I saw an item for sale on Ali Express's video and I thought "Wow, they hired some really attractive actors to pitch their little gadget." 30 seconds in, I realized they used GenAI. Not because it looked AI, but because the production values looked too high and professional for the item. I would get in on this if you sell anything online.

Kind of surprised it hasn't been pulled yet. Have seen some very disturbing (grok tier) examples of completely bypassing whatever censors they have in place by simply asking gemini to write the prompt

I have Google AI Ultra. Where can I test this? They say its in aistudio, which says its a paid model and I need to setup billing (as if paying for Ultra isnt enough). They say its available in antigravity, but I cant seem to find it there?

I'm officially done with the Nano Banana name. It was fun, but can we go back just calling it Gemini Image?

I really really want to see how these images are starting to form into videos. The stills are clearly getting better and better, but what about when you need the stills to organically conform to a keyed script?

How does it compare to Nano Banana Pro?

What is annoying about Nano Banana, is how bad is experience when you try to iterate or, especially, repeat same task for another photo. After second of third image it starts randomly ansering with complete nonsense like "I'm just a language mode and can't assist with that" or "I can't do that" (with absolutely the same prompt it had no issues 2 photos in a row in the same chat).

It also gaslights me, when I point out on an error. I tried to create a cartoon portrait of the person from photo and use background from another photo. It got wrong the order of photos. I provided filenames and explicitly told which one is for person and which for bg. It generated it wrong again, and all attempts to explain that it got it wrong were met with "No, it's YOU incorrect". So frustrating.

Interesting they get to rev this with the release of a new flash model. I'm speculating part of the distil pipeline includes the image gen stuff; that seems like internal tooling that will pay dividends over time, if true. New frontier model -> automatic new image model. Even if it's just incremental updates, it's good for both the product cadence and compounding improvements.

Google updated it early in AI Studio so I've been experimenting:

- Base pricing for a 1024x1024 image is almost 1.6x what normal Nano Banana is ($0.067 vs. $0.039), however you can now get a 512x512 image for cheaper, or a 4k image for cheaper than four 1k images: https://ai.google.dev/gemini-api/docs/pricing#gemini-3.1-fla...

- Thinking is now configurable between `Minimal` and `High` (was not the case with Nano Banana Pro)

- Safety of the model appears to be increased so typical copyright infringing/NSFW content is difficult to generate (it refused to let me generate cartoon characters having taken psychedelics)

- Generation speed is really slow (2-3min per image) but that may be due to load.

- Prompt adherence to my trickier prompts for Nano Banana Pro (https://minimaxir.com/2025/12/nano-banana-pro/) is much worse, unsurprisingly. For example I asked it to make a 5x2 grid with 10 given inputs and it keeps making 4x3 grids with duplicate inputs.

However, I am skeptical with their marquee feature: image search. Anyone who has used Nano Banana Pro for awhile knows that it will strongly overfit on any input images by copy/pasting the subject without changes which is bad for creativity, and I suspect this implementation appears the same.

Additionally I have a test prompt which exploits the January 2025 knowledge cutoff:

    Generate a photo of the KPop Demon Hunters performing a concert at Golden Gate Park in their concert outfits.

That still fails even with Grounding with Google Search and Image Search enabled, and more charitable variants of the prompt.

tl;dr the example images (https://deepmind.google/models/gemini-image/flash/) seem similar to Nano Banana Pro which is indeed a big quality improvement but even relative to base Nano Banana it's unclear if it justifies a "2" subtitle especially given the increased cost.

Would be interesting to see latency vs quality tradeoffs here. Are they targeting consumer-facing generation speed or prioritizing fidelity for professional workflows?