Nano Banana Pro by Google: Examples & Prompts

Kind
post

This page is a Nano Banana Pro capability explorer. The main experience is the selector above. What follows is the technical appendix.

Endpoints

Every example on this page was made with the Pro endpoints above. Nano Banana 2 (Gemini 3.1 Flash Image) is a separate, faster and cheaper model on fal: fal-ai/nano-banana-2 and fal-ai/nano-banana-2/edit.

When Nano Banana Pro is worth it

Minimal Python (text-to-image)

Make sure FAL_KEY is set in your environment.

python - <<'PY'
import urllib.request
import fal_client

result = fal_client.subscribe(
    "fal-ai/nano-banana-pro",
    arguments={
        "prompt": "A minimalist product photo of a tiny banana-shaped robot resting on a matte black pedestal, studio softbox lighting, clean white background, subtle shadow, macro photography.",
        "aspect_ratio": "1:1",
        "num_images": 1,
        "output_format": "png",
        "resolution": "1K",
        "seed": 123,
        "limit_generations": True,
    },
)

url = result["images"][0]["url"]
urllib.request.urlretrieve(url, "nano-banana-pro-product.png")
print("saved nano-banana-pro-product.png")
PY

Minimal Python (background replacement)

python - <<'PY'
import urllib.request
import fal_client

# Run this from the post directory, or update paths if needed.
base_url = fal_client.upload_file("./cover.png")

result = fal_client.subscribe(
    "fal-ai/nano-banana-pro/edit",
    arguments={
        "prompt": "Keep the banana robot unchanged. Replace the background with a deep blue to magenta gradient, add a clean cinematic rim light, preserve the subject details, and keep the macro depth of field.",
        "image_urls": [base_url],
        "num_images": 1,
        "output_format": "png",
        "resolution": "1K",
        "limit_generations": True,
    },
)

url = result["images"][0]["url"]
urllib.request.urlretrieve(url, "nano-banana-edit-pro.png")
print("saved nano-banana-edit-pro.png")
PY

Minimal Python (multi-image edit)

python - <<'PY'
import urllib.request
import fal_client

# Run this from the post directory, or update paths if needed.
subject_url = fal_client.upload_file("./cover.png")
environment_url = fal_client.upload_file("./example-terrarium-empty.png")

result = fal_client.subscribe(
    "fal-ai/nano-banana-pro/edit",
    arguments={
        "prompt": "Use image 1 as the subject and image 2 as the environment. Place the tiny banana robot from image 1 naturally inside the terrarium from image 2. Preserve the robot's design and materials, keep the glass geometry and moss, add soft morning light and realistic reflections, and maintain a premium macro-photography look.",
        "image_urls": [subject_url, environment_url],
        "num_images": 1,
        "output_format": "png",
        "resolution": "1K",
        "limit_generations": True,
    },
)

url = result["images"][0]["url"]
urllib.request.urlretrieve(url, "nano-banana-multi-edit-pro.png")
print("saved nano-banana-multi-edit-pro.png")
PY

References

Other formats for this page:

For everything on the site: JSON Feed (summaries), Sitemap.