> ## Documentation Index
> Fetch the complete documentation index at: https://docs.oxen.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Nano Banana

> On-device photorealistic image generation

<CardGroup cols={1}>
  <Card title="Try Nano Banana in the Workbench" icon="flask" href="https://www.oxen.ai/ai/workbench?model=nano-banana">
    Run this model interactively, tune parameters, and compare outputs.
  </Card>
</CardGroup>

**Model ID:** `nano-banana`

nano-banana is an image generation model (sometimes referred to as Gemini 2.5 Flash Image) that excels in efficient on-device image synthesis, high prompt adherence, and advanced text rendering within images. It is designed for both speed and quality, enabling image generation at native 1024x1024 resolution while maintaining consistent quality across various aspect ratios and device types.

The model's main strengths are its ability to process and generate photorealistic images with accurate text integration, its efficiency on mobile and cloud hardware, and its strong semantic understanding of prompts. It reliably interprets and renders complex scenes, textual elements, and styles, outperforming previous diffusion models in prompt adherence and visual coherence, especially for applications requiring accurate text in images and mobile deployment.

Some other noteworthy features of nano-banana include mask-free inpainting (editing image regions with natural language rather than pixel masks), layout-aware outpainting (extending images while preserving perspective and lighting), and high style transfer consistency, making it suitable for professional branding, creative workflows, and mobile-first applications.

| Metric             | Value                                                    |
| ------------------ | -------------------------------------------------------- |
| Parameter Count    | 450 million (base); up to 8 billion (enterprise scaling) |
| Mixture of Experts | No                                                       |
| Context Length     | Unknown                                                  |
| Multilingual       | Yes (supports text rendering in multiple languages)      |
| Quantized\*        | Yes                                                      |

\**Quantization is specific to the inference provider and the model may be offered with different quantization levels by other providers.*

## Example request

<Tip>
  Use the [Workbench](https://www.oxen.ai/ai/workbench?model=nano-banana) 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.
</Tip>

<Tabs>
  <Tab title="Sync">
    See the [image editing reference](/inference-api/reference/image_editing) for more details.

    <Tabs>
      <Tab title="Minimal">
        <CodeGroup>
          ```bash cURL theme={null}
          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",
            "prompt": "<prompt>"
          }'
          ```

          ```python Python theme={null}
          import os
          import requests

          response = requests.post(
              "https://hub.oxen.ai/api/ai/images/edit",
              headers={
                  "Content-Type": "application/json",
                  "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
              },
              json={
                  "model": "nano-banana",
                  "prompt": "<prompt>"
              },
          )
          response.raise_for_status()
          print(response.json())
          ```
        </CodeGroup>
      </Tab>

      <Tab title="Basic parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          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",
            "prompt": "<prompt>",
            "input_image": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ]
          }'
          ```

          ```python Python theme={null}
          import os
          import requests

          response = requests.post(
              "https://hub.oxen.ai/api/ai/images/edit",
              headers={
                  "Content-Type": "application/json",
                  "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
              },
              json={
                  "model": "nano-banana",
                  "prompt": "<prompt>",
                  "input_image": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ]
              },
          )
          response.raise_for_status()
          print(response.json())
          ```
        </CodeGroup>
      </Tab>

      <Tab title="All parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          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",
            "prompt": "<prompt>",
            "input_image": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ],
            "aspect_ratio": "16:9"
          }'
          ```

          ```python Python theme={null}
          import os
          import requests

          response = requests.post(
              "https://hub.oxen.ai/api/ai/images/edit",
              headers={
                  "Content-Type": "application/json",
                  "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
              },
              json={
                  "model": "nano-banana",
                  "prompt": "<prompt>",
                  "input_image": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ],
                  "aspect_ratio": "16:9"
              },
          )
          response.raise_for_status()
          print(response.json())
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Tab>

  <Tab title="Async">
    See the [async queue reference](/inference-api/reference/async_queue) for more details.

    <Tabs>
      <Tab title="Minimal">
        <CodeGroup>
          ```bash cURL theme={null}
          # 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",
            "prompt": "<prompt>"
          }' | jq -r '.generations[0].generation_id')

          # Poll until the generation reaches a terminal status.
          while true; do
            STATUS=$(curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
              "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq -r '.status')
            echo "Status: $STATUS"
            case $STATUS in succeeded|failed|cancelled) break;; esac
            sleep 5
          done

          # Print the result.
          curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
            "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq .
          ```

          ```python Python theme={null}
          import os
          import time
          import requests

          HEADERS = {
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          }

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers=HEADERS,
              json={
                  "model": "nano-banana",
                  "prompt": "<prompt>"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          while True:
              data = requests.get(
                  f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
                  headers=HEADERS,
              ).json()
              if data["status"] in {"succeeded", "failed", "cancelled"}:
                  break
              time.sleep(5)

          if data["status"] == "succeeded":
              print(f"Result: {data['result_url']}")
          else:
              print(f"Generation {data['status']}: {data.get('error_message')}")
          ```
        </CodeGroup>
      </Tab>

      <Tab title="Basic parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # 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",
            "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 until the generation reaches a terminal status.
          while true; do
            STATUS=$(curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
              "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq -r '.status')
            echo "Status: $STATUS"
            case $STATUS in succeeded|failed|cancelled) break;; esac
            sleep 5
          done

          # Print the result.
          curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
            "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq .
          ```

          ```python Python theme={null}
          import os
          import time
          import requests

          HEADERS = {
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          }

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers=HEADERS,
              json={
                  "model": "nano-banana",
                  "prompt": "<prompt>",
                  "input_image": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ]
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          while True:
              data = requests.get(
                  f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
                  headers=HEADERS,
              ).json()
              if data["status"] in {"succeeded", "failed", "cancelled"}:
                  break
              time.sleep(5)

          if data["status"] == "succeeded":
              print(f"Result: {data['result_url']}")
          else:
              print(f"Generation {data['status']}: {data.get('error_message')}")
          ```
        </CodeGroup>
      </Tab>

      <Tab title="All parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # 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",
            "prompt": "<prompt>",
            "input_image": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ],
            "aspect_ratio": "16:9"
          }' | jq -r '.generations[0].generation_id')

          # Poll until the generation reaches a terminal status.
          while true; do
            STATUS=$(curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
              "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq -r '.status')
            echo "Status: $STATUS"
            case $STATUS in succeeded|failed|cancelled) break;; esac
            sleep 5
          done

          # Print the result.
          curl -s -H "Authorization: Bearer $OXEN_API_KEY" \
            "https://hub.oxen.ai/api/ai/queue/$GEN_ID" | jq .
          ```

          ```python Python theme={null}
          import os
          import time
          import requests

          HEADERS = {
              "Content-Type": "application/json",
              "Authorization": f"Bearer {os.environ['OXEN_API_KEY']}",
          }

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers=HEADERS,
              json={
                  "model": "nano-banana",
                  "prompt": "<prompt>",
                  "input_image": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ],
                  "aspect_ratio": "16:9"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          while True:
              data = requests.get(
                  f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
                  headers=HEADERS,
              ).json()
              if data["status"] in {"succeeded", "failed", "cancelled"}:
                  break
              time.sleep(5)

          if data["status"] == "succeeded":
              print(f"Result: {data['result_url']}")
          else:
              print(f"Generation {data['status']}: {data.get('error_message')}")
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Tab>

  <Tab title="Async with SSE">
    See the [async queue reference](/inference-api/reference/async_queue) for more details.

    <Tabs>
      <Tab title="Minimal">
        <CodeGroup>
          ```bash cURL theme={null}
          # 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",
            "prompt": "<prompt>"
          }' | 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 .
          ```

          ```python Python theme={null}
          import json
          import os
          import requests

          API_KEY = os.environ["OXEN_API_KEY"]
          AUTH = {"Authorization": f"Bearer {API_KEY}"}

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers={**AUTH, "Content-Type": "application/json"},
              json={
                  "model": "nano-banana",
                  "prompt": "<prompt>"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          with requests.get(
              "https://hub.oxen.ai/api/events",
              headers=AUTH,
              stream=True,
          ) as stream:
              event_name = None
              for line in stream.iter_lines(decode_unicode=True):
                  if line.startswith("event: "):
                      event_name = line.removeprefix("event: ")
                  elif line.startswith("data: ") and event_name == "media_generation_completed":
                      payload = json.loads(line.removeprefix("data: "))
                      if payload.get("generation_id") == generation_id:
                          print(payload)
                          break
          ```
        </CodeGroup>
      </Tab>

      <Tab title="Basic parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # 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",
            "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 .
          ```

          ```python Python theme={null}
          import json
          import os
          import requests

          API_KEY = os.environ["OXEN_API_KEY"]
          AUTH = {"Authorization": f"Bearer {API_KEY}"}

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers={**AUTH, "Content-Type": "application/json"},
              json={
                  "model": "nano-banana",
                  "prompt": "<prompt>",
                  "input_image": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ]
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          with requests.get(
              "https://hub.oxen.ai/api/events",
              headers=AUTH,
              stream=True,
          ) as stream:
              event_name = None
              for line in stream.iter_lines(decode_unicode=True):
                  if line.startswith("event: "):
                      event_name = line.removeprefix("event: ")
                  elif line.startswith("data: ") and event_name == "media_generation_completed":
                      payload = json.loads(line.removeprefix("data: "))
                      if payload.get("generation_id") == generation_id:
                          print(payload)
                          break
          ```
        </CodeGroup>
      </Tab>

      <Tab title="All parameters">
        <CodeGroup>
          ```bash cURL theme={null}
          # 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",
            "prompt": "<prompt>",
            "input_image": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ],
            "aspect_ratio": "16:9"
          }' | 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 .
          ```

          ```python Python theme={null}
          import json
          import os
          import requests

          API_KEY = os.environ["OXEN_API_KEY"]
          AUTH = {"Authorization": f"Bearer {API_KEY}"}

          enqueue = requests.post(
              "https://hub.oxen.ai/api/ai/queue",
              headers={**AUTH, "Content-Type": "application/json"},
              json={
                  "model": "nano-banana",
                  "prompt": "<prompt>",
                  "input_image": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ],
                  "aspect_ratio": "16:9"
              },
          )
          enqueue.raise_for_status()
          generation_id = enqueue.json()["generations"][0]["generation_id"]

          with requests.get(
              "https://hub.oxen.ai/api/events",
              headers=AUTH,
              stream=True,
          ) as stream:
              event_name = None
              for line in stream.iter_lines(decode_unicode=True):
                  if line.startswith("event: "):
                      event_name = line.removeprefix("event: ")
                  elif line.startswith("data: ") and event_name == "media_generation_completed":
                      payload = json.loads(line.removeprefix("data: "))
                      if payload.get("generation_id") == generation_id:
                          print(payload)
                          break
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Tab>
</Tabs>

## Fetch model details

The [models endpoint](/inference-api/reference/models/overview) returns the full model object, including its `json_request_schema`.

```bash theme={null}
curl -H "Authorization: Bearer $OXEN_API_KEY" https://hub.oxen.ai/api/ai/models/nano-banana
```

## 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. Use @Image1, @Image2, etc. to reference the input images. |

### Optional parameters

| Field          | Type            | Default  | Description                                                                                                                                |
| -------------- | --------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
| `input_image`  | `array<string>` | —        | Optional reference image(s) to edit. Leave empty to generate from the prompt alone. Reference them in the prompt as @Image1, @Image2, etc. |
| `aspect_ratio` | `string`        | `"16:9"` | Aspect ratio for the generated image One of: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3.                                                          |