AI Image Generator
Models
Nano

Google's cutting-edge image generation model

3 credits
Fast
High Quality
Gpt

OpenAI's GPT-4o image generation model

3 credits
High Quality
Text & Image
Seedream

ByteDance image generation and reference-based editing in 2K, 3K, or 4K

6 credits
2K/3K/4K
Text & Image
Flux

Flux Kontext standard model with balanced performance

4 credits
Fast
High Quality

Powered by Google Nano Banana 2 Official API

Public Visibility

When this option is enabled, the output image may be selected by AI Generate and published to the Explore.

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Sample Images
Gemini 3.1 Flash Image on Lovart ME

Nano Banana 2 AI Image Generator Create, edit, and iterate with Gemini 3.1 Flash Image

Start from a written brief or upload reference images, then choose the format that fits the job. This Lovart ME workflow supports up to 14 references, 15 aspect ratios, 1K to 4K output, and JPG or PNG files.

14
Reference images
JPEG, PNG, or WebP inputs
15
Aspect ratios
From 1:8 to 8:1, plus Auto
4K
Maximum output
Choose 1K, 2K, or 4K
2
Output formats
Download as JPG or PNG

What Nano Banana 2 is useful for

Google positions Nano Banana 2 as Gemini 3.1 Flash Image: a fast image model for generation and editing. The practical advantage is a shorter path from a rough direction to a controlled, reusable visual.

Text-to-image drafts

Describe the subject, setting, composition, lighting, and required text in one brief. Use 1K while exploring, then raise the resolution after the direction is stable.

Reference-led editing

Upload one image for a focused edit or combine several references for subject, object, palette, texture, and layout cues. State which property comes from each reference.

Readable text and localization

Create posters, labels, cards, and mockups that include text. Put the exact wording in quotation marks and request a clear hierarchy; always proofread the result before publishing.

Consistent subjects and objects

Google reports consistency for up to five characters and fidelity for up to 14 objects in a workflow. Stable names, clothing notes, and reference order make repeat scenes easier to direct.

Format-aware composition

Choose the final channel before generating. A vertical story, square product tile, wide banner, and panoramic backdrop need different subject placement and negative space.

Choose resolution and aspect ratio before the final render

Higher resolution is useful when the image will be cropped, printed, or reviewed closely, but it also uses more credits. Set the composition first so the final render is not spent fixing a layout problem.

1K for exploration

Use 1K for prompt testing, composition choices, and early stakeholder review. It is the lowest-cost way to compare directions.

2K for everyday publishing

Choose 2K for web headers, product pages, presentations, and social assets that need more detail without the highest output cost.

4K for final detail

Use 4K when the approved image needs cropping room, larger displays, or print preparation. Inspect faces, hands, logos, and small text at full size.

A practical ratio map

01

Square and product

1:1, 4:5, and 5:4 suit catalog tiles, profile posts, and balanced product compositions.

02

Portrait and mobile

2:3, 3:4, and 9:16 leave room for people, covers, posters, and full-screen mobile stories.

03

Landscape and campaign

3:2, 4:3, 16:9, and 21:9 fit editorial images, presentations, banners, and cinematic scenes.

04

Extreme formats

1:4, 4:1, 1:8, and 8:1 are for narrow placements. Mention where the subject and copy area should sit so the composition does not collapse.

Nano Banana 2 prompt templates built around real deliverables

Replace the bracketed fields, keep the business requirement near the start, and remove any detail that does not affect the final image. These templates work as starting points, not magic phrases.

Localized event poster

Use when the wording must appear inside the image in a specific language.

Prompt Design a [ratio] poster for [event]. Display the exact headline '[headline]' and supporting line '[line]'. Use [visual style], high text contrast, and a simple reading order. Keep all other marks abstract and do not invent dates or sponsors.

Working note: Generate one language at a time and proofread every character before use.

Consistent character scene

Use for a new scene while preserving a referenced person's main visual traits.

Prompt Using reference 1 as the character identity, show [character name] [action] in [setting]. Preserve [hair, clothing, and defining features]. Camera: [shot and angle]. Mood: [mood]. Do not add duplicate people or change the outfit colors.

Working note: Reuse the same character name and reference order across the series.

Simple process infographic

Use for an explanatory visual with a small number of clearly ordered steps.

Prompt Create a [ratio] infographic explaining [process] in [number] steps. Use short labels, clear arrows, and one distinct visual per step. Exact title: '[title]'. Palette: [colors]. Keep the background plain and avoid decorative text.

Working note: Verify facts separately; the model should arrange approved content, not be the source of the facts.

How to use Nano Banana 2 on Lovart ME

The same four-step process works for a first draft and for a reference-based edit.

  1. 01

    Choose the input mode

    Use Text to image for a new concept. Switch to Image to image when an existing subject, object, style, or composition must guide the result.

  2. 02

    Write the brief and add references

    Name the deliverable, subject, setting, composition, and constraints. For multiple references, explain the role of each image instead of asking the model to guess.

  3. 03

    Set ratio, resolution, and format

    Match the aspect ratio to the publishing channel. Start at 1K for exploration, then choose 2K or 4K for the approved direction. Select JPG or PNG.

  4. 04

    Generate, inspect, and refine

    Check subject identity, hands, small objects, typography, and edge details. Change one or two instructions at a time so you can tell which revision improved the image.

Nano Banana 2 questions

Answers reflect Google’s published model information and the options currently available in this Lovart ME workflow.

What is Nano Banana 2?

Nano Banana 2 is the product name for Google’s Gemini 3.1 Flash Image model. It is designed for fast image generation and editing, with support for detailed instructions, image references, text rendering, and multiple output formats.

Can I edit an existing photo?

Yes. Choose Image to image, upload one or more references, and describe what must change and what must stay fixed. Results still need review, especially for identity, text, and small details.

How many reference images can I upload?

The current Nano Banana 2 workflow supports up to 14 JPEG, PNG, or WebP reference images. Use only references that have a clear purpose, and describe that purpose in the prompt.

Does Nano Banana 2 support 4K images?

Yes. Lovart ME offers 1K, 2K, and 4K output for this model. Higher resolutions use more credits, so 1K is usually better for testing and 4K for an approved final direction.

Which aspect ratios are available?

You can use Auto plus 1:1, 2:3, 3:2, 1:4, 4:1, 3:4, 4:3, 4:5, 5:4, 1:8, 8:1, 9:16, 16:9, and 21:9.

Can it generate accurate text inside an image?

Google highlights improved text rendering and in-image translation. For production work, provide the exact copy in quotation marks, keep the layout simple, and proofread every word before publishing.

Is Nano Banana 2 free on Lovart ME?

New accounts may use included registration credits to try generation. Each job consumes credits according to the selected resolution; the live controls show the current cost before you generate.

Can I use the output commercially?

Usage depends on the platform terms, your source materials, and local law. Make sure you have rights to uploaded references and review current Lovart ME terms before using an image in commercial work.