Google Nano Banana Edit API Documentation

Google Nano Banana Edit API Documentation

Playground

Nano-Banana is an advanced image generation and editing model that produces photorealistic or stylized visuals and performs precise inpainting, outpainting, and background replacement. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Nano-Banana Edit is Google’s advanced AI-powered image editing and generation model, designed to make visual transformation as intuitive as describing it in words. Built on Google’s cutting-edge computer vision and generative research, it combines precision, flexibility, and semantic awareness for professional-grade editing.

Try the New Version of Nano Banana!

• Nano Banana Pro
• Nano Banana Pro edit
• Nano Banana Pro Ultra
• Nano Banana Pro Edit Ultra
• Nano Banana Pro Multi

🌟 Why it stands out

• Natural Language Editing Modify images using simple text instructions — no masking, layering, or manual tools required.
• Context-Aware Understanding Accurately interprets scene structure, spatial relationships, and object semantics for realistic results.
• Style and Tone Preservation Keeps lighting, shadows, and texture consistent with the original image while applying changes seamlessly.
• High Precision Control Excels at fine-grained edits such as color adjustments, object replacement, or composition shifts with minimal distortion.
• Creative Versatility Suitable for concept art, photography, advertising design, and everyday content creation.

⚙️ How to use

• Input: existing image + text prompt

• Output: edited image (JPEG/PNG/WEBP)

• Size: 1:1, 4:3, 16:9, 21:9, and so on.

• Supports style transfer, relighting, background replacement, and object modification

• Works with natural prompts like:

• “Replace the cloudy sky with a clear sunset.”

• “Add soft studio lighting and a modern background.”

• “Turn the model’s outfit into a formal business suit.”

💰 Pricing

• $0.038 per image

• Commercial use allowed

💡 Best Use Cases

• Marketing & Branding — Update campaign visuals without reshooting.
• Product Photography — Adjust materials, lighting, or layout instantly.
• Social Media & Content Creation — Generate multiple variations with minimal effort.
• Artistic Design — Experiment with colors, styles, and compositions effortlessly.

📝 Notes

Please ensure your prompts comply with Google’s Safety Guidelines. If an error occurs, review your prompt for restricted content, adjust it, and try again.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "images": [
    "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
  ],
  "aspect_ratio": "1:1",
  "output_format": "png"
}
JSON
)

# 1. Submit the prediction once. Never retry this request automatically:
# a retry after an unclear failure can create a second, billed task.
CHECK='The task may already exist. Check History or the predictions list before submitting again.'
if ! SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --connect-timeout 10 --max-time 60 \
  -X POST "https://api.wavespeed.ai/api/v3/google/nano-banana/edit" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}"); then
  printf 'Submit failed. %s\n' "${CHECK}" >&2
  exit 1
fi

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

# 2. Poll until the prediction reaches a final status.
BODY_FILE=$(mktemp)
trap 'rm -f "${BODY_FILE}"' EXIT
while true; do
  # Transient errors (429, 5xx) are retried, honoring Retry-After.
  HTTP_CODE=$(curl --silent --show-error --fail-with-body \
    --connect-timeout 10 --max-time 60 --retry 5 --retry-delay 2 \
    --output "${BODY_FILE}" --write-out '%{http_code}' \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}" || true)
  case "${HTTP_CODE}" in
    2??) ;;
    000|429|5??)  # dropped connection or temporary error: keep polling
      printf 'Task %s: HTTP %s, polling again in 10s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      sleep 10; continue ;;
    *) printf 'Task %s: HTTP %s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      cat "${BODY_FILE}" >&2; exit 1 ;;
  esac
  RESULT=$(jq 'if type == "object" and has("data") then .data else . end' "${BODY_FILE}")
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted)
      printf 'Task %s ended with status %s\n' "${PREDICTION_ID}" "${STATUS}" >&2
      printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Every model also accepts the global request options enable_sync_mode and enable_base64_output; see their pages for details.

Response Parameters

Result Request Parameters

Result Response Parameters