Nano Banana Pro: A Launch-Day Image Generation Review

In November 2025, shortly after Google introduced Nano Banana Pro, I tested its image generation and found the results striking. These examples are a first impression, not a controlled benchmark or a statement about current products and prices.

My first prompt asked for William Hogarth’s The Rake’s Progress reimagined in 2025. The resulting sequence translated the rise and fall of the original into modern details such as crypto speculation, gig work and an eviction notice.

Compared with examples from the original Nano Banana and Seedream 4, I thought the new model produced a more coherent interpretation. These are selected examples and the comparison is subjective.

A second comparison asks for a London topographic map made from felt and yarn. I prefer the Pro image’s visual treatment, while acknowledging that getting real-world geography right is a separate problem.

The model can use search grounding for some requests. In one example it incorporated a real match score and date, although the surrounding London scene was not perfectly accurate. Search access does not make every generated detail reliable.

I test a double-exposure movie poster using three supplied characters. The image combines their worlds and places the characters in a shared action scene; I compare it with outputs from earlier models.

Quality comes with tradeoffs. At the time of this review, the Pro model cost more than the original Nano Banana and took longer in my tests; the exact price ratios I cite were specific to November 2025.

I also describe failures: repeated attempts to create an exciting thumbnail with the desired lettering fell short, and some prompts involving people were refused. These are experiences from my particular prompts, not universal failure rates.

I mention Google’s SynthID watermark checking in the Gemini app. A watermark check concerns the watermark it detects; it should not be treated as proof that every unmarked image is human-made.

An infographic about the Black Death is visually detailed and largely convincing in my test, but I find a claim that Paris was spared that appears wrong. An attractive infographic still needs its facts, labels and sources checked before publication.

The more polished an image looks, the easier it may be to overlook a small factual mistake. I argue that apparent quality can make verification more important, not less.

For scene composition, I supply a hedgehog and a photograph and ask the model to place the animal in the scene with realistic lighting and a person nearby. The result is close to my intended arrangement, though not perfect.

A four-panel comic uses a supplied character and a turtle, with dialogue and recurring visual traits. A follow-up prompt moves the pair to a ship while trying to preserve their personalities and voices.

Some details change between panels, including accessories. Even so, I see value in combining readable text, visual consistency and a coherent sequence; the example still benefits from human review and editing.

The model also misses a requested count in a nested image: I ask for eight layers of technology shown inside one another, but the result does not clearly contain eight. Complex composition remains a limitation in this test.

I briefly test multiple supplied characters in one image and mention image-generation benchmarks. My overall conclusion is enthusiastic, but the ranking and comparisons reflect a launch-day assessment and selected examples.