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Google Nano Banana Lite Text to Image API

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Google Nano Banana 2 Lite Text to Image generates high-quality images from text prompts with low latency, flexible aspect ratios, and fast image creation for creative and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

text-to-image
Input

Idle

A foreign astronaut floating inside a damaged spacecraft cabin, red emergency lights flashing, Earth visible through a cracked window, loose objects drifting around him, microphone near his mouth, helmet visor reflecting warning screens, claustrophobic sci-fi composition, emotional final-message storytelling, cinematic realism

$0.04per run·~25 / $1

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ExamplesView all

A foreign astronaut floating inside a damaged spacecraft cabin, red emergency lights flashing, Earth visible through a cracked window, loose objects drifting around him, microphone near his mouth, helmet visor reflecting warning screens, claustrophobic sci-fi composition, emotional final-message storytelling, cinematic realism

A foreign astronaut floating inside a damaged spacecraft cabin, red emergency lights flashing, Earth visible through a cracked window, loose objects drifting around him, microphone near his mouth, helmet visor reflecting warning screens, claustrophobic sci-fi composition, emotional final-message storytelling, cinematic realism

Related Models

README

Google Nano Banana 2 Lite Text-to-Image

Google Nano Banana 2 Lite Text-to-Image generates images from text prompts with a fast, lightweight image model. The public interface keeps the workflow simple: write a prompt, choose an aspect ratio, select an output format, and generate a single image result.

Why Choose This?

  • Fast text-to-image generation
    Generate images quickly from natural-language prompts.

  • Flexible aspect ratios
    Choose common square, portrait, landscape, and wide-format aspect ratio presets.

  • Simple generation controls
    The public form focuses on prompt, size, and output_format.

  • Single-image output
    Each request generates one image for predictable cost and behavior.

  • Standard image output
    Generated images are returned as URLs in the standard WaveSpeed prediction response.

Parameters

ParameterRequiredDescription
promptYesText prompt describing the image to generate.
aspect_ratioNoOutput aspect ratio preset. Default: 1:1.
output_formatNoOutput image format: png or jpeg. Default: png.
enable_sync_modeNoWait for the result to be generated and uploaded before returning the response. API only. Synchronous requests may hit timeouts because Google inference time can fluctuate. Default: false.
enable_base64_outputNoReturn output as a BASE64 string instead of a URL. API only. Default: false.

How to Use

  1. Write your prompt — Describe the subject, scene, style, lighting, and composition.
  2. Choose aspect ratio — Select the output size based on your target layout.
  3. Choose output format — Use png or jpeg depending on your workflow.
  4. Submit — Generate the image and retrieve the output URL.

Pricing

Output ImagesPrice
1$0.04

Best Use Cases

  • Creative image generation — Generate concept art, illustrations, thumbnails, and visual ideas from text.
  • Marketing assets — Create campaign images, social visuals, blog graphics, and promotional content.
  • Prompt testing — Quickly iterate on prompt wording, style direction, and composition.
  • Layout-specific generation — Generate square, portrait, landscape, or banner-style images for different use cases.

Pro Tips

  • Use clear prompts with subject, scene, lighting, style, and composition.
  • Keep the prompt focused on the main subject and visual intent.
  • Use png for higher-quality general output.
  • Use jpeg for smaller file sizes.
  • Choose the aspect ratio based on the final placement, such as square, portrait, landscape, or wide banner.
Note:This website uses AI models provided by third parties.

Nano Banana 2 Lite Text To Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/google/nano-banana-2-lite/text-to-image with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Nano Banana 2 Lite Text To Image below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "aspect_ratio": "1:1",
    "output_format": "png"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/google/nano-banana-2-lite/text-to-image" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/google/nano-banana-2-lite/text-to-image";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "1:1",
        "output_format": "png"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "aspect_ratio": "1:1",
    "output_format": "png"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/google/nano-banana-2-lite/text-to-image", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Nano Banana 2 Lite Text To Image API — Frequently asked questions

What is the Nano Banana 2 Lite Text To Image API?

Nano Banana 2 Lite Text To Image is a Google model for image generation, exposed as a REST API on WaveSpeedAI. Google Nano Banana 2 Lite Text to Image generates high-quality images from text prompts with low latency, flexible aspect ratios, and fast image creation for creative and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Nano Banana 2 Lite Text To Image API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/google/google-nano-banana-2-lite-text-to-image.

How much does Nano Banana 2 Lite Text To Image cost per run?

Nano Banana 2 Lite Text To Image starts at $0.040 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Nano Banana 2 Lite Text To Image accept?

Key inputs: `prompt`, `aspect_ratio`, `enable_base64_output`, `enable_sync_mode`, `output_format`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/google/google-nano-banana-2-lite-text-to-image.

How long does Nano Banana 2 Lite Text To Image take to generate?

Median end-to-end generation time on WaveSpeedAI is around 22 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Nano Banana 2 Lite Text To Image outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Google). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Google Nano Banana Lite Text to Image API | WaveSpeedAI