GPT Image 2.5 Flare

Try GPT Image 2.5 Flare in the Workbench

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

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

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
Basic parameters
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": "gpt-image-2-5-flare",
  "prompt": "<prompt>"
}'

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())

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"
  ]
}'

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())

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"
}'

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())

See the async queue reference for more details.

Minimal
Basic parameters
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": "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 .

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')}")

# 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 .

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')}")

# 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 .

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')}")

See the async queue reference for more details.

Minimal
Basic parameters
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": "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 .

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

# 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 .

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

# 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 .

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

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/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.

Try GPT Image 2.5 Flare 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