Google's AI model lineup: Gemini, Veo, Nano Banana, and more explained

Google’s AI ecosystem has grown into a collection of specialized model families, each optimized for different tasks. The flagship Gemini family handles multimodal workloads—text, images, audio, video, and code—with variants like Pro (heavy reasoning and coding), Flash/Flash-Lite (speed and cost efficiency), and Nano (on-device features). For video, Google DeepMind’s Veo generates clips from text prompts and reference images, with controls for camera movement, style, and lighting. Imagen, Google’s older text-to-image family, is now deprecated for developers (endpoints discontinued June 2026) in favor of Gemini-based image models. The current image-generation and editing line is Nano Banana, built on Gemini, which supports detailed instructions, background replacement, object removal, and consistent character rendering across images. It comes in three tiers: Nano Banana Pro, Nano Banana 2, and Nano Banana 2 Lite, differing in capability, speed, and cost.

Beyond these, Google maintains additional specialized models. Gemma offers open-weight models for developers who want to customize and deploy locally. Lyria generates music from descriptions, while Chirp handles speech recognition and transcription. Gemini Nano powers on-device AI features in Android and other mobile contexts, enabling privacy-sensitive processing without cloud calls. For businesses, the key takeaway is that Google no longer offers a single universal AI; instead, professionals should evaluate each model family’s strengths (e.g., speed, modality, cost) and choose accordingly. Google AI Studio and Gemini Enterprise provide platforms to access and integrate these models into workflows, from coding assistants to marketing content creation.