GPT Image 2 Edit

Try GPT Image 2 Edit in the Workbench

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

Model ID: gpt-image-2-edit GPT Image 2 Edit is OpenAI’s image editing model available through Fal. It transforms one or more reference images using a text prompt, supporting multi-image composition and accurate preservation of subject identity, text, and layout. Ideal for photo modifications, style transfer, composition changes, and product mockups.

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": "gpt-image-2-edit",
  "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
  "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-edit",
        "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
        "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-edit",
  "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ],
  "resolution": "1024x1024",
  "quality": "high",
  "num_images": 1,
  "output_format": "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-edit",
        "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
        "input_image": [
            "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
        ],
        "resolution": "1024x1024",
        "quality": "high",
        "num_images": 1,
        "output_format": "png"
    },
)
response.raise_for_status()
print(response.json())

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": "gpt-image-2-edit",
  "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
  "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."

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-edit",
        "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
        "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:
    resp = requests.get(
        f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
        headers=HEADERS,
    )
    if resp.status_code == 404:
        break
    time.sleep(5)
print("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": "gpt-image-2-edit",
  "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ],
  "resolution": "1024x1024",
  "quality": "high",
  "num_images": 1,
  "output_format": "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."

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-edit",
        "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
        "input_image": [
            "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
        ],
        "resolution": "1024x1024",
        "quality": "high",
        "num_images": 1,
        "output_format": "png"
    },
)
enqueue.raise_for_status()
generation_id = enqueue.json()["generations"][0]["generation_id"]

while True:
    resp = requests.get(
        f"https://hub.oxen.ai/api/ai/queue/{generation_id}",
        headers=HEADERS,
    )
    if resp.status_code == 404:
        break
    time.sleep(5)
print("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": "gpt-image-2-edit",
  "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
  "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-edit",
        "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
        "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-edit",
  "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ],
  "resolution": "1024x1024",
  "quality": "high",
  "num_images": 1,
  "output_format": "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-edit",
        "prompt": "Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting.",
        "input_image": [
            "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
        ],
        "resolution": "1024x1024",
        "quality": "high",
        "num_images": 1,
        "output_format": "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

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-edit

Request parameters

Required parameters

Field	Type	Default	Description
`prompt`	`string`	`"Place the subject on the surface of the moon with Earth rising in the background, photorealistic, cinematic lighting."`	Text description of how to edit the input image(s).
`input_image`	`array<string>`	—	One or more reference images to transform. Multiple URLs are composed together by the model.

Optional parameters

Field	Type	Default	Description
`resolution`	`string`	`"1024x1024"`	Output image resolution. HD sizes (1920x1080 and lower) bill at the standard tier; QHD+ sizes (2560x1440 and higher) bill at the high-resolution tier. One of: 1024x768, 1024x1024, 1024x1536, 1920x1080, 2560x1440, 3840x2160.
`quality`	`string`	`"high"`	Output quality tier. Locked to high for best fidelity. One of: high.
`num_images`	`integer`	`1`	Number of images to generate per request. Range: 1 – 4.
`output_format`	`string`	`"png"`	File format for the generated image. One of: png, jpeg, webp.
`mask_url`	`string`	—	Optional mask image URL. White pixels mark regions to edit; black pixels are preserved. Leave empty to edit the whole image. Format: uri.

Try GPT Image 2 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