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Model details
Nano Banana 2 (Vertex AI)
Nano Banana 2 is presented as Google's latest state-of-the-art image model, built on the Gemini the listed price family of models so that the same deep reasoning capabilities used in Gemini text models can be applied to image generation and editing. Google describes the model as bringing "advanced world knowledge, quality and reasoning" to image tasks while still running at the "fast speed" needed for interactive creative work, and it is positioned alongside Veo and Lyria as part of Google's broader creative model lineup. The image generation overview page frames it as a tool that lets users "dial in every detail," transforming the vibe of an image, shifting lighting from a sunny day to a moody night, experimenting with camera angles, and adjusting focus to make a subject pop.
In practice, Nano Banana 2 is aimed at creators and teams who need both high-quality generation and flexible editing in a single workflow. It can produce new images from text prompts, transform the look and texture of existing photos, and apply the style or color palette of a reference image to a subject, making it useful for rapid visual prototyping, marketing visuals, and photo-style experimentation. Google integrates the model into Vertex AI and the Gemini Enterprise Agent Platform, so it can be combined with other Gemini capabilities and creative models like Veo and Lyria for multi-step pipelines that mix reasoning, language, image, and video generation. This makes Nano Banana 2 a strong fit when an application needs an image model that can follow nuanced, knowledge-rich prompts while still feeling responsive in real-time creative tools.
Quick Info
Powered by- Provider
- Eden AI
- Model key
- vertex/gemini-3.1-flash-image
- Release date
- May 28, 2026
- Last updated
- May 28, 2026
- Knowledge cutoff
- 2025-01
- Input modalities
- Output modalities
- Capabilities
Cost
- Input token cost
- $0.50
- Output token cost
- $3.00
Limits
- Output tokens
- 32,768 tokens
- Context window
- 131,072 tokens
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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.
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