Nano Banana Pro
Nano Banana Pro (also known as Nano Banana 2) is a Gemini 3 Pro Image Preview model for controlled visual creation. It improves reasoning over lighting and camera angle. It supports high resolution output and multi image blending for production ready design workflows and creative tools.
API Options
Platform-level options for task execution and delivery.
-
taskType
string required value: imageInference -
Identifier for the type of task being performed
-
taskUUID
string required UUID v4 -
UUID v4 identifier for tracking tasks and matching async responses. Must be unique per task.
-
outputType
string default: URL -
Image output type.
Allowed values 3 values
-
outputFormat
string default: JPG -
Specifies the file format of the generated output. The available values depend on the task type and the specific model's capabilities.
- `JPG`: Best for photorealistic images with smaller file sizes (no transparency).
- `PNG`: Lossless compression, supports high quality and transparency (alpha channel).
- `WEBP`: Modern format providing superior compression and transparency support.
**Transparency**: If you are using features like background removal or LayerDiffuse that require transparency, you must select a format that supports an alpha channel (e.g., `PNG`, `WEBP`, `TIFF`). `JPG` does not support transparency.Allowed values 3 values
-
outputQuality
integer min: 20 max: 99 default: 95 -
Compression quality of the output. Higher values preserve quality but increase file size.
-
webhookURL
string URI -
Specifies a webhook URL where JSON responses will be sent via HTTP POST when generation tasks complete. For batch requests with multiple results, each completed item triggers a separate webhook call as it becomes available.
Learn more 1 resource
- Webhooks PLATFORM
- Webhooks
-
deliveryMethod
string default: sync -
Determines how the API delivers task results.
Allowed values 2 values
- Returns complete results directly in the API response.
- Returns an immediate acknowledgment with the task UUID. Poll for results using getResponse.
Learn more 1 resource
- Task Polling PLATFORM
-
uploadEndpoint
string URI -
Specifies a URL where the generated content will be automatically uploaded using the HTTP PUT method. The raw binary data of the media file is sent directly as the request body. For secure uploads to cloud storage, use presigned URLs that include temporary authentication credentials.
Common use cases:
- Cloud storage: Upload directly to S3 buckets, Google Cloud Storage, or Azure Blob Storage using presigned URLs.
- CDN integration: Upload to content delivery networks for immediate distribution.
// S3 presigned URL for secure upload https://your-bucket.s3.amazonaws.com/generated/content.mp4?X-Amz-Signature=abc123&X-Amz-Expires=3600 // Google Cloud Storage presigned URL https://storage.googleapis.com/your-bucket/content.jpg?X-Goog-Signature=xyz789 // Custom storage endpoint https://storage.example.com/uploads/generated-image.jpgThe content data will be sent as the request body to the specified URL when generation is complete.
-
safety
object -
Content safety checking configuration for image generation.
Properties 2 properties
-
safety»checkContentcheckContent
boolean default: false -
Enable or disable content safety checking. When enabled, defaults to
fastmode.
-
safety»modemode
string default: none -
Safety checking mode for image generation.
Allowed values 2 values
- Disables checking.
- Performs a single check.
-
-
ttl
integer min: 60 -
Time-to-live (TTL) in seconds for generated content. Only applies when
outputTypeisURL.
-
includeCost
boolean default: false -
Include task cost in the response.
-
numberResults
integer min: 1 max: 20 default: 1 -
Number of results to generate. Each result uses a different seed, producing variations of the same parameters.
Inputs
Input resources for the task (images, audio, etc). These must be nested inside the inputs object.
inputs object.-
inputs»referenceImagesreferenceImages
array of strings min items: 1max items: 14 -
List of reference images (UUID, URL, Data URI, or Base64).
Generation Parameters
Core parameters for controlling the generated content.
-
model
string required value: google:4@2 -
Identifier of the model to use for generation.
Learn more 3 resources
-
positivePrompt
string required min: 3 max: 45000 -
Text prompt describing elements to include in the generated output.
Learn more 2 resources
-
width
integer paired with height -
Width of the generated media in pixels.
Learn more 2 resources
-
height
integer paired with width -
Height of the generated media in pixels.
Learn more 2 resources
-
resolution
string -
Resolution preset for the output. When used with input media, automatically matches the aspect ratio from the input.
Allowed values 3 values
-
seed
integer min: 0 max: 9223372036854776000 -
Random seed for reproducible generation. When not provided, a random seed is generated in the unsigned 32-bit range.
Learn more 1 resource
Settings
Technical parameters to fine-tune the inference process. These must be nested inside the settings object.
settings object.-
settings»systemPromptsystemPrompt
string min: 1 max: 50000 -
System-level instruction that guides the model's behavior and output style across the entire generation.
-
settings»temperaturetemperature
float min: 0 max: 1 step: 0.01 -
Controls randomness in generation. Lower values produce more deterministic outputs, higher values increase variation and creativity.
-
settings»topPtopP
float min: 0 max: 1 step: 0.01 -
Nucleus sampling parameter that controls diversity by limiting the probability mass. Lower values make outputs more focused, higher values increase diversity.
Provider Settings
Parameters specific to this model provider. These must be nested inside the providerSettings.google object.
providerSettings.google object.-
providerSettings»google»safetyTolerancesafetyTolerance
string default: none -
Safety filter tolerance level. Use
offto use Google's defaults.Allowed values 5 values
-
providerSettings»google»webSearchwebSearch
boolean default: false -
Enable live web search grounding to incorporate real-world, up-to-date information into image generation.
Aurora Research Outpost Panorama
{
"taskType": "imageInference",
"taskUUID": "02351264-91e9-47b0-a382-5bd47569be1c",
"model": "google:4@2",
"positivePrompt": "A sweeping ultra-detailed panoramic view of a near-future Arctic research outpost at blue hour, built on dark basalt cliffs above a frozen fjord, glowing modular labs connected by transparent heated walkways, autonomous snow rovers parked near antenna arrays, shimmering green and violet aurora overhead, crisp wind-carved snow textures, realistic atmospheric haze, distant icebreaker ship lights on the horizon, cinematic wide-angle composition from an elevated camera position, precise cold-weather lighting with warm interior contrast, grounded scientific design, photorealistic materials, production-ready concept art, highly coherent architecture, dramatic but believable mood",
"width": 2528,
"height": 1696,
"seed": 63274,
"settings": {
"temperature": 0.72,
"topP": 0.9,
"systemPrompt": "Create a visually coherent, realistic, high-resolution image with strong attention to lighting, camera angle, and physical plausibility."
},
"providerSettings": {
"google": {
"webSearch": true,
"safetyTolerance": "off"
}
}
}{
"taskType": "imageInference",
"taskUUID": "02351264-91e9-47b0-a382-5bd47569be1c",
"imageUUID": "80639e7d-c777-4eb7-a16f-4429253b52b0",
"imageURL": "https://im.runware.ai/image/os/a07d11/ws/3/ii/80639e7d-c777-4eb7-a16f-4429253b52b0.jpg",
"seed": 63274,
"cost": 0.138
}Bioluminescent Library Observatory Interior
{
"taskType": "imageInference",
"taskUUID": "c9215d29-8a43-4f23-958e-c94d9e2d87d6",
"model": "google:4@2",
"positivePrompt": "A grand circular observatory-library built inside a hollow crystal cliff above a moonlit sea, towering bookshelves curving upward into darkness, brass astrolabes suspended from the ceiling, glowing bioluminescent vines threaded through carved stone arches, a massive refracting telescope aimed through an open dome at a sky filled with aurora and unfamiliar constellations. In the foreground, a solitary scholar in a deep teal coat stands at a luminous map table covered in star charts and glass instruments. Cinematic three-quarter camera angle from a slightly elevated viewpoint, strong depth layering, moody atmosphere, precise rim lighting from the dome opening, warm amber lamp light mixing with cool cyan bioluminescence, polished wood, aged parchment, crystal reflections, volumetric dust beams, ultra-detailed environment design, elegant composition, realistic materials, production-ready concept art quality.",
"width": 2528,
"height": 1696,
"seed": 92974,
"settings": {
"temperature": 0.72,
"topP": 0.9,
"systemPrompt": "Create a highly coherent, visually rich image with careful attention to camera placement, mixed lighting, and believable spatial structure."
},
"providerSettings": {
"google": {
"safetyTolerance": "off",
"webSearch": false
}
}
}{
"taskType": "imageInference",
"taskUUID": "c9215d29-8a43-4f23-958e-c94d9e2d87d6",
"imageUUID": "8bc5b8f2-3371-4682-9484-a1abbf93d27c",
"imageURL": "https://im.runware.ai/image/os/a12d13/ws/3/ii/8bc5b8f2-3371-4682-9484-a1abbf93d27c.jpg",
"seed": 92974,
"cost": 0.138
}Bioluminescent Desert Observatory Interior
{
"taskType": "imageInference",
"taskUUID": "23cd75bd-f3ec-41fc-9ff5-941deccc9ad7",
"model": "google:4@2",
"positivePrompt": "A vast retro-futurist observatory carved into a desert mesa at midnight, interior view looking outward through a colossal circular aperture toward dunes under a meteor shower. In the foreground, a polished brass telescope platform surrounded by hanging glass terrariums filled with glowing blue bioluminescent plants, scattered star charts, translucent holographic constellations, and copper instruments. Two small human figures in sand-worn expedition coats stand near the edge for scale. Cinematic three-quarter camera angle from slightly above railing height, strong depth layering, moonlight mixing with warm amber practical lamps, luminous cyan plant glow reflecting on metal surfaces, drifting dust particles, ultra-detailed textures, elegant production-design realism, surreal yet believable architecture, crisp focus, premium concept-art quality.",
"width": 2528,
"height": 1696,
"seed": 20653,
"settings": {
"temperature": 0.72,
"topP": 0.9,
"systemPrompt": "Generate a visually coherent, production-ready image with careful attention to lighting direction, perspective, material realism, and environmental storytelling."
},
"providerSettings": {
"google": {
"safetyTolerance": "off",
"webSearch": false
}
}
}{
"taskType": "imageInference",
"taskUUID": "23cd75bd-f3ec-41fc-9ff5-941deccc9ad7",
"imageUUID": "7347c3b5-6b7c-48ee-966c-427b2cbc5e94",
"imageURL": "https://im.runware.ai/image/os/a09d21/ws/3/ii/7347c3b5-6b7c-48ee-966c-427b2cbc5e94.jpg",
"seed": 20653,
"cost": 0.138
}Surreal Four-Source Fashion Collage
{
"taskType": "imageInference",
"taskUUID": "3b561ab7-e504-43ac-825e-b85bb666ac9b",
"model": "google:4@2",
"positivePrompt": "Create a polished high-fashion editorial composition using all four reference images in a cohesive and believable way. Keep the model as the main subject, place them inside a grand glass greenhouse environment, reinterpret the beetle-wing iridescence as luxurious material accents in the garment, and integrate the reflective twilight water and lantern atmosphere into the floor and background lighting. Camera angle: slightly low and cinematic, medium-wide framing. Lighting should feel intelligently merged: dramatic studio key light on the subject, diffused greenhouse daylight from above, and subtle twilight glow with lantern reflections below. The final image should feel surreal yet premium, like a luxury magazine cover, with rich texture separation, elegant color harmony, and production-ready detail.",
"width": 2528,
"height": 1696,
"seed": 35590,
"settings": {
"temperature": 0.72,
"topP": 0.9
},
"providerSettings": {
"google": {
"safetyTolerance": "off",
"webSearch": false
}
},
"inputs": {
"referenceImages": [
"https://assets.runware.ai/assets/inputs/247e0ba5-a121-42ca-ab71-df1b6927d5da.jpg",
"https://assets.runware.ai/assets/inputs/1a920881-2331-413a-959b-15074c894771.jpg",
"https://assets.runware.ai/assets/inputs/33e88432-5194-4916-8dd5-44ffff0d54e5.jpg",
"https://assets.runware.ai/assets/inputs/1f23dc7b-0daf-49b6-b265-0d94fce8f952.jpg"
]
}
}{
"taskType": "imageInference",
"taskUUID": "3b561ab7-e504-43ac-825e-b85bb666ac9b",
"imageUUID": "cd1af865-c710-4266-81f1-f39d492a56dd",
"imageURL": "https://im.runware.ai/image/os/a07d11/ws/3/ii/cd1af865-c710-4266-81f1-f39d492a56dd.jpg",
"seed": 35590,
"cost": 0.1424
}