Introduction
The generative‑AI world moves fast. Hardly a week goes by without some research lab or software giant releasing a new model capable of conjuring images from a handful of words. Google’s latest entry into this race is Gemini 2.5 Flash Image, better known as Nano Banana.
The oddly cute nickname belies a serious piece of technology. Nano Banana extends Google’s Gemini family by offering a model designed for fast, conversational image generation and editing.
It was built from the ground up to process text and images in a single step, enabling not just basic text‑to‑image generation but also local edits, multi‑image composition and logical reasoning about image content.
I wanted to see how this new tool performs in the real world. So I spent an afternoon running my own mini “nano bana review,” trying four very different prompts on my own photo.
I also compared the results with what other reviewers have said about popular AI image generators like Adobe Firefly, Midjourney and DALL‑E. This post is my candid, first‑person take on Nano Banana.
I’ll explain what it does well, what feels rough around the edges and how it stacks up against the competition. Along the way I’ll sprinkle in tips from Google’s own guidelines for getting the best results.
What Is Nano Banana?
Nano Banana is the playful codename for Gemini 2.5 Flash Image, a state‑of‑the‑art image model built by Google. This variant of the Gemini 2.5 family is designed to support fast, multi‑turn workflows, meaning you can have a back‑and‑forth conversation with the model and refine an image over multiple prompts. The model is offered through the Gemini API, Google AI Studio and Google Cloud’s Vertex AI platform, so developers and end‑users alike can access it.
Key Features
According to the official documentation and developer blog posts, Nano Banana stands out for several reasons:
- Native image generation and editing: The model understands and produces images natively, allowing a smooth workflow for both creating new images and editing existing ones.
- Multi‑image fusion: You can combine multiple input images to create a new scene or transfer style across photos. For example, you could insert a product into a different setting or restyle a room.
- Character and style consistency: The model maintains consistent subjects and styles across prompts and images, which is critical for storytelling and branding.
- Conversational editing: Users can make targeted edits through natural language—blurring a background, removing an object or colorizing a black‑and‑white photo—without complex tools.
- Visual reasoning: Gemini’s deep world knowledge enables the model to interpret diagrams, answer educational queries and follow multi‑step instructions, going beyond simple photorealism.
- SynthID watermarking: Every image generated or edited by the model is embedded with an invisible digital watermark to help identify AI‑generated content.
Google’s developer blog adds another useful detail: the model’s natively multimodal architecture was trained to process text and images in a single, unified step, which unlocks capabilities like conversational editing and multi‑image composition. The same blog post outlines the kinds of tasks it excels at, including text‑to‑image generation, image+text editing, multi‑image composition and iterative refinement.
My Nano Banana Experiment
To put Nano Banana through its paces, I uploaded a straightforward portrait of myself—an ordinary man wearing formal eyeglasses—and wrote four different prompts. My goal was to see how well the model handled object replacement, stylistic additions and complex scene changes. The prompts were:
- “Replace the formal eyeglasses on the subject with sleek aviator goggles, ensuring realistic reflections, proper fit on the face, and seamless blending with the lighting and shadows of the original image, 16:9.”
- “Replace the formal eyeglasses on the subject with beach goggles, ensuring realistic reflections, proper fit on the face, and seamless blending with the lighting and shadows of the original image, 16:9.”
- “Replace the formal eyeglasses on the subject with a colourful birthday cap, ensuring realistic reflections, proper fit on the face, and seamless blending with the lighting and shadows of the original image, 16:9.”
- “This man is sitting proudly on a royal throne, wearing a majestic king’s costume with a velvet robe and golden crown, detailed embroidery, regal palace background, ultra‑realistic, 8K resolution.”
I made sure to follow Google’s advice to “describe the scene” rather than simply listing keywords. As their prompt guide explains, a narrative description yields better results than a list of disconnected words. I also specified the aspect ratio (16:9 or 8K) because image composition matters.
Below is my original Pic. We give all the prompts to be applied on this Pic
Prompt 1: Aviator Goggles
The first prompt asked the model to swap my formal glasses for aviator goggles. Nano Banana nailed the overall viberight away.
“Replace the formal eyeglasses on the subject with sleek aviator goggles, ensuring realistic reflections, proper fit on the face, and seamless blending with the lighting and shadows of the original image, 16:9.”
The aviator goggles were sleek and mirrored, reflecting a faint hint of the environment. They sat at the correct angle on my face, and the straps blended into my hair without any obvious seams. The reflections even matched the lighting of the original photo, producing a believable metallic sheen.
Where the model struggled was in the fine details around the nose bridge and ear. In some iterations, the nose pads looked a little misaligned or slightly blurred. Because Nano Banana currently embeds a SynthID watermark,
I also noticed subtle artifacts when zooming in on the goggles—tiny patterns that reveal the AI origin. Overall, though, this felt like a solid start, and I appreciated that the model kept my facial expression unchanged while swapping accessories.
Prompt 2: Realistic 90‑Year‑Old Transformation
After donning crowns and party hats, I decided to take a trip in the other direction: into the future. My fifth experiment asked Nano Banana to age the subject in my portrait by several decades. The prompt read:
“Transform this person into a realistic 90‑year‑old version. Add natural signs of aging such as deep wrinkles, age spots, sagging skin, and thin white or gray hair. Maintain the same facial features, expression, and overall appearance for recognizability. Keep clothing and background unchanged, focusing only on the natural aging effect.”
I wasn’t sure what to expect—aging a face convincingly is a tall order even for professional retouchers. To my surprise, Nano Banana delivered a remarkably believable elderly version of me. The thin hair turned a dignified silver; deep crow’s‑feet and laugh lines etched across my cheeks and forehead; and the skin tone dulled slightly with subtle age spots. Through all that, my signature features—the shape of my nose, the curve of my smile and even the arch of my eyebrows—remained intact.
You can see the result below:
What impressed me most was how Nano Banana balanced realism with recognizability. It didn’t simply paste stock wrinkles onto my face; the lines followed the natural contours of my features and changed the texture without obscuring my expression. The hairline thinned out gradually, and the color shifted seamlessly from black to gray. Even my formal shirt and background stayed exactly the same, as requested, which heightened the illusion that I’d stepped through a time machine.
Were there flaws? A few. In some versions the wrinkles looked a bit too perfect, almost like a textbook illustration of aging rather than the messy diversity of real life. There were also tiny artifacts around the ears where the skin sagged in unnatural ways. But overall the transformation captured the spirit of a 90‑year‑old me in a way that felt both respectful and slightly unsettling (in a good way). It’s the kind of image you might show at a family gathering to spark laughter and reflection. For educational or storytelling purposes, having access to this “time‑travel” feature opens up all sorts of possibilities.
This fifth experiment reinforced my sense that Nano Banana is capable of more than quick costume changes. Its visual reasoning and style consistency can extend into realistic aging, time‑lapse concepts and other subtle alterations. As always, a bit of prompt tinkering goes a long way, but the core technology shows real promise.
Prompt 3: Colourful Birthday Cap
The third prompt was more whimsical. I asked Nano Banana to replace my glasses with a vibrant birthday hat.
“Replace the formal eyeglasses on the subject with a colourful birthday cap, ensuring realistic reflections, proper fit on the face, and seamless blending with the lighting and shadows of the original image, 16:9.”
The model produced a triangular cap adorned with colourful circles and tiny pom‑poms. It perched neatly on my head without messing up my hairstyle, and the band seamlessly wrapped around my hairline.
The lighting and shadows matched the original photo, making it look as though I had truly donned the party hat.
One surprise was that the hat sometimes partially obscured my forehead and eyebrows, especially when I requested “colourful confetti” patterns.
I found that specifying “keep the face unobstructed” helped. Again, the natural‑language editing allowed me to articulate this preference without resorting to Photoshop‑style masking. The fact that I could instruct the model to adjust the angle and pattern of the hat in plain English underscored how Nano Banana’s conversational editing saves time.
Prompt 4: Majestic Throne Scene
The final prompt was the most ambitious. Rather than swapping accessories, I asked Nano Banana to place me on a royal throne in a palace, wearing a velvet robe and golden crown.
To my amazement, the model generated an ultra‑realistic 8K image that looked like a still from a historical drama.
“This man is sitting proudly on a royal throne, wearing a majestic king’s costume with a velvet robe and golden crown, detailed embroidery, regal palace background, ultra‑realistic, 8K resolution.”
My posture changed slightly to convey a regal demeanor, and the throne’s carved details cast accurate shadows. The robe draped naturally, complete with gold embroidery and soft folds.
The crown sat perfectly centered on my head, and the background glowed with diffused golden light.
This scene showcased Nano Banana’s ability to compose multi‑image elements into a cohesive image. It combined my portrait with a throne, costume and palace environment—demonstrating exactly the kind of style consistency and reasoning Google advertised.
There were still a few imperfections: the embroidery pattern repeated in places, and the crown’s jewels lacked fine resolution. But given that I wrote a single prompt, the result was astonishingly polished.
Lessons From High‑Ranking Reviews of Other AI Tools
To put Nano Banana’s performance into perspective, I read several recent reviews of competing AI image generators. Ryan Law’s Ahrefs article, “I Reviewed the Best AI Image Generators for 2025,” tested Adobe Firefly, Midjourney, DALL‑E 3 (via ChatGPT) and other tools. His findings highlight how the major players compare:
Adobe Firefly
Law praised Adobe Firefly for having “by far the best editing controls” among the tools tested. Firefly lets you change aspect ratios with generative fill, regenerate specific portions of an image (like fixing a missing hand) and upscale low‑quality images to high resolutions. It also allows you to use existing images as style and composition references, which makes it easy to generate a series of images with a cohesive look. Another article on Critical Playground notes that Firefly’s training data comes from Adobe Stock and public‑domain materials, avoiding the controversy around scraping user artwork. Firefly can animate still images, extend shots and apply style presets ranging from anime to claymation.
Midjourney
Midjourney remains beloved for its beautiful aesthetics. Law, a longtime paying customer, remarked that everything it generates is “gorgeous, and more aesthetically pleasing than any other AI model” he tested. The tool excels at fantasy‑style illustration and photorealistic images. However, Midjourney’s editing workflows are still limited. Users can vary an image, upscale it or remove parts of it, but they can’t specify what should replace the removed element. The tool also struggles with data visualizations and consistent style across images.
Wikipedia’s entry on Midjourney provides additional context. The service originally ran through a Discord bot; users issued /imagine commands and received four images, with options to upscale or generate variations.
In August 2024 Midjourney launched a web interface that integrated editing, panning, zooming, region variation and inpainting into a single platform.
Features like Vary (Region) let you select a portion of an image and apply changes only to that area. Other tools include Image Weight for controlling how much influence the original image has on the final result, Style Reference for transferring artistic styles and Character Reference for maintaining consistent character designs across multiple images.
These features hint at Midjourney’s gradual shift toward more professional editing, but they still lag behind Firefly’s precision and Nano Banana’s natural‑language editing.
DALL‑E 3 / ChatGPT
Law’s review is blunt about DALL‑E 3: although it’s accessible through ChatGPT, its images often look obviously AI‑generated and lack polish. Editing tools exist, but they’re unreliable, and maintaining consistent style across multiple outputs is difficult.
The Wikipedia article on DALL‑E adds more context. DALL‑E can generate images in various styles—photorealistic, painterly, emoji and more—and it can “manipulate and rearrange” objects in plausible ways. It even shows strong visual reasoning ability.
Both DALL‑E 2 and DALL‑E 3 support inpainting and outpainting, meaning they can edit or expand an existing image by filling in missing areas consistent with the original. However, the models struggle with complex instructions, accurate text rendering and nuanced language. In short, DALL‑E is versatile but unpredictable.
Other Tools
Firefly, Midjourney and DALL‑E aren’t the only players. Adobe’s post‑production‑focused Firefly Video Model can generate B‑roll, animate stills and extend shots with adjustable camera angles and motion parameters. It also offers composition transfer and style presets.
These features show how generative AI is being woven directly into professional editing tools. For designers who need to maintain control over every pixel, that level of integration might be more appealing than Nano Banana’s chat‑like interface. Meanwhile, open‑source models like Stable Diffusion (not covered in depth here) offer local control but require more technical expertise.
Tips and Best Practices for Nano Banana
Based on my experiments and Google’s official guidance, here are some practical tips for getting good results with Nano Banana:
- Write descriptive prompts. The model performs best when you describe the scene in narrative form rather than listing keywords. Mention camera angles, lighting, mood and aspect ratio to steer the result.
- Specify aspect ratio and resolution. Including “16:9” or “square” helps the model frame the scene correctly. For high‑detail scenes, ask for “8K” or “high resolution.”
- Use iterative refinement. Because the model supports multi‑turn conversations, don’t be afraid to ask for subtle changes. Adjust colors, replace objects or refine composition in follow‑up prompts.
- Leverage style consistency. If you need a series of images with a cohesive look, reuse language from your initial prompt or ask the model to “match the style of the previous image.”
- Watch out for artifacts. Like all AI models, Nano Banana sometimes produces artifacts (e.g., repeating patterns or blurred details). Zoom in and check edges, then regenerate or refine as needed.
Nano Banana vs. the Competition
So how does Nano Banana stack up? Here’s my take after testing the tool and reading other reviews.
Strengths
- Conversational editing. Unlike many image models that require manual masking or parameter tweaking, Nano Banana lets you describe changes in plain English. This lowers the learning curve and speeds up creative iteration.
- Style and character consistency. Keeping a consistent subject across multiple images is notoriously tricky. Nano Banana handles this better than DALL‑E and arguably on par with Midjourney’s character reference system.
- Speed. The “Flash” moniker isn’t just marketing. The model generates and edits images quickly, which is handy when refining details or exploring variations.
- Watermarking. SynthID ensures that images can be identified as AI‑generated. This transparency is important as generative content proliferates.
Weaknesses
- Fine‑detail fidelity. While my aviator goggles looked good from afar, close inspection revealed minor misalignments. This is common across AI models, but Adobe Firefly’s targeted regenerate feature allows more precise corrections.
- Limited editing controls. Nano Banana relies on natural language rather than granular sliders. For designers who want to adjust saturation or mask specific regions, Firefly still offers more control.
- Aspect‑ratio quirks. Occasionally the model ignored my aspect ratio request or cropped awkwardly. Specifying the aspect ratio up front usually solved this, but it’s something to watch.
- Potential for repetition. In complex scenes, patterns or textures sometimes repeat. This stems from the model’s data synthesis and isn’t unique to Nano Banana, but it underscores the need for human oversight.
Final Thoughts
Running my own nano bana review was both entertaining and illuminating. Nano Banana is more than a cute codename—it’s a powerful demonstration of Google’s ability to combine text and images into a single, conversational workflow.
The tool handled simple accessory swaps with ease and even produced a convincing regal portrait. Its strengths lie in speed, style consistency and natural‑language editing, making it ideal for rapid ideation, social media posts or storyboarding.However, Nano Banana isn’t perfect.
It struggles with tiny details and lacks the fine‑grained editing controls that professionals might need. Adobe Firefly still leads in precise image manipulation,
while Midjourney remains the king of aesthetics. DALL‑E is versatile but unpredictable, especially when it comes to consistent output. Each tool serves a different audience: if you need beautiful art quickly, Midjourney or Firefly may fit; if you want conversational edits with reasonable fidelity, Nano Banana is a great option.
What excites me most is how rapidly these models are evolving. Google’s developer blog hints that Gemini’s multimodal architecture will support ever more complex tasks like multi‑image composition and logical reasoning, and the AI industry as a whole is racing to improve editing precision and creative control.
As users, we can benefit by experimenting with multiple tools, understanding their strengths and combining them in our workflows. The future of image creation may involve not just one model but a toolbox of generative assistants tailored to different needs.
If you’re curious about Nano Banana, I encourage you to play with it. Start with descriptive prompts, iterate on your requests and don’t be afraid to compare the results with other tools. You might just find that this “banana” is ripe for your next creative project.
