> ## 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.

# GPT Image 2.5 Flare

> Fast, high-quality image generation and editing

<CardGroup cols={1}>
  <Card title="Try GPT Image 2.5 Flare in the Workbench" icon="flask" href="https://www.oxen.ai/ai/workbench?model=gpt-image-2-5-flare">
    Run this model interactively, tune parameters, and compare outputs.
  </Card>
</CardGroup>

**Model ID:** `gpt-image-2-5-flare`

GPT Image 2.5 Flare is OpenAI's general-purpose image generation and editing model, the successor to GPT Image 2. It renders images with more natural lighting and richer textures than GPT Image 2 at up to 50% lower latency, preserves subjects from reference photos, and follows editing instructions reliably across repeated edits without degrading earlier ones.

It generates from a text prompt or edits up to 16 reference images, with optional mask-based inpainting, transparent backgrounds, custom dimensions up to 4K (3840x2160), and five quality tiers from low through the new xhigh and max settings. It suits creator and social content, product imagery, visual search, rapid prototyping, and high-volume generation. For edit-heavy workflows that need the tightest control, see GPT Image 2.5 Sunburst.

## Example request

<Tip>
  Use the [Workbench](https://www.oxen.ai/ai/workbench?model=gpt-image-2-5-flare) 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": "gpt-image-2-5-flare",
            "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": "gpt-image-2-5-flare",
                  "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": "gpt-image-2-5-flare",
            "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": "gpt-image-2-5-flare",
                  "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": "gpt-image-2-5-flare",
            "prompt": "<prompt>",
            "input_image": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ],
            "aspect_ratio": "16:9",
            "resolution": "2K",
            "quality": "high",
            "output_format": "png",
            "background": "auto",
            "moderation": "low"
          }'
          ```

          ```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": "gpt-image-2-5-flare",
                  "prompt": "<prompt>",
                  "input_image": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ],
                  "aspect_ratio": "16:9",
                  "resolution": "2K",
                  "quality": "high",
                  "output_format": "png",
                  "background": "auto",
                  "moderation": "low"
              },
          )
          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": "gpt-image-2-5-flare",
            "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": "gpt-image-2-5-flare",
                  "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": "gpt-image-2-5-flare",
            "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": "gpt-image-2-5-flare",
                  "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": "gpt-image-2-5-flare",
            "prompt": "<prompt>",
            "input_image": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ],
            "aspect_ratio": "16:9",
            "resolution": "2K",
            "quality": "high",
            "output_format": "png",
            "background": "auto",
            "moderation": "low"
          }' | 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": "gpt-image-2-5-flare",
                  "prompt": "<prompt>",
                  "input_image": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ],
                  "aspect_ratio": "16:9",
                  "resolution": "2K",
                  "quality": "high",
                  "output_format": "png",
                  "background": "auto",
                  "moderation": "low"
              },
          )
          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": "gpt-image-2-5-flare",
            "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": "gpt-image-2-5-flare",
                  "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": "gpt-image-2-5-flare",
            "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": "gpt-image-2-5-flare",
                  "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": "gpt-image-2-5-flare",
            "prompt": "<prompt>",
            "input_image": [
              "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
            ],
            "aspect_ratio": "16:9",
            "resolution": "2K",
            "quality": "high",
            "output_format": "png",
            "background": "auto",
            "moderation": "low"
          }' | 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": "gpt-image-2-5-flare",
                  "prompt": "<prompt>",
                  "input_image": [
                      "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
                  ],
                  "aspect_ratio": "16:9",
                  "resolution": "2K",
                  "quality": "high",
                  "output_format": "png",
                  "background": "auto",
                  "moderation": "low"
              },
          )
          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/gpt-image-2-5-flare
```

## Request parameters

### Required parameters

| Field    | Type     | Default | Description                                                                                                                                                  |
| -------- | -------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `prompt` | `string` | —       | Text description of the image to generate, or the instruction on how to edit the reference images. 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, up to 16. Leave empty to generate from the prompt alone.                                                                                                                |
| `mask_url`      | `string`        | —        | Optional mask image URL for inpainting. Transparent pixels mark regions to edit; opaque pixels are preserved. Must match the first reference image's size. Leave empty to edit the whole image. Format: uri. |
| `aspect_ratio`  | `string`        | `"16:9"` | Aspect Ratio One of: auto, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 21:9, 9:21.                                                                                                                                  |
| `resolution`    | `string`        | `"2K"`   | Resolution One of: 1K, 2K, 4K.                                                                                                                                                                               |
| `quality`       | `string`        | `"high"` | Output quality tier. Higher tiers render more detail and cost more; xhigh and max are the slowest and most detailed. One of: low, medium, high, xhigh, max.                                                  |
| `output_format` | `string`        | `"png"`  | File format for the generated image. One of: png, jpeg, webp.                                                                                                                                                |
| `background`    | `string`        | `"auto"` | Background of the generated image. 'transparent' requires png or webp output. One of: auto, opaque, transparent.                                                                                             |
| `moderation`    | `string`        | `"low"`  | Content moderation strictness. 'low' is less restrictive than 'auto'; OpenAI still filters all prompts and outputs under its usage policies. One of: low, auto.                                              |