Nano Banana 2 - Image Edit

Try Nano Banana 2 - Image Edit in the Workbench

Run this model interactively, tune parameters, and compare outputs.

Model ID: nano-banana-2-edit Gemini 2.5 Flash Image (aka nano-banana), is a state-of-the-art image generation and editing model capable of blending multiple images into a single image, maintaining character consistency for storytelling, making targeted transformations with natural language prompts (e.g., blurring backgrounds, removing objects, altering poses, colorizing B&W photos), and using Gemini’s world knowledge for semantic understanding of real-world scenarios. It excels at visual templates for applications like real estate, badges, product mockups, multi-image fusion (e.g., placing objects in scenes, restyling rooms), and interactive educational tools. The model includes SynthID watermarking for AI-generated content identification.

Example request

Use the Workbench as a request builder: configure parameters for this model in the UI, then open the API tab to copy the exact cURL or Python call.

Sync
Async
Async with SSE

See the image editing reference for more details.

Minimal
All parameters

curl -X POST https://hub.oxen.ai/api/ai/images/edit \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "nano-banana-2-edit",
  "prompt": "<prompt>",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ]
}'

curl -X POST https://hub.oxen.ai/api/ai/images/edit \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "nano-banana-2-edit",
  "prompt": "<prompt>",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ],
  "aspect_ratio": "auto",
  "resolution": "2K",
  "enable_web_search": true,
  "safety_tolerance": "6"
}'

See the async queue reference for more details.

Minimal
All parameters

# Enqueue, capture the generation id.
GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "nano-banana-2-edit",
  "prompt": "<prompt>",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ]
}' | jq -r '.generations[0].generation_id')

# Poll the single generation until it 404s (terminal state).
while curl -s -o /dev/null -w "%{http_code}" \
    -H "Authorization: Bearer $OXEN_API_KEY" \
    "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | grep -q "^200$"; do
  sleep 5
done
echo "Done. See the 'Async with SSE' tab to receive the result URL."

# Enqueue, capture the generation id.
GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "nano-banana-2-edit",
  "prompt": "<prompt>",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ],
  "aspect_ratio": "auto",
  "resolution": "2K",
  "enable_web_search": true,
  "safety_tolerance": "6"
}' | jq -r '.generations[0].generation_id')

# Poll the single generation until it 404s (terminal state).
while curl -s -o /dev/null -w "%{http_code}" \
    -H "Authorization: Bearer $OXEN_API_KEY" \
    "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | grep -q "^200$"; do
  sleep 5
done
echo "Done. See the 'Async with SSE' tab to receive the result URL."

See the async queue reference for more details.

Minimal
All parameters

# Enqueue, capture the generation id.
GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "nano-banana-2-edit",
  "prompt": "<prompt>",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ]
}' | jq -r '.generations[0].generation_id')

# Stream the SSE channel, grab the data line that follows a
# media_generation_completed event for our id, and pretty-print it.
curl -sN -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/events \
  | awk -v id="$GEN_ID" '
    /^event: media_generation_completed$/ { expect=1; next }
    /^data: / && expect {
      payload = substr($0, 7)
      if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit }
      expect = 0
    }
  ' | jq .

# Enqueue, capture the generation id.
GEN_ID=$(curl -s -X POST https://hub.oxen.ai/api/ai/queue \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "nano-banana-2-edit",
  "prompt": "<prompt>",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ],
  "aspect_ratio": "auto",
  "resolution": "2K",
  "enable_web_search": true,
  "safety_tolerance": "6"
}' | jq -r '.generations[0].generation_id')

# Stream the SSE channel, grab the data line that follows a
# media_generation_completed event for our id, and pretty-print it.
curl -sN -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/events \
  | awk -v id="$GEN_ID" '
    /^event: media_generation_completed$/ { expect=1; next }
    /^data: / && expect {
      payload = substr($0, 7)
      if (index(payload, "\"generation_id\":\"" id "\"")) { print payload; exit }
      expect = 0
    }
  ' | jq .

Fetch model details

The models endpoint returns the full model object, including its json_request_schema.

curl -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/ai/models/nano-banana-2-edit

Request parameters

Required parameters

Field	Type	Default	Description
`prompt`	`string`	—	Text description of what you want to generate, or the instruction on how to edit the given image.
`input_image`	`array<string>`	—	Input images to transform or use as reference (supports multiple image urls)

Optional parameters

Field	Type	Default	Description
`aspect_ratio`	`string`	`"auto"`	Aspect ratio for the generated image One of: auto, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 4:5, 5:4, 21:9, 4:1, 1:4, 8:1, 1:8.
`resolution`	`string`	`"2K"`	Resolution of the generated image One of: 1K, 2K, 4K.
`enable_web_search`	`boolean`	`true`	Enable web search for the image generation task. This will allow the model to use the latest information from the web to generate the image.
`safety_tolerance`	`string`	`"6"`	The safety tolerance level for content moderation. 1 is the most strict (blocks most content), 6 is the least strict. Default value: 4 One of: 1, 2, 3, 4, 5, 6.

Inference API

Try Nano Banana 2 - Image Edit in the Workbench

​Example request

​Fetch model details

​Request parameters

​Required parameters

​Optional parameters

Example request

Fetch model details

Request parameters

Required parameters

Optional parameters