Banana != chocolate - having robot issues - need help from fellow humans

I’m using gpt-4.1 to identify food items from photos. My prompt instructs the model to visually identify foods in an image and return ingredient names

The issue: When I send a photo of a white bowl containing pieces of chocolate and blueberries , the model consistently returns “blueberries” (correct) and “banana” (wrong — these are clearly chocolate pieces).

This isn’t random — it’s reproducible across multiple calls. The prompt emphasizes visual inference and says “Only identify food that is CLEARLY VISIBLE in the image.”

A few things I’m wondering:

1. Is this a known issue with gpt-4.1 and dark-colored foods?

2. Would a different model (gpt-4o, etc.) handle this better?

3. Any prompt engineering tips to reduce food identification hallucinations?

4. You get what you pay for?

Thank you for taking a look and any suggestions!