Nano Banana Pro
91 comments
·November 20, 2025throwacct
arecsu
Agree. I can't keep up with it, it's hard to grasp my head around them, where to go to actually use them, etc
theoldgreybeard
The interesting tidbit here is SynthID. While a good first step, it doesn't solve the problem of AI generated content NOT having any kind of watermark. So we can prove that something WITH the ID is AI generated but we can't prove that something without one ISN'T AI generated.
Like it would be nice if all photo and video generated by the big players would have some kind of standardized identifier on them - but now you're left with the bajillion other "grey market" models that won't give a damn about that.
slashdev
If there was a standardized identifier, there would be software dedicated to just removing it.
I don't see how it would defeat the cat and mouse game.
aqme28
I don't think it will be easy to just remove it. It's built into the image and thus won't be the same every time.
Plus, any service good at reverse-image search (like Google) can basically apply that to determine whether they generated it.
There will always be a way to defeat anything, but I don't see why this won't work for like 90% of cases.
VWWHFSfQ
There will be a model trained to remove synthids from graphics generated by other models
paulryanrogers
It doesn't have to be perfect to be helpful.
For example, it's trivial to post an advertisement without disclosure. Yet it's illegal, so large players mostly comply and harm is less likely on the whole.
baby
It solves some problems! For example, if you want to run a camgirl website based on AI models and want to also prove that you're not exploiting real people
echelon
Your use case doesn't even make sense. What customers are clamoring for that feature? If the law cares, the law has tools to inquire.
All of this is trivially easy to circumvent ceremony.
Google is doing this to deflect litigation. They'll do this (1) as long as they're the market leader, (2) as long as there aren't dozens of other similar products - especially ones available as open source, (3) as long as the public is still freaked out / new to the idea anyone can make images and video of whatever, and (4) as long as the signing compute doesn't eat into the bottom line once everyone in the world has uniform access to the tech.
{Law enforcement, lawyers, journalists} find a deep fake {illegal, porn, libelous, controversial} image and goes to Google to ask who made it. That only works for so long, if at all. Once everyone can do this and the lookup hit rates (or even inquiries) are < 0.01%, it'll go away.
We're just in the awkward phase where everyone is freaking out that you can make images of Trump wearing a bikini or Tim Cook saying he hates Apple and loves Samsung. In ten years, this will be normal for everyone.
echelon
This watermarking ceremony is useless.
We will always have local models. Eventually the Chinese will release a Nano Banana equivalent as open source.
staplers
have some kind of standardized identifier on them
theoldgreybeard
yeah, personally identifying undetectable watermarks are kindof a terrifying prospect
morkalork
Labelling open source models as "grey market" is a heck of a presumption
theoldgreybeard
It's why I used "scare quotes".
markdog12
I asked Gemini "dymamic view" how SynthID works: https://gemini.google.com/share/62fb0eb38e6b
evrenesat
I've tried to repaint the exterior of my house. More than 20 times with very detailed prompts. I even tried to optimize it with Claude. No matter what, every time it added one, two or three extra windows to the same wall.
fumeux_fume
I also tried that in the past with poor results. I just tried it this morning with nano banana pro and it nailed it with a very short prompt: "Repaint the house white with black trim. Do not paint over brick."
cj
I tried this in AI studio just now with nano banana.
Results: https://imgur.com/a/xFMkx68
The white house was the original (random photo from Google). The prompt was "What paint color would look nice? Paint the house."
vunderba
Guess they ran out of paint - notice the upper window.
jasonjmcghee
Maybe I'm an obscure case, but I'm just not sure what I'd use an image generation model for.
For people that use them (regularly or not), what do you use them for?
volkk
SynthID seems interesting but in classic Google fashion, I haven't a clue on how to use it and the only button that exists is join a waitlist. Apparently it's been out since 2023? Also, does SynthID work only within gemini ecosystem? If so, is this the beginning of a slew of these products with no one standard way? i.e "Have you run that image through tool1, tool2, tool3, and tool4 before deciding this image is legit?"
edit: apparently people have been able to remove these watermarks with a high success rate so already this feels like a DOA product
meetpateltech
Developer Blog: https://blog.google/technology/developers/gemini-3-pro-image...
DeepMind Page: https://deepmind.google/models/gemini-image/pro/
Model Card: https://storage.googleapis.com/deepmind-media/Model-Cards/Ge...
SynthID in Gemini: https://blog.google/technology/ai/ai-image-verification-gemi...
scottlamb
The rollout doesn't seem to have reached my userid yet. How successful are people at getting these things to actually produce useful images? I was trying recently with the (non-Pro) Nano Banana to see what the fuss was about. As a test case, I tried to get it to make a diagram of a zipper merge (in driving), using numbered arrows to indicate what the first, second, third, etc. cars should do.
I had trouble reliably getting it to...
* produce just two lanes of traffic
* have all the cars facing the same way—sometimes even within one lane they'd be facing in opposite directions.
* contain the construction within the blocked-off area. I think similarly it wouldn't understand which side was supposed to be blocked off. It'd also put the lane closure sign in lanes that were supposed to be open.
* have the cars be in proportion to the lane and road instead of two side-by-side within a lane.
* have the arrows go in the correct direction instead of veering into the shoulder or U-turning back into oncoming traffic
* use each number once, much less on the correct car
This is consistent with my understanding of how LLMs work, but I don't understand how you can "visualize real-time information like weather or sports" accurately with these failings.
Below is one of the prompts I tried to go from scratch to an image. I did have a bit better luck introducing one element at a time, starting from a simple image, and then adding to it. But on the other hand, when I did that it wouldn't do as well at keeping space for things. And sometimes it just didn't make any changes to the image at all.
The prompt:
You are an illustrator for a drivers' education handbook. You are an expert on US road signage and traffic laws. We need to prepare a diagram of a "zipper merge". It should clearly show what drivers are expected to do, without distracting elements.
First, draw two lanes representing a single direction of travel from the bottom to the top of the image (not an entire two-way road), with a dotted white line dividing them. Make sure there's enough space for the several car-lengths approaching a construction site. Include only the illustration; no title or legend.
Add the construction in the right lane only near the top (far side). It should have the correct signage for lane closure and merging to the left as drivers approach a demolished section. The left lane should be clear. The sign should be in the closed lane or right shoulder.
Add cars in the unclosed sections of the road. Each car should be almost as wide as its lane.
Add numbered arrows #1–#5 indicating the next cars to pass to the left of the "lane closed" sign. They should be in the direction the cars will move: from the bottom of the illustration to the top. One car should proceed straight in the left lane, then one should merge from the right to the left (indicate this with a curved arrow), another should proceed straight in the left, another should merge, and so on.
vunderba
I'll be running it through my GenAI Comparison benchmark shortly - but so far it seems to be failing on the same tests that the original Nano Banana struggled with (such as SHRDLU).
fouronnes3
I guess the true endgame of AI products is naming them. We still have quite a way to go.
timenotwasted
We just need a new AI for that.
riskable
Need a name for something? Try our new Mini Skibidi model!
b33j0r
This has always been the hardest problem in computer science besides “Assume a lightweight J2EE distribution…”
awillen
Honestly I give Google credit for realizing that they had something that people were talking about and running with it instead of just calling it gemini-image-large-with-text-pro
echelon
They tried calling it gemini-2.5-whatever, but social media obsessed over the name "Nano Banana", which was just its codename that got teased on Twitter for a few weeks prior to launch.
After launch, Google's public branding for the product was "Gemini" until Google just decided to lean in and fully adopt the vastly more popular "Nano Banana" label.
The public named this product, not Google. Google's internal codename went virally popular and outstaged the official name.
Branding matters for distribution. When you install yourself into the public consciousness with a name, you'd better use the name. It's free distribution. You own human wetware market share for free. You're alive in the minds of the public.
Renaming things every human has brand recognition of, eg. HBO -> Max, is stupid. It doesn't matter if the name sucks. ChatGPT as a name sucks. But everyone in the world knows it.
This will forever be Nano Banana unless they deprecate the product.
dangoodmanUT
I've had nano banana pro for a few weeks now, and it's the most impressive AI model I've ever seen
The inline verification of images following the prompt is awesome, and you can do some _amazing_ stuff with it.
It's probably not as fun anymore though (in the early access program, it doesn't have censoring!)
refulgentis
"Inline verification of images following the prompt is awesome, and you can do some _amazing_ stuff with it." - could you elaborate on this? sounds fascinating but I couldn't grok it via the blog post (like, it this synthid?)
dangoodmanUT
It uses Gemini 3 inline with the reasoning to make sure it followed the instructions before giving you the output image
echelon
LLMs might be a dead end, but we're going to have amazing images, video, and 3D.
To me the AI revolution is making visual media (and music) catch up with the text-based revolution we've had since the dawn of computing.
Computers accelerated typing and text almost immediately, but we've had really crude tools for images, video, and 3D despite graphics and image processing algorithms.
AI really pushes the envelope here.
I think images/media alone could save AI from "the bubble" as these tools enable everyone to make incredible content if you put the work into it.
Everyone now has the ingredients of Pixar and a music production studio in their hands. You just need to learn the tools and put the hours in and you can make chart-topping songs and Hollywood grade VFX. The models won't get you there by themselves, but using them in conjunction with other tools and understanding as to what makes good art - that can and will do it.
Screw ChatGPT, Claude, Gemini, and the rest. This is the exciting part of AI.
dangoodmanUT
I wouldn’t call LLMs a dead end, they’re so useful as-is
Shalomboy
The SynthID check for fishy photos is a step in the right direction, but without tighter integration into everyday tooling its not going to move the needle much. Like when I hold the power button on my Pixel 9, It would be great if it could identify synthetic images on the screen before I think to ask about it. For what its worth it would be great if the power button shortcut on Pixel did a lot more things.
maliker
I wonder how hard it is to remove that SynthID watermark...
Looks like: "When tested on images marked with Google’s SynthID, the technique used in the example images above, Kassis says that UnMarker successfully removed 79 percent of watermarks." From https://spectrum.ieee.org/ai-watermark-remover
mudkipdev
We know what it looks like at least https://www.reddit.com/r/nanobanana/comments/1o1tvbm/nano_ba...
Google needs to pace themselves. AI studio, Antigravity, Banana, Banana Pro, Grape Ultra, Gemini 3, etc. This information overload don't do them any good whatsoever.