HiAPI
Nano-Banana-2-Lite 详情页 Hero 图:右侧通透玻璃浮卡层叠延展,虹彩分光,名字以发光蚀刻玻璃立体字嵌入,左侧暖奶油光晕留白。

Google

Nano Banana 2 Lite

Nano-Banana-2-Lite

A lightweight, efficiency-focused model in the Google image family, built for low latency and low cost, suited to rapid ideation and high-throughput image generation, and a seamless replacement for the first-generation Nano Banana

Nano-Banana-2-Lite

Try Nano-Banana-2-Lite

Input

Output

image
Fill in the parameters and run — results show up here.

Pricing

Nano-Banana-2-Lite per image

Unit Price $0.033

Positioning Overview

Nano-Banana-2-Lite is an efficiency-oriented lightweight model in Google's image generation series, supporting both text-to-image generation and image editing based on reference images. It prioritizes response speed and invocation cost, making it suitable for developers who need batch image generation and rapid iteration of first drafts; it maintains usable performance in instruction following and character consistency, and can handle multi-size output from concept sketches to marketing images, with fine-tuning as needed.

Key Highlights

  • Unified interface for text-to-image and image editing — The same pipeline can both generate images directly from prompts and accept up to 10 reference images for editing and remixing, reducing workflow switching.
  • Efficiency positioning for high-frequency invocation — Within the series, it prioritizes speed and cost, making it suitable for throughput-sensitive tasks such as batch assets and template-based image generation.
  • Output coverage across 14 aspect ratios — From 1:1, 16:9 to extreme ratios such as 1:8 and 8:1, all can be specified directly, generating in one pass for multiple platform placements.
  • Support for multi-round local iteration — Existing results can be repeatedly modified in local areas, rapidly advancing first drafts to a usable state.

Capability Description

Text-to-image and reference image editing: Passing only a prompt performs text-to-image generation; attaching 1 to 10 reference image URLs switches to editing or remixing. The same interface covers both types of needs, facilitating unified encapsulation in a single pipeline.

Aspect ratio controllable output: aspect_ratio provides 14 values and supports auto automatic selection. Developers can directly lock the ratio according to placement positions, eliminating subsequent cropping and secondary adaptation.

Long prompt input: prompts can be up to 20,000 characters, accommodating fairly complete descriptions of subject, composition, and style, suitable for batch construction of generation requests through template concatenation.

Multi-reference image input: Up to 10 JPEG, PNG, WebP reference images (each no larger than 30MB), usable for editing tasks requiring multi-image context such as style transfer and asset mixing.

Applicable Scenarios

  • Creative teams generating batch concept sketches — Batch generate proposal sketches with short prompts as materials for internal review and direction screening, deciding on refinement investment after seeing the direction.
  • Developers building high-throughput image generation pipelines — Batch generate product or content images using templated prompts, directly stored for on-demand invocation by business systems.
  • Marketing and social media multi-placement images — Specify ratios such as 1:1, 9:16, 16:9 for placement positions, generating finished images in multiple sizes at once, reducing post-processing cropping rework.
  • Multi-round local modification of existing images — Upload reference images and describe changes with prompts, adjusting local details round by round to produce deliverable iterative versions.
  • Cross-image character-consistent series content — Use the same reference image to maintain character and visual identity, batch producing complete sets of illustrations or storyboards with a consistent series look.

Limitations and Selection Advice

As an efficiency-first lightweight model, first drafts of long sentences or complex layout text rendering may require manual adjustment, with simple and clear text instructions being more reliable; for complex layouts and high-precision details, reserve a rework phase. Currently, specific specifications such as resolution limits, concurrency, and quotas are not available and need to be verified independently before integration. If the task requires higher image quality and complex instruction understanding than throughput, choose a higher-tier model in the same series; if it is only batch sketches and rapid iteration, this model is more suitable.

Frequently asked questions

View all FAQs →
  • What is Nano Banana 2 Lite best for?

    A fixed-1K entry route for high-volume drafts, fast iteration, and optional multi-reference remixing.

  • Does Nano Banana 2 Lite accept reference images?

    Yes, up to 10 optional references. Omit them for text-only generation.

  • Which output settings are supported?

    The page exposes 1K and auto, 1:1, 16:9, 9:16, 4:3, 3:4, 8:1, 1:8; use the Playground contract for the final available set.

  • How is Nano Banana 2 Lite billed?

    Billing is per successful generated image. Resolution or quality differences, when present, are reflected by the live page price.

Related Models

View all models →

Same Type