Google Nano Banana 2 Edit (Gemini 3.1 Flash Image) enables advanced image editing with 4K-capable output, fast iteration, and precise instruction following. Supports text translation, localization within images, and maintains subject consistency during edits. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Boşta

$0.07çalıştırma başına·~14 / $1

Keep the dancer exactly as-is. Replace background with a neon-lit Tokyo street at night — wet pavement reflecting pink and blue light, blurred pedestrians, Japanese signage. Same camera angle and perspective. Maintain dancer pose and clothing. Change environment to an empty rooftop at golden hour, city skyline behind him, warm orange backlight creating a rim light effect around his silhouette.
Nano Banana 2 Edit (Gemini 3.1 Flash Image) 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.
Natural language editing Modify images using simple text instructions — the model understands context and relationships.
Multi-image reference Upload up to 14 reference images for complex edits and compositions.
Multi-resolution support Output in 1K, 2K, or 4K resolution based on your needs.
Flexible aspect ratios Multiple options including 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9, 1:4, 4:1, 1:8, and 8:1.
Prompt Enhancer Built-in tool to automatically improve your edit descriptions.
Format choice Export in PNG or JPEG format.
| Parameter | Required | Description |
|---|---|---|
| images | Yes | Reference images to edit (max: 14, click "+ Add Item" to add more) |
| prompt | Yes | Text description of the desired edit |
| aspect_ratio | No | Aspect ratio: 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9, 1:4, 4:1, 1:8, 8:1 |
| resolution | No | Output resolution: 0.5k, 1k (default), 2k, 4k |
| enable_web_search | No | Enable web search to enhance generation with real-time info (default: false) |
| enable_image_search | No | Enable image search to enhance generation with real-time info (default: false) |
| output_format | No | Output format: png (default), jpeg |
| Resolution | Cost |
|---|---|
| 0.5k | $0.045 |
| 1k | $0.07 |
| 2k | $0.105 |
| 4k | $0.14 |
| Web search | +$0.014 |
| Image search | +$0.014 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/google/nano-banana-2/edit with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Nano Banana 2 Edit below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/google/nano-banana-2/edit" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "1:1",
"resolution": "1k",
"enable_web_search": false,
"enable_image_search": false,
"output_format": "png",
"enable_sync_mode": false,
"enable_base64_output": false
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("google/nano-banana-2/edit", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "1:1",
"resolution": "1k",
"enable_web_search": false,
"enable_image_search": false,
"output_format": "png",
"enable_sync_mode": false,
"enable_base64_output": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"google/nano-banana-2/edit",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"aspect_ratio": "1:1",
"resolution": "1k",
"enable_web_search": false,
"enable_image_search": false,
"output_format": "png",
"enable_sync_mode": false,
"enable_base64_output": false
}
)
print(output["outputs"][0]) # → URL of the generated outputNano Banana 2 Edit is a Google model for image editing, exposed as a REST API on WaveSpeedAI. Google Nano Banana 2 Edit (Gemini 3.1 Flash Image) enables advanced image editing with 4K-capable output, fast iteration, and precise instruction following. Supports text translation, localization within images, and maintains subject consistency during edits. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
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 prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/google/google-nano-banana-2-edit.
Nano Banana 2 Edit starts at $0.070 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.
Key inputs: `prompt`, `images`, `aspect_ratio`, `resolution`, `enable_base64_output`, `enable_image_search`. 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-edit.
Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.
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.