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Model details
Nano Banana
Nano Banana is Google DeepMind's internally nicknamed image generation and editing model that brings together text and image understanding in a single system. Unlike earlier AI image tools that often lost track of a subject's appearance during edits, this model prioritizes likeness preservation—keeping a character's or product's look consistent across multiple transformations. It handles everything from seamless text-to-image generation to nuanced multi-step edits using plain language instructions, and supports flexible aspect ratio control through the API. The architecture is designed to be responsive, delivering lower latency than previous generations while maintaining strong character and scene consistency, making it well-suited for storytelling, branding, and rapid creative prototyping.
Originally unveiled in August 2025 with broader availability through Google's AI Studio, Gemini API, and Vertex AI platforms, the model integrates naturally into existing Google developer workflows. Each generated output carries Google's SynthID watermark, providing built-in transparency about AI-generated content. Creative professionals, marketers, and developers have found it particularly useful for projects requiring iterative visual refinement, image fusion, and contextual editing where maintaining visual coherence matters. The multi-turn conversation capability allows users to build on previous outputs without starting over, supporting more complex creative workflows and collaborative refinement cycles.
Quick Info
Powered by- Provider
- Kilo Gateway
- Model key
- google/gemini-2.5-flash-image
- Release date
- Aug 26, 2025
- Last updated
- Aug 26, 2025
- Knowledge cutoff
- 2024-06
- Input modalities
- Output modalities
- Capabilities
Cost
- Input token cost
- $0.15
- Output token cost
- $1.25
Limits
- Output tokens
- 8,192 tokens
- Context window
- 32,768 tokens
Transparent token rates
Compare Nano Banana pricing
Rates are shown per one million tokens. Combined means one million input plus one million output tokens.
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