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Image·2026年7月1日·更新于 2026年7月2日·6 min read

Nano Banana API — call Google's image models OpenAI-compatibly at half the price

Nano Banana is Google's image model family. Here's how to call it through an OpenAI-compatible API — text-to-image, image edit, per-model pricing at roughly half of list, on one key.

Nano Banana is Google's image-generation model family — the model behind Gemini's native image output. Kunavo serves the whole family (nano-banana, nano-banana-2, nano-banana-pro) through the OpenAI-compatible images endpoint, at roughly half of Google's list price, on one bearer token and one Stripe balance. If your code can call the OpenAI images API, it can call Nano Banana by changing only the base_url.

Call the Nano Banana API

Generate a key at /app/keys, keep the OpenAI SDK, and point base_url at Kunavo. Text-to-image is POST /v1/images/generations:

nano_banana.py
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["KUNAVO_API_KEY"],
    base_url="https://api.kunavo.com/v1",
)

img = client.images.generate(
    model="nano-banana",
    prompt="A neon ramen stall in the rain, cinematic, 35mm",
    size="1024x1024",
)
print(img.data[0].url)  # temporary URL (~24h) — download and re-host

Returned URLs are temporary (~24h) — download and re-host on your own CDN. Full parameters (size, resolution, quality, async + webhooks) are in the images API reference.

Models and pricing

Per-image rates below are about half of Google's official list. Live rates are on each model page.

ModelKunavo / imageOfficialBest for
nano-banana~$0.027$0.039Fast, cheap, everyday generation
nano-banana-2from $0.047$0.067Better fidelity; 1K / 2K / 4K tiers
nano-banana-profrom $0.067$0.134Top-tier fidelity, text-in-image
gpt-image-2~$0.063$0.127OpenAI alternative, prompt fidelity

Nano Banana Pro API

Nano Banana Pro is the premium tier — the pick when output quality is the product: hero images, posters, ads, and anything with text rendered inside the image, where Pro is clearly ahead of the base models. The call is identical to the example above with model="nano-banana-pro"; resolution tiers (1K/2K/4K) price separately, from about $0.067 per image against Google's ~$0.134 list — live rates on the nano-banana-pro model page. For volume drafts, generate with nano-banana first and re-render the winners with Pro; the two share prompts cleanly.

Edit an image (image-to-image)

POST /v1/images/edits takes a prompt plus a source image — an https URL or a data: base64 URI, and returns the edited result. Use nano-banana-edit for Nano Banana image-to-image.

edit.sh
# Image-to-image: pass a source image URL (or a data: base64 URI)
curl https://api.kunavo.com/v1/images/edits \
  -H "Authorization: Bearer $KUNAVO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nano-banana-edit",
    "prompt": "make the sky golden hour, keep the subject",
    "image": "https://example.com/source.png"
  }'

When to use which

  • nano-banana — highest volume at the lowest cost; thumbnails, variations, drafts.
  • nano-banana-2 — the default when fidelity matters and you want resolution tiers.
  • nano-banana-pro — hero images, posters and anything with text baked into the image.
  • For the full multimodal picture — image → video → voiceover pipelines — see the multimodal AI guide.

FAQ

What is the Nano Banana API?

Google's image model family, served on Kunavo's OpenAI-compatible /v1/images/generations endpoint at about half of list price.

How do I get a Nano Banana API key?

Sign up, create a key at /app/keys, and set base_url=https://api.kunavo.com/v1 — no Google Cloud project required. See the quickstart.

How much does it cost?

About $0.027 per image for nano-banana, scaling up to nano-banana-pro — roughly half of Google's list, billed per image.

What is the Nano Banana Pro API?

The premium tier — top fidelity and text-in-image. Same endpoint, model="nano-banana-pro", from ~$0.067/image (vs ~$0.134 list).

Can I edit images, not just generate them?

Yes — POST /v1/images/edits with a source image does image-to-image. Details in the images reference.