Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)

gemini-3.1-flash-lite-image

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is Google's fastest and most cost-efficient multimodal image generation model, designed for high-throughput visual workflows and real-time applications. It supports text-to-image generation, image editing, and multi-image composition through a unified API, while also producing text outputs alongside images. Delivering image generation in approximately 4 seconds, it combines fast inference with strong character consistency, precise editing, and real-world knowledge. The model generates 1K-resolution images across 14 aspect ratios and embeds an invisible SynthID watermark in all outputs. Optimized for the best balance of quality, speed, and cost, Nano Banana 2 Lite is ideal for prototyping, developer pipelines, and large-scale visual content generation.

Context: 66K tokens
Endpoint

Pricing

Pay Per Request

Request$0.0336 / request

BillingPay Per Request

Cache Write (5m)Not applicable

Cache Write (1h)Not applicable

Cache ReadNot applicable

Quick Start

Select an endpoint and copy a working example for this model.

Endpoint

python

from openai import OpenAI client = OpenAI(    api_key="YOUR_API_KEY",    base_url="https://api.apertis.ai/v1") response = client.chat.completions.create(    model="gemini-3.1-flash-lite-image",    messages=[        {"role": "user", "content": "Hello!"}    ],    max_tokens=1024,    temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(#     model="gemini-3.1-flash-lite-image",#     messages=[{"role": "user", "content": "Hello!"}],#     extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )

Supported Parameters

API docs

Common5 params

modelpromptsizequalityresponse_format

Extended4 params

nstylebackgroundoutput_format

Cursor IDE Model IDs

Use these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.

gemini-3.1-flash-lite-image

Questions about Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)

How much does Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) cost on Apertis?

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) costs $0.0336 per request on Apertis.

What is Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)'s context window?

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) has a context window of 66K tokens.

Which company develops Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)?

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) is developed by Google.

Which model ID do I use to call Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image)?

Use the model ID gemini-3.1-flash-lite-image to call Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image).

Compare with Other Models

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Gemini 4 Hydrogen is Google's high-efficiency multimodal model in the Gemini 4 family, optimized for high-throughput agentic workflows, coding, and multi-model routing. It delivers strong performance at lower cost and latency than Gemini 4 Carbon, supporting text, image, audio, video, and file inputs for versatile multimodal applications. Designed for scalable production workloads and long-horizon execution, Gemini 4 Hydrogen supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high, and xhigh) to balance reasoning depth, speed, and cost. It is well suited for coding assistants, autonomous agents, complex workflow automation, and large-scale AI systems.

Context: 1M
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Output: $7.50/M

Gemini 4 Carbon

Gemini 4 Carbon is Google's frontier multimodal reasoning model, designed for advanced coding, agentic workflows, and complex multi-step problem solving. It supports text, image, audio, video, and file inputs, enabling integrated reasoning and analysis across diverse modalities. Optimized for long-horizon execution and demanding professional workloads, Gemini 4 Carbon supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high) to balance reasoning depth, latency, and cost. It is well suited for autonomous agents, software engineering, multimodal analysis, and large-scale workflow automation.

Context: 1M
Input: $2.00/M
Output: $10.00/M

Gemini Nano Banana 2.1 (Google AI Studio)

Gemini Nano Banana 2.1 served from Google AI Studio. Billed per image at US$0.0336 (up to 1K).

Context: N/A
Input: — (Not priced per input token)
Output: — (Not priced per output token)

Gemini 4 Argon

Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.

Context: 1M
Input: $2.00/M
Output: $10.00/M