Google’s new Nano Banana 2 Lite image model is its fastest and cheapest yet


There are plenty of AI image-generation models these days, but the ones capable of quality outputs tend to be slow and expensive. Google DeepMind says its new image model, known as Nano Banana 2 Lite, offers the best balance of quality and speed. It’s available today across the Google ecosystem, creating images in a fraction of the time it takes Google’s beefier models.

The new model is part of the Gemini 3.1 family—it’s technically called Gemini 3.1 Flash Lite Image. On one hand, Google says this model is ideal for exploring ideas and “rapid-fire” prototyping, applications in which quality can take a backseat. However, the company has also provided some examples aimed at showing how close Nano Banana 2 Lite can get to the quality of its other image models.

two AI images compared

A comparison of Nano Banana 2 Lite with the non-Lite version.

Credit:
Google

A comparison of Nano Banana 2 Lite with the non-Lite version.


Credit:

Google

In addition to the examples, Google also has Elo scores from Arena.ai ready to go, showing that users rate Nano Banana 2 Lite outputs almost as highly as the non-Lite versions. However, vibemarking doesn’t always focus on the details that can make AI images look silly upon closer inspection. Google notes that Nano Banana 2 Lite tends to have more trouble with text, particularly if it’s very small, and infographics are more likely to include incorrect data. Characters and people may also show poor consistency across iterations.

But it’s fast. You can go from text to an image in about 4 seconds in the default low-thinking mode. Generating the same images in the standard Nano Banana takes about 20 seconds. The speed and efficiency mean developers accessing Nano Banana 2 Lite via the API will pay a lot less. Google says it averages $0.034 per 1K image. The API rates are $0.25 for 1M input tokens and $1.50 for 1M output tokens. That’s half the rate for Nano Banana 2. For Nano Banana Pro, the input tokens are only a little more at $2 for 1M, but the output pricing is $12 (eight times higher).



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