Google releases Nano Banana 2.1, based on Gemini 3.6 Flash, saying it improves on previous versions "across the board"; pricing is ~50% lower vs. Nano Banana 2

Image generation costs are cut in half, making advanced AI image creation more accessible for everyday use.

Google has launched Nano Banana 2.1, an image generation model based on its Gemini 3.6 Flash technology. This new version aims to improve across various aspects, including visual quality, text rendering, character consistency, panorama generation, and infographic accuracy, compared to its predecessor, Nano Banana 2, which was released in February 2026. A key change is a significant price reduction; generating a 1K image now costs 3.36 cents, approximately half of the previous 6.70 cents, with 4K images also seeing a similar price cut. Nano Banana 2.1 supports up to 14 reference images simultaneously, maintaining consistency for up to four characters and ten objects. It can also connect to Google Search and offers adjustable 'thinking levels' to influence image output. While benchmarks show improvements, the model is positioned as a more efficient counterpart to the higher-tier Nano Banana Pro. Nano Banana 2.1 is rolling out across Google's suite of products, including the Gemini app, Google Search, and Google Ads, while the older model, "gemini-3.1-flash-image," will be shut down on October 29, 2026.

The release of Nano Banana 2.1 signifies a strategic move by Google to democratize AI image generation by drastically reducing costs. This pricing strategy, nearly 50% lower than its predecessor, aims to encourage broader adoption and integration across a wider array of applications and user bases. By making high-resolution image generation more affordable, Google is likely to see increased usage across its various platforms, potentially setting a new market standard for cost-effectiveness in generative AI.

This tiered approach, with Nano Banana 2.1 as the efficient option and Nano Banana Pro for premium quality, allows Google to cater to diverse user needs and budget constraints. The improved consistency features and integration with Google Search suggest a push towards more practical, real-world applications rather than just experimental image creation. Users can expect more refined and contextually relevant AI-generated images in their daily interactions with Google's services.