Nano Banana can be prompt engineered for nuanced AI image generation

https://minimaxir.com/2025/11/nano-banana-prompts/

by minimaxir • 8 months ago

887 233 8 months ago

minimaxir.com

doctorpangloss• 8 months ago

lots of words

okay, look at imagen 4 ultra:

https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...

In this link, Imagen is instructed to render the verbatim prompt “the result of 4+5”, which shows that text, and not instructed, which renders “4+5=9”

Is Imagen thinking?

Let's compare to gemini 2.5 flash image (nano banana):

look carefully at the system prompt here: https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%...

Gemini is instructed to reply in images first, and if it thinks, to think using the image thinking tags. It cannot seemingly be prompted to show verbatim the result 4+5 without showing the answer 4+5=9. Of course it can show whatever exact text that you want, the question is, does it prompt rewrite (no) or do something else (yes)?

compare to ideogram, with prompt rewriting: https://ideogram.ai/g/GRuZRTY7TmilGUHnks-Mjg/0

without prompt rewriting: https://ideogram.ai/g/yKV3EwULRKOu6LDCsSvZUg/2

We can do the same exercises with Flux Kontext for editing versus Flash-2.5, if you think that editing is somehow unique in this regard.

Is prompt rewriting "thinking"? My point is, this article can't answer that question without dElViNg into the nuances of what multi-modal models really are.

gryfft• 8 months ago

Can you provide screenshots or links that don't require login

PunchTornado• 8 months ago

sorry, but I don't understand you post. those links don't work.

dostick• 8 months ago

Use Google AI Studio to submit requests, and to remove watermark, open browser development tools and right click on request to “watermark_4” image and select to block it. And from next generation there will be no watermark!

billynomates• 8 months ago

That sounds dangerous honestly. Watermarks should be mandatory for AI generated images.

dymk• 8 months ago

How would you enforce that when it’s actually important? Any “bad actor” could just open photoshop and remove it. Or run a delobotimized model which doesn’t watermark.

dieortin• 8 months ago

This only applies to the visible watermark on the corner, which you could crop anyways. If I’m not mistaken, all images generated by Google models have an invisible watermark: https://deepmind.google/models/synthid/

dreis_sw• 8 months ago

So the watermark is being added to the image on the client-side? That's pretty bad

wormpilled• 8 months ago

Can't believe that worked, thanks!

squigz4• 8 months ago

I'm getting annoyed by using "prompt engineered" as a verb. Does this mean I'm finally old and bitter?

(Do we say we software engineered something?)

vpShane• 8 months ago

You're definitely old and bitter, welcome to it.

You CREATED something, and I like to think that creating things that I love and enjoy and that others can love and enjoy makes creating things worth it.

squigz4• 8 months ago

Don't get me wrong, I have nothing against using AI as an expression of creativity :)

officeplant• 8 months ago

Not really since "prompt engineering" can be tossed in the same pile as "vibe coding." Just people coping with not developing the actual skills to produce the desired products.

bongodongobob• 8 months ago

Couldn't care less. I don't need to know how to do literally everything. AI fills in my gaps and I'm a ton more productive.

koakuma-chan• 8 months ago

Try getting a small model to do what you want quickly with high accuracy, high quality, etc, and using few tokens per request. You'll find out that prompt engineering is real and matters.

pavlov• 8 months ago

I think it’s meant to be engineering in the same sense as “social engineering”.

antegamisou• 8 months ago

No it means you can still discern what is BS.

miladyincontrol• 8 months ago

Theres lots these models can do but I despise when people suggest they can do edits with "with only the necessary aspects changed".

No, that simply is not true. If you actually compare the before and after you can see it still regenerates all the details on the "unchanged" aspects. Texture, lighting, sharpness, even scale its all different even if varyingly similar to the original.

Sure they're cute for casual edits but it really pains me people suggesting these things are suitable replacements for actual photo editing. Especially when it comes to people, or details outside their training data theres a lot of nuance that can be lost as it regenerates them no matter how you prompt things.

Even if you

StevenWaterman• 8 months ago

That is true for gpt-image-1 but not nano-banana. They can do masked image changes

minimaxir15• 8 months ago

Nano Banana is different and much better at edits without changing texture/lighting/sharpness/color balance, and I am someone that is extremely picky about it. That's why I add the note that Gemini 2.5 Flash is aware of segmentation masks, and that's my hunch why that's the case.

BoredPositron2• 8 months ago

Nano banana has a really low spatial scaling and doesn't affect details like other models.

miohtama2• 8 months ago

Could you just mask out the area you wish to change in more advanced tools, or is there something in the model itself which would prevent this?

lunarboy• 8 months ago

That's probably where things are headed and there are already products trying this (even photoshop already). Just like how code gen AI tools don't replace the entire file on every prompt iteration.

mkagenius2• 8 months ago

Nano Banana is still bad at rendering text perfectly/without typos as most image generation models.

I figured that if you write the text in Google docs and share the screenshot with banana it will not make any spelling mistake.

So, use something like "can you write my name on this Wimbledon trophy, both images are attached. Use them" will work.

minimaxir15• 8 months ago

Google's example documentation for Nano Banana does demo that pipeline: https://ai.google.dev/gemini-api/docs/image-generation#pytho...

That's on my list of blog-post-worthy things to test, namely text rendering to image in Python directly and passing both input images to the model for compositing.

mkagenius2• 8 months ago

Yeah, close.

But it is still generating it with a prompt

Logo: "A simple, modern logo with the letters 'G' and 'A' in a white circle.

My idea was do to it manually so that there is no probabilities involved.

Though your idea of using python is same.

ml-anon2• 8 months ago

"prompt engineered"...i.e. by typing in what you want to see.

harpiaharpyja• 8 months ago

Not all models can actually do that if your prompt is particular

pksebben3• 8 months ago

Most designers can't, either. Defining a spec is a skill.

It's actually fairly difficult to put to words any specific enough vision such that it becomes understandable outside of your own head. This goes for pretty much anything, too.

darepublic• 8 months ago

"amenable to highly specific and granular instruction"

simonw4• 8 months ago

... and then iterating on that prompt many times, based on your accumulated knowledge of how best to prompt that particular model.

minimaxir15• 8 months ago

Case in point, the final image in this post (the IP bonanza) took 28 iterations of the prompt text to get something maximally interesting, and why that one is very particular about the constraints it invokes, such as specifying "distinct" characters and specifying they are present from "left to right" because the model kept exploiting that ambiguity.

mensetmanusman• 8 months ago

We understand now that we interface with LLMs using natural and unnatural language as the user interface.

This is a very different fuzzy interface compared to programming languages.

There will be techniques better or worse at interfacing.

This is what the term prompt engineering is alluding to since we don’t have the full suite of language to describe this yet.

w_for_wumbo2• 8 months ago

Yes, that is a serious skill. How many of the woes that we see is because people don't know what they want or are unable to describe it in such a way that others understand it. I believe prompt engineer to properly convey how complex communication can be, when interacting with a multitude of perspectives, world views, assumptions, presumptions etc. I believe it works well to counter the over-confidence that people have, from not paying attention to what gaps exist between what is said and what is meant.

CobrastanJorji• 8 months ago

Yes, obviously a role involving complex communication while interacting with a multitude of perspectives, world views, assumptions, presumptions, etc needs to be called "engineer."

That is why I always call technical writers "documentation engineers," why I call diplomats "international engineers," why I call managers "team engineers," and why I call historians "hindsight engineers."

thisOtterBeGood• 8 months ago

It IS a skill. And most often it is disregarded by those who did not yet conquer it ...

jazzyjackson• 8 months ago

Used to be called Google Fu

yieldcrv• 8 months ago

right? 15 months ago in image models you used to have to designate rendering specifications, and know the art of negative prompting

now you can really use natural language and people want to debate you about how poor they are at articulating a shared concepts, amazing

it's like the people are regressing and the AI is improving

pfortuny• 8 months ago

Well, I just asked it for a 13-sided irregular polygon (is it that hard?)…

https://imgur.com/a/llN7V0W

BoredPositron2• 8 months ago

The kicker for nano banana is not prompt adherence which is a really nice to have but the fact that it's either working on pixel space or with a really low spatial scaling. It's the only model that doesn't kill your details because of vae encode/decode.

sebzim4500• 8 months ago

It's really cool how good of a job it did rendering a page given its HTML code. I was not expecting it to do nearly as well.

kridsdale12• 8 months ago

Same. This must have training from sites that show html next to screenshots of the pages.

leviathant2• 8 months ago

I was kind of surprised by this line:

Nano Banana is terrible at style transfer even with prompt engineering shenanigans

My context: I'm kind of fixated on visualizing my neighborhood as it would have appeared in the 18th century. I've been doing it in Sketchup, and then in Twinmotion, but neither of those produce "photorealistic" images... Twinmotion can get pretty close with a lot of work, but that's easier with modern architecture than it is with the more hand-made, brick-by-brick structures I'm modeling out.

As different AI image generators have emerged, I've tried them all in an effort to add the proverbial rough edges to snapshots of the models I've created, and it was not until Nano Banana that I ever saw anything even remotely workable.

Nano Banana manages to maintain the geometry of the scene, while applying new styles to it. Sometimes I do this with my Twinmotion renders, but what's really been cool to see is how well it takes a drawing, or engraving, or watercolor - and with as simple a prompt as "make this into a photo" it generates phenomenal results.

Similarly to the Paladin/Starbucks/Pirate example in the link though, I find that sometimes I need to misdirect a little bit, because if I'm peppering the prompt with details about the 18th century, I sometimes get a painterly image back. Instead, I'll tell it I want it to look like a photograph of a well preserved historic neighborhood, or a scene from a period film set in the 18th century.

As fantastic as the results can be, I'm not abandoning my manual modeling of these buildings and scenes. However, Nano Banana's interpretation of contemporary illustrations has helped me reshape how I think about some of the assumptions I made in my own models.

echelon4• 8 months ago

You can't take a highly artistic image and supply it as a style reference. Nano Banana can't generalize to anything not in its training.

leviathant2• 8 months ago

Fair enough! I suppose I've avoided that kind of "style transfer" for a variety of reasons, it hadn't even occurred to me that people were still interested in that. And I don't say that to open up debate on the topic, just explaining away my own ignorance/misinterpretation. Thanks

simonw4• 8 months ago

I like the Python library that accompanies this: https://github.com/minimaxir/gemimg

I added a CLI to it (using Gemini CLI) and submitted a PR, you can run that like so:

  GEMINI_API_KEY="..." \
  uv run --with https://github.com/minimaxir/gemimg/archive/d6b9d5bbefa1e2ffc3b09086bc0a3ad70ca4ef22.zip \
    python -m gemimg "a racoon holding a hand written sign that says I love trash"

Result in this comment: https://github.com/minimaxir/gemimg/pull/7#issuecomment-3529...

echelon4• 8 months ago

The author went to great lengths about open source early on. I wonder if they'll cover the QwenEdit ecosystem.

I'm exceptionally excited about Chinese editing models. They're getting closer and closer to NanoBanana in terms of robustness, and they're open source. This means you can supply masks and kernels and do advanced image operations, integrate them into visual UIs, etc.

You can even fine tune them and create LoRAs that will do the style transferring tasks that Nano Banana falls flat on.

I don't like how closed the frontier US models are, and I hope the Chinese kick our asses.

That said, I love how easy it'll be to distill Nano Banana into a new model. You can pluck training data right out of it: ((any image, any instruction) -> completion) tuples.

minimaxir15• 8 months ago

I've been keeping an eye on Qwen-Edit/Wan 2.2 shenanigans and they are interesting: however actually running those types of models is too cumbersome and in the end unclear if it's actually worth it over the $0.04/image for Nano Banana.

msp26• 8 months ago

I don't like how closed the frontier US models are, and I hope the Chinese kick our asses.

For imagegen, agreed. But for textgen, Kimi K2 thinking is by far the best chat model at the moment from my experience so far. Not even "one of the best", the best.

It has frontier level capability and the model was made very tastefully: it's significantly less sycophantic and more willing to disagree in a productive, reasonable way rather than immediately shutting you out. It's also way more funny at shitposting.

I'll keep using Claude a lot for multimodality and artifacts but much of my usage has shifted to K2. Claude's sycophancy is particular is tiresome. I don't use ChatGPT/Gemini because they hide the raw thinking tokens, which is really cringe.

vunderba5• 8 months ago

The Qwen-Edit images from my GenAI Image Editing Showdown site were all generated from a ComfyUI workflow on my machine - it's shockingly good for an open-weight model. It was also the only model that scored a passing grade on the Van Halen M&M test (even compared against Nanobanana)

https://genai-showdown.specr.net/image-editing

ctippett• 8 months ago

Any reason for not also adding a project.scripts entry for pyproject.toml? That way the CLI (great idea btw) could be installed as a tool by uv.

simonw4• 8 months ago

I decided to avoid that purely to keep changes made to the package as minima as possible - adding a project.scripts means installing it adds a new command alias. My approach changes nothing other than making "python -m gemimg" do something useful.

I agree that a project.scripts would be good but that's a decision for the maintainer to take on separately!

sorcercode2• 8 months ago

@simonw: slight tangent but super curious how you managed to generate the preview of that gemini-cli terminal session gist - https://gistpreview.github.io/?17290c1024b0ef7df06e9faa4cb37...

is this just a manual copy/paste into a gist with some html css styling; or do you have a custom tool à la amp-code that does this more easily?

simonw4• 8 months ago

I used this tool: https://tools.simonwillison.net/terminal-to-html

I made a video about building that here: https://simonwillison.net/2025/Oct/23/claude-code-for-web-vi...

It works much better with Claude Code and Codex CLI because they don't mess around with scrolling in the same way as Gemini CLI does.

ilyakaminsky• 8 months ago

I use Gemini CLI on a daily basis. It used to crash often and I'd lose the chat history. I found this tool called ai-cli-log [1] and it does something similar out of the box. I don't run Gemini CLI without it.

[1] https://github.com/alingse/ai-cli-log

minimaxir15• 8 months ago

I just merged the PR and pushed 0.3.1 to PyPI. I also added README documentation and allowed for a `gemimg` entrypoint to the CLI via project.scripts as noted elsewhere in the thread.

peetle• 8 months ago

In my own experience, nano banana still has the tendency to:

- make massive, seemingly random edits to images - adjust image scale - make very fine grained but pervasive detail changes obvious in an image diff

For instance, I have found that nano-banana will sporadically add a (convincing) fireplace to a room or new garage behind a house. This happens even with explicit "ALL CAPS" instructions not to do so. This happens sporadically, even when the temperature is set to zero, and makes it impossible to build a reliable app.

Has anyone had a better experience?

andblac• 8 months ago

The "ALL CAPS" part of your comment got me thinking. I imagine most llms understand subtle meanings of upper case text use depending on context. But, as I understand it, ALL CAPS text will tokenize differently than lower case text. Is that right? In that case, won't the upper case be harder to understand and follow for most models since it's less common in datasets?

minimaxir15• 8 months ago

There's more than enough ALL CAPS text in the corpus of the entire internet, and enough semantic context associated with it for it to be intended to be in the imperative voice.

symisc_devel• 8 months ago

I work on the PixLab prompt based photo editor (https://editor.pixlab.io), and it follows exactly what you type with explicit CAPS.

ainiriand• 8 months ago

The blueberry and strawberry are not actually where they prompted.

mFixman• 8 months ago

The author overlooked an interesting error in the second skull pancake image: the strawberry is on the right eye socket (to the left of the image), and the blackberry is on the left eye socket (to the right of the image)!

This looks like it's caused by 99% of the relative directions in image descriptions describing them from the looker's point of view, and that 99% of the ones that aren't it they refer to a human and not to a skull-shaped pancake.

martin-adams• 8 months ago

I picked up on that also. I feel that a lot of humans would also get confused about whether you mean the eye on the left, or the subject's left eye.

Closi• 8 months ago

To be honest this is the sort of thing Nano Bannana is weak at in my experience. It's absolutely amazing - but doesn't understand left/right/up/down/shrink this/move this/rotate this etc.

See below to demonstrate this weakness with the same prompts as the article see the link below, which demonstrates that it is a model weakness and not just a language ambiguity:

https://gemini.google.com/share/a024d11786fc

jonas21• 8 months ago

I am a human, and I would have done the same thing as Nano Banana. If the user had wanted a strawberry in the skull's left eye, they should've said, "Put a strawberry in its left eye socket."

kjeksfjes• 8 months ago

Exactly what I was thinking too. I'm a designer, and I'm used to receiving feedback and instructions. "The left eye socket" would to me refer to what I currently see in front of me, while "its left eye socket" instantly shift the perspective from me to the subject.

minimaxir15• 8 months ago

I admit I missed this, which is particularly embarrassing because I point out this exact problem with the character JSON later in the post.

For some offline character JSON prompts I ended up adding an additional "any mentions of left and right are from the character's perspective, NOT the camera's perspective" to the prompt, which did seem to improve success.

frumiousirc• 8 months ago

The lack of proper indentation (which you noted) in the Python fib() examples was even more apparent. The fact that both AIs you tested failed in the same way is interesting. I've not played with image generation, is this type of failure endemic?

sib• 8 months ago

Came to make exactly the same comment. It was funny that the author specifically said that Nano Banana got all five edit prompts correct, rather than noting this discrepancy, which could be argued either way (although I think the "right eye" of a skull should be interpreted with respect to the skull's POV.)

zulban• 8 months ago

Extroverts tend to expect directions from the perspective of the skull. Introverts tend to expect their own perspective for directions. It's a psychology thing, not an error.

layer8• 8 months ago

It’s one of the best results I’ve seen for this particular test, and it’s one that doesn’t have obvious signs of “AI slop” aside from the ridiculous premise.

It’s pretty good, but one conspicuous thing is that most of the blueberries are pointing upwards.

satvikpendem2• 8 months ago

For images of people generated from scratch, Nano Banana always adds a background blur, it can't seem to create more realistic or candid images such as those taken via a point and shoot or smartphone, has anyone solved this sort of issue? It seems to work alright if you give it an existing image to edit however. I saw some other threads online about it but I didn't see anyone come up with solutions.

kridsdale12• 8 months ago

Maybe try including “f/16” or “f/22” as those are likely to be in the training set for long depth of field photos.

satvikpendem2• 8 months ago

I tried that but they don't seem to make much difference for whatever reason, you still can't get a crisp shot such as this [0] where the foreground and background details are all preserved (linked shot was taken with an iPhone which doesn't seem to do shallow depth of field unless you use their portrait mode).

[0] https://www.lux.camera/content/images/size/w1600/2024/09/IMG...

astrange5• 8 months ago

Those are rarely in the captions for the image. They'd have to extract the EXIF for photos and include it in recaptioning. Which they should be doing, but I doubt they thought about it.

jdc0589• 8 months ago

I don't feel like I should search for "nano banana" on my work laptop

insane_dreamer2• 8 months ago

I haven't paid much attention to image generation models (not my area of interest), but these examples are shockingly good.

comex• 8 months ago

I tried asking for a shot from a live-action remake of My Neighbor Totoro. This is a task I’ve been curious about for a while. Like Sonic, Totoro is the kind of stylized cartoon character that can’t be rendered photorealistically without a great deal of subjective interpretation, which (like in Sonic’s case) is famously easy to get wrong even for humans. Unlike Sonic, Totoro hasn’t had an actual live-action remake, so the model would have to come up with a design itself. I was wondering what it might produce – something good? something horrifying? Unfortunately, neither; it just produced a digital-art style image, despite being asked for a photorealistic one, and kept doing so even when I copied some of the keyword-stuffing from the post. At least it tried. I can’t test this with ChatGPT because it trips the copyright filter.

roywiggins2• 8 months ago

Another thing it can't do is remove reflections in windows, it's nearly a no-op.

sejje• 8 months ago

> "The image style is definitely closer to Vanity Fair (the photographer is reflected in his breastplate!)"

I didn't expect that. I would have definitely counted that as a "probably real" tally mark if grading an image.

Genego10• 8 months ago

I have been generating a few dozen images per day for storyboarding purposes. The more I try to perfect it, the easier it becomes to control these outputs and even keep the entire visual story as well as their characters consistent over a few dozen different scenes; while even controlling the time of day throughout the story. I am currently working with 7 layers prompts to control for environment, camera, subject, composition, light, colors and overall quality (it might be overkill, but it’s also experimenting).

I also created a small editing suite for myself where I can draw bounding boxes on images when they aren’t perfect, and have them fixed. Either just with a prompt or feeding them to Claude as image and then having it write the prompt to fix the issue for me (as a workflow on the api). It’s been quite a lot of fun to figure out what works. I am incredibly impressed by where this is all going.

Once you do have good storyboards. You can easily do start-to-end GenAI video generation (hopping from scene to scene) and bring them to life and build your own small visual animated universes.

taylorhughes• 8 months ago

We use nano banana extensively to build video storyboards, which we then turn into full motion video with a combination of img2vid models. It sounds like we're doing similar things, trying to keep images/characters/setting/style consistent across ~dozens of images (~minutes of video). You might like the product depending on what you're doing with the outputs! https://hypernatural.ai

Genego10• 8 months ago

Yes we are definitely doing the same! For now I’m just familiarizing myself in this space technically and conceptually. https://edwin.genego.io/blog

roywiggins2• 8 months ago

Your "Dracula" character is possibly the least vampiric Dracula I've ever seen tbh

nolroz• 8 months ago

The website lets you type in an entire prompt, then tells you to login, then dumps your prompt and leaves you with nothing. Lame.

nashadelic• 8 months ago

The more I try to perfect it, the easier it becomes I have the opposite experience, once it goes off track, its nearly impossible to bring it back on message

Genego10• 8 months ago

How much have you experimented with it? For some stories I may generate 5 image variations of 10-20 different scenes and then spend time writing down what worked and what did not; and running the generation again (this part is mostly for research). It’s certainly advancing my understanding over time and being able to control the output better. But I’m learning that it takes a huge amount of trial and error. So versioning prompts is definitely recommended, especially if you find some nuances that work for you.

brulard• 8 months ago

That sounds intriguing. 7 layers - do you mean its one prompt composed of 7 parts, like different paragraphs for each aspect? How do you send bounding box info to banana? Does it understand something like that? What does claude add to that process? Makes your prompt more refined? Thanks

Genego10• 8 months ago

Yes, the prompt is composed of 7 different layers, where I group together coherent visual and temporal responsibilities. Depending on the scene, I usually only change 3-5 layers, but the base layers still stay the same; so the scenes all appear within the same story universe and same style. If something feels off, or feels like it needs to be improved, I just adjust one layer after the other to experiment with the results on the entire story, but also on individual scene level. Over time, I have created quite some 7-Layer style profiles, that work well, and I can cast onto different story universes. Keep in mind this is heavy experimentation, it may just be that there is a much easier way to do this, but I am seeing success with this. https://edwin.genego.io/blog/lpa-studio - at any point I may throw this all out and start over; depending on how well my understanding of this all develops.

Bounding boxes: I actually send an image with a red box around where the requested change is needed. And 8 out of 10 times it works well. But if it doesn't work, I use Claude to make the prompt more refined. The Claude API call that I make, can see the image + the prompt, as well understanding the layering system. This is one of the 3 ways I edit, there is another one where I just sent the prompt to Claude without it looking at the image. Right now this all feels like dial-up. With a minimum of 0.035$ per image generation (0.0001$ if I just use a LoRa though) and a minimum of 12-14 seconds wait on each edit/generation.

weq• 8 months ago

I dont get how these tools are considered good when they cant even do a simple thing decribing this scene.

i was to bring awareness to the dangers of dressing up like a seal while surfboarding (ie. wearing black wetsuites, arms hanging over the board). Create a scene from the perspective of a shark looking up from the bottom of the ocean into a clear blue sky with silhouettes of a seal and a surfer and fishing boat with line dangling in the water and show how the shark contemplates attacking all these objects because they look so similiar.

I havnt found a model yet that can process that description, or any varition, into a scene that usable and makes sense visually to anyone older the a 1st grader. They will never place the seal, surfer, shark or boat in the correct location to make sense visually. Typically everyone is under water, sizing of everything is wrong. You tell them to the image is wrong, to place the person ontop of the water, and they cant. Please can someone link to a model that is capable or tell me what i am doing wrong? How can you claim to process words into images in a repeatable way when these systems cant deal with multiple contraints at once?

astrange5• 8 months ago

You'll have somewhat better luck if you fix the spelling errors.

https://lmarena.ai/c/019a84ec-db09-7f53-89b1-3b901d4dc6be

https://gemini.google.com/share/da93030f131b

Obviously neither are good but it is better.

I think image models could be producing a lot more editable outputs if eg they output multi-layer PSDs.

vunderba5• 8 months ago

I also created a small editing suite for myself where I can draw bounding boxes on images when they aren’t perfect, and have them fixed. Either just with a prompt or feeding them to Claude as image and then having it write the prompt to fix the issue for me (as a workflow on the api)

Are you talking about Automatic1111 / ComfyUI inpainting masks? Because Nano doesn't accept bounding boxes as part of its API unless you just stuffed the literal X/Y coordinates into the raw prompt.

You could do something where you draw a bounding box and when you get the response back from Nano, you could mask that section back back over the original image - using a decent upscaler as necessary in the event that Nano had to reduce the size of the original image down to ~1MP.

rcarr2• 8 months ago

You can literally just open the image up in Preview or whatever and add a red box, circle etc and then say "in the area with the red square make change foo" and it will normally get rid of the red box on the generated image. Whether or not it actually makes the change you want to see is another matter though. It's been very hit or miss for me.

Genego10• 8 months ago

No I am using my own workflows and software for this. I made nano-banana accept my bounding boxes. Everything is possible with some good prompting: https://edwin.genego.io/blog/lpa-studio < there are some videos of an earlier version there while I am editing a story. Either send the coords and describe the location well, or draw a box around the bb and tell it to return the image without the drawn bb, and only the requested changes.

It also works well if you draw a bb on the original image, then ask Claude for a meta-prompt to deconstruct the changes into a much more detailed prompt, and then send the original image without the bbs for changes. It really depends on the changes you need, and how long you're willing to wait.

- normal image editing response: 12-14s

- image editing response with Claude meta-prompting: 20-25s

- image editing response with Claude meta-prompting as well as image deconstructing and re-constructing the prompt: 40-60s

(I use Replicate though, so the actual API may be much faster).

This way you can also go into new views of a scene by zooming in and out the image on the same aspect-ratio canvas, and asking it to generatively fill the white borders around. So you can go from an tight inside shot, to viewing the same scene from outside of an house window. Or from inside the car, to outside the car.

gassi3• 8 months ago

Once you do have good storyboards. You can easily do start-to-end GenAI video generation (hopping from scene to scene) and bring them to life and build your own small visual animated universes.

I keep hearing advocates of AI video generation talking at length about how easy the tools are to use and how great the results are, but I've yet to see anyone produce something meaningful that's coherent, consistent, and doesn't look like total slop.

scotty799• 8 months ago

You'll have to wait for actual talented artists to start using these tools.

DrSiemer• 8 months ago

Bots in the Hall. Neural Viz. The Meat Dept video for Igorrr's ADHD. More will come.

You need talented people to make good stuff, but at this time most of them still fear the new tools.

BeetleB2• 8 months ago

Nano Banana can be frustrating at times. Yesterday I tried to get it to do several edits to an image, and it would return back pretty much the same photo.

Things like: Convert the people to clay figures similar to what one would see in a claymation.

And it would think it did it, but I could not perceive any change.

After several attempts, I added "Make the person 10 years younger". Suddenly it made a clay figure of the person.

minimaxir15• 8 months ago

The first request is a style transfer, which is why I included the Ghibli failure example.

BeetleB2• 8 months ago

I've gotten it to make Ghibli transfers by responding to the initial attempt with "I can barely tell the difference. Make the effect STRONGER."

Der_Einzige• 8 months ago

I really wish that real expert stuff, like how to do controlnet, use regional prompting, or most other advanced ComfyUI stuff got upvoted to the top instead.

tomalbrc• 8 months ago

Cute. What’s the use case?

qayxc• 8 months ago

NSFW, mostly

AuthError• 8 months ago

use it for technical design doc, where i sketch out something on paper and ask nano banana to make flow chat, its incredibly good at this kind of editing (also if want to borrow image from someone and change some bridges usually its hard its embedded image, but nano banana solves that)

4b11b4• 8 months ago

I found this well written. I read it start to finish. The author does a good job of taking you through their process

smerrill25• 8 months ago

Created a tool you can try out!! sorry to self-plug but I launch on Product Hunt next week that lets you do this:)

www.brandimagegen.com

if you want a premium account to try out, you can find my email in my bio!!

icemelt8• 8 months ago

how did you do NSFW?

vunderba5• 8 months ago

Good read minimaxir! From the article:

Nano Banana supports a context window of 32,768 tokens: orders of magnitude above T5’s 512 tokens and CLIP’s 77 tokens.

In my pipeline for generating highly complicated images (particularly comics [1]), I take advantage of this by sticking a Mistral 7b LLM in-between that takes a given prompt as an input and creates 4 variations of it before sending them all out.

Surprisingly, Nano Banana is terrible at style transfer even with prompt engineering shenanigans, which is not the case with any other modern image editing model.

This is true - though I find it works better by providing a minimum of two images. The first image is intended to be transformed, and the second image is used as "stylistic aesthetic reference". This doesn't always work since you're still bound by the original training data, but it is sometimes more effective than attempting to type out a long flavor text description of the style.

[1] https://mordenstar.com/portfolio/zeno-paradox

junon2• 8 months ago

It might also be an explicit guard against Studio Ghibli specifically after the "make me Ghibli" trend a while back, which upset Studio Ghibli (understandably so).

minimaxir15• 8 months ago

It happens with other styles. The demo documentation example which attempts to transfer an image into the very-public-domain Starry Night by Van Gogh doesn't do a true style transfer: https://x.com/minimaxir/status/1963429027382694264

empressplay• 8 months ago

This article was a good read, but the writer doesn't seem to understand how model-based image generation actually works, using language that suggests the image is somehow progressively constructed the way a human would do it. Which is absurd.

I've noticed a lot of this misinformation floating around lately, and I can't help but wonder if it's intentional?

minimaxir15• 8 months ago

I'm not sure what you're implying is incorrect/misleading. As noted in the post, autoregressive models like Nano Banana and gpt-image-1 generate by token (and each generated token attends to all previous tokens, both text and image) which are then decoded, while diffusion models generate the entire image simultaneously, refined over n iteration steps.

achatham• 8 months ago

My personal project is illustrating arbitrary stories with consistent characters and settings. I've rewritten it at least 5 times, and Nano Banana has been a game-changer. My kids are willing to listen to much more sophisticated stories as long as it has pictures, so I've used it to illustrate text like Ender's Game. Unfortunately, it's getting harder to legally acquire books in a format you can feed to an LLM.

I first extract all the entities from the text, generate characters from an art style, and then start stitching them together into individual illustrations. It works much better with NB than anything else I tried before.

squigz4• 8 months ago

so I've used it to illustrate text like Ender's Game

That sounds interesting. Could you share?

sigspec• 8 months ago

regarding buzzword usage

"YOU WILL BE PENALIZED FOR USING THEM"

That is disconcerting.

sixhobbits2• 8 months ago

It's really nice to see long-form, obviously human-written blogs from people deep into the LLM space - maybe us writers will be around for a while still in spite of all the people saying we've been replaced.

minimaxir15• 8 months ago

I've started increasing the number of jokes in my blog posts to make it sound more obviously human-written: to be honest I was expecting some "why is this so unserious" complaints.

sixhobbits2• 8 months ago

Can't make everyone happy!

baxtr• 8 months ago

In other words: you show your "personality".

AI can't do that (yet?).

debesyla• 8 months ago

Kinda like paper newspapers. In some ways it's "not optimal", but in many ways it's irreplaceable.

Bromeo• 8 months ago

This works with the openrouter API as well, which skips having to make a google account etc. Here's a Claude-coded openrouter compatible adaptation which seems to work fine: https://github.com/RomeoV/gemimg

A 1024x1024 image seems to cost about 3ct to generate.

Psype2• 8 months ago

That article says that most image generators had been over-shadowed by gpt.

Yet when I ask some simple tasks to it, like doing a 16:9 picture sized image instead of a square one, it ends up doing a 16:9 on a white background that matches a square.

When I ask it to make it with text, then on the second request to redo while changing just a certain visual element, it ends up breaking the previously asked text.

It's getting more good at flattering people and telling them how clever and right they are than actually doing the task.

Miraltar• 8 months ago

It doesn't say that gpt is better, just that it is more popular

Ylpertnodi• 8 months ago

It's getting more good at flattering people and telling them how clever and right they are than actually doing the task.

Not (knowingly) used an llm for a long time. Is the above true?

jamesthurley• 8 months ago

Nope

James_K• 8 months ago

Perhaps I'm childish, but nano banana = tiny penis.

kuu• 8 months ago

It was very interesting, I liked your style of explaining both at user level but also at more technical level.

Very cool post, thanks for sharing!

sd9• 8 months ago

Nano Banana supports a context window of 32,768 tokens: orders of magnitude above T5’s 512 tokens and CLIP’s 77 tokens.

I had no idea that the context window was so large. I’d been instinctively keeping my prompts small because of experience with other models. I’m going to try much more detailed prompts now!

skeptrune• 8 months ago

I need to give this a shot for turning written stories into comics. Seems like the technology is finally there.

d4rkp4ttern• 8 months ago

Photo-realism is great but the real step-jump in image-gen I’m looking for is the ability to draw high quality technical diagrams with a mix of text and images, so I can stop having LLMs generate crappy diagrams with mermaid, SVG, HTML/CSS, draw.io

Twelveday• 8 months ago

Great post with some nice insights I could've used a few days ago!

I was trying to create a simple "mascot logo" for my pet project. I first created an account on Kittl [0] and even paid for one month but it was quite cumbersome to generate images until I figured out I could just use the nano banana api myself.

Took me 4 prompts to ai-slop a small python script I could run with uv that would generate me a specified amount of images with a given prompt (where I discovered some of the insight the author shows in their post). The resulting logo [1] was pretty much what I imagined. I manually added some text and played around with hue/saturation in Kittl (since I already paid for it :)) et voilà.

Feeding back the logo to iterate over it worked pretty nicely and it even spit out an "abstract version" [2] of the logo for favicons and stuff without a lot of effort.

All in all this took me 2 hours and around 2$ (excluding the 1 month Kittl subscription) and I would've never been able to draw something like that in Illustrator or similar.

[0] https://www.kittl.com/ [1] https://github.com/sidneywidmer/yass/blob/master/client/publ... [2] https://github.com/sidneywidmer/yass/blob/master/client/publ...

slightknack• 8 months ago

The minimaxir/gemimg repo is pretty cool, fwiw.

Going further, one thing you can do is give Gemini 2.5 a system prompt like the following:

https://goto.isaac.sh/image-prompt

And then pass Gemini 2.5's output directly to Nano-Banana. Doing this yields very high-quality images. This is also good for style transfer and image combination. For example, if you then give Gemini 2.5 a user prompt that looks something like this:

    I would like to perform style transfer. I will provide the image generation model a photograph alongside your generated prompt. Please write a prompt to transfer the following style: {{ brief style description here }}.

You can get aesthetic consistently-styled images, like these:

https://goto.isaac.sh/image-style-transfer

skocznymroczny• 8 months ago

I like to use these AI models for generating mockup screenshots of game. I can drop a "create a mockup screenshot of a steampunk 2D platformer in which you play as a robot" and it will give me some interesting screenshot. Then I can ask it to iterate on the style. Of course it's going to be broken in some ways and it's not even real pixel art, but it gives a good reference to quickly brainstorm some ideas.

Unfortunately I have to use ChatGPT for this, for some reason local models don't do well with such tasks. I don't know if it's just the extra prompting sauce that ChatGPT does or just diffusion models aren't well designed for these kind of tasks.

AgentMatt• 8 months ago

Great article!

Regarding the generated cat image:

Each and every rule specified is followed.

Not quite; the eye color and heterochromia is followed only so-so.

The black-and-silver cat seems to have no heterochromia; eye color could be interpreted as silver though.

The white-and-gold cat _does_ have heterochromia. The colors can be interpreted as "white" and "gold", though I'd describe them as whitish-blue and orange. What's interesting about this is an adjustment of the instructions toward biologically more plausible eye colors in the cat which also has more natural fur colors.

The last cat's fur colors are so "implausible" that the model doesn't seem to have problems taking exactly those colors for the (heterochromatic) eyes too!

Zopieux• 8 months ago

it is possible to generate NSFW images through Nano Banana—obviously I cannot provide examples.

It is in fact not at all obvious why you can't.

The American prudishness continues to boggle my mind.

Nano Banana can be prompt engineered for nuanced AI image generation

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