Google’s Nano Banana 2 flash model could be nearing launch: Report

Google appears to be closing in on the release of its next lightweight image generation tool, Nano Banana 2 Flash. The new model is expected to build on the current Flash variant, which focuses on speed and efficiency rather than high-end precision. While the company has not formally acknowledged its existence, emerging evidence from app code references and early user reports suggests a public rollout may not be far off. If this version mirrors Google’s previous pattern, it could reach free-tier users, a notable shift after Nano Banana Pro remained exclusive to paying subscribers.

A report from TestingCatalog uncovered the first substantial clues. The publication found direct references to Nano Banana 2 Flash within the Gemini app, including the codename “Mayo”, which appears to be paired with the earlier “Ketchup” codename used for the Pro edition. This internal naming pattern hints at a connected development cycle. Adding to the anticipation, several users on social platforms claim they have already accessed the model through early testing channels, sharing samples attributed to Nano Banana 2 Flash.

Technical details remain unconfirmed, but the broader Flash series provides a strong indication of what to expect. The model is likely to prioritise low-latency output, quick image generation, and reduced compute overheads. This focus makes it especially suitable for users who want fast results rather than complex, high-fidelity visuals. For Google, efficiency improvements also translate to lower operating costs, creating space to offer more tools without locking them behind paid tiers. If that holds true, free-tier users could gain access to image editing and generation abilities that have so far been out of reach.

NotebookLM may also benefit from this upcoming release. At present, its style-based image capabilities rely on Nano Banana Pro and are limited to Google AI Pro subscribers. If Nano Banana 2 Flash reaches a wider audience, NotebookLM could extend similar features with appropriate usage caps. This fits Google’s broader strategy of expanding lightweight AI upgrades across its ecosystem, offering more functionality while managing infrastructure load.