Google’s latest AI image generator, nano banana pro, marks a significant leap forward in the capabilities of generative AI, combining the advanced understanding of its Gemini 3 model with the vast informational resources of Google Search. Early tests of this new tool suggest that Google may have even undersold what it can do. While the original nano banana model was popular and showcased impressive features, nano banana pro takes things to a new level — especially in how it handles complex text rendering within images, a persistent challenge for AI image generation tools.
One of the standout improvements in nano banana pro is its ability to generate clear, legible text in images, including complex infographics and captions, without the usual nonsensical or “hallucinated” text artifacts that have plagued AI-generated visuals in the past. This is a game changer in the AI image generation space because it opens up possibilities for creating informative visuals that can actually convey accurate information, rather than just looking visually interesting but being textually meaningless. The quality of these infographics is striking: clean, well-organized, and effective in breaking down complicated topics into digestible visuals.
Nano banana pro’s text generation prowess reflects its integration with Google Search’s extensive database. By tapping into real-time online content, the AI can pull accurate information to include in infographics, making them not only visually appealing but also factually grounded. Users can even specify their own sources by providing links, which the model will use to construct the infographic. For instance, when tested with a detailed article on Hollywood’s ongoing power struggle with AI, nano banana pro was able to create a visually compelling summary that captured the major themes and even included requested logos and source attributions. This level of control and accuracy in image-based information presentation is something rarely seen in earlier AI image tools.
However, the power of nano banana pro is not without its risks. The model’s ability to accurately reproduce realistic images of celebrities and public figures poses ethical and legal challenges. During testing, attempts to generate images using celebrity names like “KJ Apa” (known for his role as Archie in the TV show Riverdale) and direct references to “Riverdale” were initially blocked, as expected. Yet, by simply removing explicit names from the prompt, the AI produced disturbingly accurate images that resembled the actor and the scene. While it sometimes failed to capture a celebrity’s likeness perfectly—such as with Reese Witherspoon in a “Legally Blonde” style scene—it successfully recreated two distinct versions of Dr. Seuss’s The Grinch, both the Jim Carrey live-action portrayal and the animated character voiced by Benedict Cumberbatch.
These results highlight a growing concern among celebrities and public figures about AI’s ability to fabricate realistic images of them without consent. Despite AI companies’ claims of technical safeguards and policies aimed at preventing misuse, the reality is that these protections can be circumvented. As AI models like nano banana pro become more sophisticated, distinguishing between real and AI-generated content becomes increasingly difficult, raising serious questions about misinformation, privacy, and the potential for abuse.
Another area where nano banana pro shines is in its handling of text embedded within images, such as store signs, T-shirt logos, and other objects where legible text is crucial. Historically, AI image generators have struggled with this, often producing garbled or nonsensical text that served as a telltale sign of artificial origin. Nano banana pro, however, nearly eliminates these errors, creating crisp, readable text that blends seamlessly into images. This advancement, while impressive, also complicates efforts to detect AI-generated content based on textual anomalies.
The improved text generation is not limited to decorative or incidental text but extends to more substantive content like infographics. Previous AI models, including OpenAI’s early image generator, showed promise in this area but still struggled with accuracy and coherence. For example, ChatGPT’s attempts to generate infographics about the water cycle included typos and even invented stages, undermining their educational value. Nano banana pro, by contrast, produces infographics with minimal errors and a high degree of factual correctness, making it a valuable tool for visual communication and education.
The integration of Gemini 3’s capabilities with Google Search enables nano banana pro to create detailed, informative visuals on a wide range of topics. The AI can summarize complex subjects into easy-to-understand infographics, making it a powerful assistant for journalists, educators, marketers, and anyone needing quick, high-quality visual content. The ability to customize sources