as Gemini 3.1 Flash Image, other versions like Nano Banana Pro (Gemini 3 Pro Image) or Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) have distinct capabilities. Specifically, Google describes Nano Banana 2 Lite as focused on speed and cost. It is not optimized for multiple reference inputs or multi-turn sequential editing. Using Nano Banana 2 Lite for complex iterative edits involving detailed mechanical parts can exacerbate distortion because the model lacks the necessary context retention for such tasks.

It is important to note that the website has a Nano Banana 2 product page at /nanobanana2 and supports text-to-image and image-to-image workflows. However, the existence of a page named Nano Banana Lite at /nanobananalite does not by itself establish support for Google Nano Banana 2 Lite features identical to the main tool. Users must rely on verified facts about model capabilities rather than assuming feature parity across all listed pages.

Diagnosing the Workflow and Reference Weight

The diagnosis for distorted pump mechanisms usually points to an imbalance between the reference image strength and the textual guidance provided. In image-to-image mode, the model relies heavily on the input image to determine structure. If the reference weight is set too high, the model may struggle to interpret the fine details of a pump head if the original image was low resolution or ambiguous. Conversely, if the weight is too low, the model ignores the structural constraints entirely, leading to the creation of new, incorrect geometries.

Another diagnostic factor is the use of negative prompts. Without explicit instructions on what not to generate, the AI fills gaps with plausible but incorrect shapes. For example, if the prompt does not explicitly state "no fused parts" or "separate nozzle and cap," the model might default to a merged aesthetic common in abstract art. Additionally, the iterative nature of the edit compounds the error. Each pass introduces slight variations that accumulate, eventually breaking the mechanical logic of the pump. This is why the limitation of Nano Banana 2 Lite regarding multi-turn sequential editing is critical; attempting to fix a pump head over several iterations on the Lite version will likely result in further degradation rather than correction.

Applying Fixes Through Negative Prompts and Adjustments

Resolving these geometric errors requires a targeted approach involving specific negative prompts and careful adjustment of reference weights. Start by refining your prompt to explicitly define the mechanical components. Use phrases that emphasize separation and rigidity, such as "distinct pump head," "clear separation between cap and bottle," and "rigid plastic structure." Simultaneously, employ negative prompts to exclude common failure modes. Add terms like "fused parts," "melting plastic," "floating nozzle," and "non-functional mechanism" to the negative prompt field. These instructions guide the model away from the hallucinated states that cause distortion.

Adjusting the reference weight is equally vital. If you are working with Nano Banana 2 (Gemini 3.1 Flash Image), ensure the weight is balanced to preserve the original bottle shape while allowing the AI to correct the pump details. Avoid setting the weight so high that the model cannot deviate from a flawed original, nor so low that it invents a completely new object. If you find yourself needing to perform multiple rounds of editing to perfect the pump, consider switching to a more capable model if available, as Nano Banana 2 Lite is not optimized for these complex, multi-step workflows.

Finally, verify the results by checking the alignment of the pump against the bottle neck. Ensure the spray direction is logical and the mechanical joints appear functional. While prompt examples describe desired outcomes, they do not guarantee identity or object preservation, so manual verification remains essential. By combining precise negative prompting with appropriate model selection and weight settings, you can significantly reduce the occurrence of distorted pump mechanisms. Try Nano Banana to apply these techniques in your own image-to-image projects and achieve cleaner, more realistic product renders.