AI image generation has become one of the most useful applications of generative AI. You can now create illustrations, product concepts, social media graphics, thumbnails, realistic scenes, posters, and many other visuals simply by describing what you want.
Google Gemini includes native image-generation capabilities known as Nano Banana. Instead of switching between separate AI tools, you can describe an image, generate it, upload reference images, and continue editing the result conversationally.
Google’s current Gemini image family includes Nano Banana 2, Nano Banana 2 Lite, Nano Banana Pro, and the original Nano Banana. Google now recommends Nano Banana models for image generation; its older Imagen models have been shut down in the Gemini API.
This guide explains how to generate AI images with Google Gemini, write better prompts, edit existing images, and use Gemini image generation through the API.
What Is Gemini AI Image Generation?
Gemini image generation allows you to create new images from natural-language instructions.
For example, you could enter:
Create a realistic photograph of a futuristic smart home surrounded by mountains at sunset, with warm cinematic lighting.
Gemini interprets the description and generates an image based on it.
However, Gemini is not limited to basic text-to-image generation. Its image models can also process existing images and follow instructions for editing or transforming them. Google specifically supports conversational image generation and editing using text, images, video in supported models, or combinations of these inputs.
That makes Gemini useful for tasks such as:
- Creating realistic AI images
- Generating illustrations
- Making blog and website graphics
- Designing social media visuals
- Creating product concepts
- Generating posters
- Adding text to images
- Editing existing photos
- Changing backgrounds
- Combining reference images
- Turning sketches into polished concepts
What Is Nano Banana?
You may have seen the name Nano Banana while using Gemini.
Nano Banana is Google’s name for Gemini’s native image-generation capabilities.
As of September 2026, Google’s Gemini API documentation lists four main Nano Banana image models.
Nano Banana 2 Lite — Gemini 3.1 Flash Lite Image
Model ID:
gemini-3.1-flash-lite-imageThis model focuses on low latency and cost-efficient image generation.
Nano Banana 2 — Gemini 3.1 Flash Image
Model ID:
gemini-3.1-flash-imageThis is Google’s recommended general-purpose image model. It balances image quality, intelligence, speed, text rendering, and cost.
Nano Banana Pro — Gemini 3 Pro Image
Model ID:
gemini-3-pro-imageThis model is designed for more demanding professional image-production tasks, complex instructions, layouts, and high-resolution visuals.
Nano Banana — Gemini 2.5 Flash Image
Model ID:
gemini-2.5-flash-imageThis is the older Nano Banana model. Google currently recommends moving newer workflows toward the Nano Banana 2 family.
For most new projects, Gemini 3.1 Flash Image / Nano Banana 2 is a sensible starting point.
How to Generate AI Images with Google Gemini
You don’t need advanced image-editing knowledge to get started. The quality of your prompt matters much more.
Step 1: Open Gemini
Open Google Gemini and sign in to your Google account.
Depending on your account, location, and available Gemini features, the interface and model options you see may differ.
Start a new conversation where image generation is available.
Step 2: Describe the Image You Want
Enter a clear description of the image.
For example:
Create a photorealistic image of a modern glass house in a green forest during light rain. Use cinematic lighting, realistic reflections, natural colors, and a wide landscape composition.
Gemini uses the details in your prompt to determine the subject, environment, composition, lighting, and overall visual style.
A simple prompt can work, but adding useful details generally gives you more control.
Step 3: Generate the Image
Submit your prompt.
Gemini will process the instructions and create an image based on your description.
If the first result isn’t exactly what you wanted, you don’t necessarily need to start again.
Instead, continue the conversation.
For example:
Make the lighting warmer and change the scene to sunset.
Then:
Add mountains in the background.
Then:
Make the house more minimal and remove the swimming pool.
Conversational iteration is one of the important strengths of Gemini’s native image generation. Google specifically recommends multi-turn conversations when iterating on image edits.
How to Write Better Gemini Image Prompts
A vague prompt such as:
Generate a car.
gives the model very little creative direction.
A stronger prompt could be:
Create a photorealistic futuristic electric sports car parked on a wet city street at night. Use a low camera angle, subtle neon reflections, realistic materials, cinematic lighting, and a premium automotive advertisement style.
A useful Gemini image prompt can include:
Subject + environment + style + composition + lighting + details
For example:
Create a realistic photo of a small coffee shop on a quiet street in Tokyo at night. Show warm light coming through the windows, light rain, reflections on the pavement, a few bicycles outside, cinematic photography, and a wide sixteen-by-nine composition.
The more important a visual detail is, the more clearly you should describe it.
Example Gemini AI Image Prompts
Here are some prompts you can modify for your own projects.
Photorealistic Image
Create a photorealistic image of a futuristic city in 2050, with electric vehicles, green skyscrapers, rooftop gardens, clean streets, pedestrians, and warm sunset lighting. Use cinematic photography and realistic architectural details.
Blog Featured Image
Create a clean modern featured image for a technology blog about artificial intelligence. Use a futuristic AI-inspired visual, lots of empty space, professional lighting, a simple composition, and a wide sixteen-by-nine layout. Avoid excessive text and clutter.
Product Image
Create a professional studio product photograph of a premium wireless earbud case on a clean desk. Use soft natural shadows, realistic materials, minimal background elements, and commercial product photography.
Social Media Graphic
Create a modern square social media graphic about artificial intelligence. Use a clean futuristic visual style, strong central composition, subtle technology elements, and enough empty space for a short headline.
YouTube Thumbnail Background
Create a dramatic sixteen-by-nine YouTube thumbnail background about artificial intelligence. Show a futuristic AI interface and glowing digital elements. Use strong contrast and keep the center-right area relatively clean for a person or headline.
Generate Images with Text
One historically difficult task for AI image generators has been producing readable text inside images.
Gemini’s newer image models specifically emphasize improved text rendering. Google recommends clearly specifying both the exact text and the desired visual treatment when text needs to appear in an image.
For example:
Create a minimalist technology poster with the exact headline “THE FUTURE OF AI”. Use large bold modern typography in the center. Add a subtle futuristic AI visual behind the headline. Keep the rest of the design clean and professional.
If the exact wording matters, place it inside quotation marks and explicitly say that it must appear exactly as written.
How to Edit an Existing Image with Gemini
Gemini can also use an existing image as input.
Upload an image and describe the change you want.
For example:
Replace the background with a modern office while keeping the main object unchanged.
Or:
Change this scene from daytime to nighttime while preserving the buildings and overall composition.
Other useful editing requests include:
Remove the unwanted objects from the background.
Make the lighting softer and more natural.
Turn this rough sketch into a realistic product concept.
Change the color of the product while keeping its shape unchanged.
Make the image look like professional studio photography.
Google’s current Gemini image API supports adding, removing, or modifying elements, changing styles, adjusting colors, and continuing those edits through multiple conversational turns.
Use Multiple Reference Images
More advanced Gemini image models can work with multiple reference images.
This can be particularly useful when you want to combine elements from different sources.
For example, you could provide a photo of a product and another photo showing a desired environment, then ask Gemini to create a new composition.
A prompt might say:
Use the product from the first image and place it naturally on the desk shown in the second image. Match the lighting, perspective, shadows, and reflections so the final result looks like a professional product photograph.
Current Gemini 3 image models can accept multiple reference images, although the exact supported number and fidelity depend on the specific model.
Generate AI Images with the Gemini API
Developers can integrate Gemini image generation directly into websites, apps, automation systems, and backend services.
First, create a Gemini API key and store it securely as an environment variable.
For Python, install Google’s SDK:
pip install -U google-genaiThen you can generate an image using Gemini.
import base64
from google import genai
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3.1-flash-image",
input="Generate a photorealistic futuristic city skyline at sunset",
)
with open("generated_image.png", "wb") as f:
f.write(
base64.b64decode(
interaction.output_image.data
)
)Google’s current getting-started documentation uses gemini-3.1-flash-image for native Gemini image generation through the Interactions API.
Generate Gemini Images with JavaScript
You can also integrate image generation into Node.js applications.
Install the package:
npm install @google/genaiThen initialize the Gemini client and send your image-generation request.
import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";
const ai = new GoogleGenAI({});
const interaction = await ai.interactions.create({
model: "gemini-3.1-flash-image",
input: "Generate a futuristic smart city at sunset",
});
const generatedImage = interaction.output_image;
if (generatedImage) {
const buffer = Buffer.from(
generatedImage.data,
"base64"
);
fs.writeFileSync(
"generated_image.png",
buffer
);
}This makes it possible to build your own AI image generator instead of requiring users to manually generate images through a chat interface.
Control Image Aspect Ratio
Different platforms need different image shapes.
For example:
1:1 works well for square social posts.
9:16 is useful for vertical content such as Stories and Shorts.
16:9 works well for YouTube thumbnails, presentations, and many blog featured images.
Gemini’s image-generation API allows developers to specify the aspect ratio.
For example:
interaction = client.interactions.create(
model="gemini-3.1-flash-image",
input="Create a futuristic AI workspace",
response_format={
"type": "image",
"aspect_ratio": "16:9",
"image_size": "2K"
},
)Gemini’s newer image models support multiple aspect ratios and image sizes.
Generate High-Resolution Images
Resolution is especially important when creating website banners, presentations, marketing graphics, or professional design assets.
Gemini 3 image models support higher-resolution generation.
Depending on the model, you can request resolutions such as:
- 1K
- 2K
- 4K
Gemini 3.1 Flash Image also supports a smaller 512-pixel option, while Gemini 3.1 Flash Lite Image is limited to 1K output.
For example:
response_format={
"type": "image",
"aspect_ratio": "16:9",
"image_size": "4K"
}When specifying these values through the API, use the exact supported format. Google notes that values such as 1K, 2K, and 4K require an uppercase K.
Nano Banana 2 vs Nano Banana Pro
Choosing the right model depends on what you’re creating.
Nano Banana 2 is designed as the general-purpose option. It offers a balance between speed, intelligence, image quality, text rendering, and cost.
It is a strong choice for:
- Blog images
- Social media graphics
- Product concepts
- General AI art
- Image editing
- High-volume applications
Nano Banana Pro focuses more heavily on professional visual production and complicated instructions.
It is better suited to situations where you need greater creative control, complex compositions, stronger text rendering, professional assets, or high-resolution output.
For most everyday users and developers, starting with Nano Banana 2 makes sense.
Can Gemini Generate 4K AI Images?
Yes, supported Gemini 3 image models can generate images up to 4K.
This makes Gemini useful beyond casual AI image generation. High-resolution output can be valuable for professional graphics, marketing assets, presentations, website visuals, and design concepts.
However, supported resolutions depend on the model you select.
Can Gemini Generate Images for Free?
Availability and pricing depend on the Gemini product, model, account, region, and whether you’re using the consumer Gemini experience or the Gemini API.
Therefore, don’t assume that every Gemini image model or every amount of image generation is unlimited and free.
For API-based projects, always check the current model pricing and your project’s available usage before building an application around large-scale image generation.
Common Problems with Gemini AI Images
The Image Doesn’t Match the Prompt
Add more specific details.
Instead of:
Create a laptop.
Try:
Create a photorealistic thin silver laptop on a wooden desk in a modern home office, viewed from a three-quarter angle, with soft morning window light and realistic shadows.
Text Is Incorrect
Specify the exact wording in quotation marks.
Also describe:
- Font appearance
- Text size
- Position
- Background
- Alignment
For complicated graphics, generating the required text first and then asking Gemini to create an image containing that text can improve results. Google specifically recommends this approach for text-heavy images.
The Image Looks Too Artificial
Add photography details such as:
Photorealistic, natural skin texture, realistic shadows, physically accurate materials, natural lighting, subtle depth of field, professional photography.
Avoid adding dozens of unnecessary style keywords. Clear visual instructions usually work better than random prompt terms.
Gemini Changes Something You Wanted to Keep
Tell it explicitly what must remain unchanged.
For example:
Keep the product, logo, camera angle, proportions, and lighting unchanged. Only replace the background with a modern office.
This is especially useful during multi-turn editing.
Tips for Better Gemini AI Images
The biggest improvement usually comes from better prompts rather than simply making prompts longer.
Describe the main subject first. Then explain the environment, visual style, camera angle or composition, lighting, colors, and any important restrictions.
For example:
Create a professional photo of a black smartwatch on a dark stone surface. Show the watch at a three-quarter angle with soft studio lighting and realistic reflections. Keep the background minimal and slightly blurred. Use a premium commercial product photography style.
That gives Gemini far more useful direction than:
Make a smartwatch image.
You can then refine the result conversationally instead of rewriting everything:
Keep everything the same but make the background lighter.
Then:
Make the watch slightly larger in the frame.
This iterative workflow is one of Gemini’s strongest image-generation features.
Are Gemini AI Images Watermarked?
Google states that images generated by its Nano Banana models include SynthID, Google’s invisible digital watermark for identifying AI-generated content.
This is designed to help identify content created or modified using Google’s generative AI systems.
Is Imagen Still Available in the Gemini API?
No.
This is important because many older tutorials still recommend Google’s Imagen models.
Google’s current documentation states that Imagen models have been shut down in the Gemini API and recommends using Nano Banana models for image generation instead.
Therefore, if you’re building a new Gemini image application in 2026, use the current Nano Banana models rather than following older Imagen API tutorials.
Frequently Asked Questions
Can Google Gemini generate AI images?
Yes. Gemini provides native image generation through Google’s Nano Banana family of image models.
What is Nano Banana 2?
Nano Banana 2 is Google’s Gemini 3.1 Flash Image model. Its API model ID is gemini-3.1-flash-image.
Can Gemini edit an existing image?
Yes. You can provide an existing image and ask Gemini to add, remove, modify, restyle, or otherwise transform visual elements.
Can Gemini generate images with text?
Yes. The newer Gemini image models are designed with improved text rendering. Clear instructions containing the exact text generally produce better results.
Can developers generate Gemini images using Python?
Yes. Google’s google-genai Python SDK supports Gemini image-generation workflows.
Can Gemini create 16:9 images?
Yes. Supported Gemini image models allow developers to specify aspect ratios including 16:9.
Can Gemini generate 4K images?
Supported Gemini 3 image models can generate images at up to 4K resolution.
Is Imagen better than Gemini for AI images?
Imagen is no longer available through the Gemini API. Google now directs developers to use the Nano Banana image models instead.
Final Thoughts
Google Gemini has evolved from an AI assistant into a powerful multimodal platform capable of both understanding and generating visual content.
With the current Nano Banana models, you can generate images from text, edit existing visuals, combine reference images, create graphics containing text, control aspect ratios, and produce high-resolution assets.
For most users and developers, Nano Banana 2 — Gemini 3.1 Flash Image is the most practical starting point because it balances quality, speed, intelligence, and flexibility.
Most importantly, focus on your prompts. Clearly describe the subject, environment, composition, lighting, style, and any elements that must remain unchanged. Then use Gemini’s conversational editing capabilities to refine the image rather than trying to create the perfect result with one enormous prompt.
With that workflow, Gemini can be used for everything from simple blog images and social graphics to product concepts, professional marketing assets, and AI-powered image-generation applications.
