Nano Banana 2 Lite

The first example of generating home interiors fills me with indescribable hatred. Recently real estate agents have taken to running every dilapidated unsellable apartment through these AI filters, and you have to scroll through a dozen of these Ikea-chic images of what the apartment presumably could look like, before you are allowed to see the horrors they are trying to peddle at insane prices.

I received early access to test this model. (through work — Google still does not like me personally lol)

It works as advertised here, and it does behave like a distilled Nano Banana 2 with respect to certain elements such as good text rendering, which Nano Banana 1 does much worse with. It is definitely not at the level of the base Nano Banana 2 of course particularly with highly-nuanced prompts. My main criticism is that you cannot programmatically force aspect ratios with NB2L but you can with NB2.

That said, the price of $0.034/image is higher than expected since price is generally correlated with generation time, and it takes half the time to generate than a Nano Banana 1 image which costs $0.039/image. Google's assertion that you can directly replace NB1 pipelines with NB2L is fair.

Yesterday, Google announced that the Gemini app will allow free image generations (https://blog.google/innovation-and-ai/products/gemini-app/pe...) but did not specify which model would be used: I suspect it's the main motivation for Nano Banana 2 Lite.

The speed is definitely impressive. I'm seeing under 5 seconds per image vs ~30 seconds for base NB2.

I built an app for my kids that generates illustrated stories for them with them as the characters. I wanted to prioritize likeness while still stylizing the illustrations. I tested a bunch of models but none seem to come close to maintaining likeness when stylized. I find the others generate generic looking characters.

I'm excited to incorporate this into the onboarding of my app since I want the users to experience the aha moment as soon as possible and waiting half a minute+ isn't ideal. I'll still be using the main NB2 for the actual illustrations as this lite version still has slight issues with nuance and consistency as others have pointed out.

They didnt include chatgpt in the comparison chart. That tells a lot

It's sort of amazing that Grok's image model beats Nano Banana on nearly every one of the metrics they chose to highlight.

Expensive and Google doesn't even have enough resources to decently deploy a model like that. Creating 10 images in parallel gives me RESOURCE_EXHAUSTED error, which is a painfully common error when using Google AI products.

I'm way behind in imagegen - only using it occasionally for roleplaying tokens, goofing around, and random personal assets. To me, this is nuts. It's able to create images in like 2 seconds... before with chatgpt it would take 30s-1m for the same quality image. I don't get the negative comments here

NB2 is an impressive tool. Camera File -> Heavy Changes in NB2 -> Final Tweaks in Photoshop -> Production Image

It seems to respond to edits much better than the current production image model, which often stubbornly locks on to prior iterations of the images.

Wow, that's a pretty massive decrease in latency, which should unlock some use cases, but the linked web page doesn't exactly make it straightforward to understand the differences between the models.

However, based off my personal experiences with general images models, Google in my opinion is the best for my workflows. Granted, I haven't tried far-east providers yet.

What does everyone else think?

gemini is so far behind. starting to wonder if their strategy is launching the low cost alternative to image/text models. last release was 3.5 flash

It's only half the full model price, $30/m output: https://cloud.google.com/gemini-enterprise-agent-platform/ge...

Nano Banana is head and shoulders above the rest, but still too steep for personal use, and half off doesn't really mean much for enterprise if the results are worse. Hopefully this drives the rest to catch up at least.

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