FLUX.2 [flex]

Delivers high-quality image generation and editing with advanced text rendering, multi-image reference for style consistency, and precise, JSON-based prompt…

Try FLUX.2 [flex] in the Workbench

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

Model ID: flux-2-flex

FLUX.2 [flex] is an image generation model that excels in high-quality image creation and editing with strong control over text rendering, typographic layout, and precise prompt adherence.

It provides granular control over image generation, allowing users to balance speed, quality, and cost by adjusting inference steps and guidance scale, and supports up to 10 reference images for tasks such as style transfer, compositing, and product continuity.

Some other noteworthy features of FLUX.2 [flex] include:

• Superior text and caption rendering, making it well-suited for infographics, marketing materials, and brand assets.
• JSON-structured prompts for precise compositional control.
• Accurate color reproduction, including support for exact HEX color codes, which is valuable for product visualization.

Metric	Value
Parameter Count	Unknown
Mixture of Experts	Unknown
Context Length	Unknown
Multilingual	No
Quantized*	Yes

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

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

See the image editing reference for more details.

Minimal

cURL

curl -X POST https://hub.oxen.ai/api/ai/images/edit \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "flux-2-flex",
  "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don'\''t include its arms or legs in the painting.",
  "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": "flux-2-flex",
        "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don't include its arms or legs in the painting.",
        "input_image": [
            "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
        ]
    },
)
response.raise_for_status()
print(response.json())

All parameters

cURL

curl -X POST https://hub.oxen.ai/api/ai/images/edit \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "flux-2-flex",
  "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don'\''t include its arms or legs in the painting.",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ],
  "aspect_ratio": "2:3",
  "resolution": "1 MP",
  "num_inference_steps": 30,
  "guidance": 2,
  "output_format": "webp",
  "output_quality": 80,
  "disable_safety_checker": false
}'

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": "flux-2-flex",
        "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don't include its arms or legs in the painting.",
        "input_image": [
            "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
        ],
        "aspect_ratio": "2:3",
        "resolution": "1 MP",
        "num_inference_steps": 30,
        "guidance": 2,
        "output_format": "webp",
        "output_quality": 80,
        "disable_safety_checker": false
    },
)
response.raise_for_status()
print(response.json())

Async

See the async queue reference for more details.

Minimal

cURL

# 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": "flux-2-flex",
  "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don'\''t include its arms or legs in the painting.",
  "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": "flux-2-flex",
        "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don't include its arms or legs in the painting.",
        "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.")

All parameters

cURL

# 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": "flux-2-flex",
  "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don'\''t include its arms or legs in the painting.",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ],
  "aspect_ratio": "2:3",
  "resolution": "1 MP",
  "num_inference_steps": 30,
  "guidance": 2,
  "output_format": "webp",
  "output_quality": 80,
  "disable_safety_checker": false
}' | 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": "flux-2-flex",
        "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don't include its arms or legs in the painting.",
        "input_image": [
            "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
        ],
        "aspect_ratio": "2:3",
        "resolution": "1 MP",
        "num_inference_steps": 30,
        "guidance": 2,
        "output_format": "webp",
        "output_quality": 80,
        "disable_safety_checker": false
    },
)
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.")

Async with SSE

See the async queue reference for more details.

Minimal

cURL

# 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": "flux-2-flex",
  "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don'\''t include its arms or legs in the painting.",
  "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": "flux-2-flex",
        "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don't include its arms or legs in the painting.",
        "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

All parameters

cURL

# 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": "flux-2-flex",
  "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don'\''t include its arms or legs in the painting.",
  "input_image": [
    "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
  ],
  "aspect_ratio": "2:3",
  "resolution": "1 MP",
  "num_inference_steps": 30,
  "guidance": 2,
  "output_format": "webp",
  "output_quality": 80,
  "disable_safety_checker": false
}' | 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": "flux-2-flex",
        "prompt": "Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don't include its arms or legs in the painting.",
        "input_image": [
            "https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"
        ],
        "aspect_ratio": "2:3",
        "resolution": "1 MP",
        "num_inference_steps": 30,
        "guidance": 2,
        "output_format": "webp",
        "output_quality": 80,
        "disable_safety_checker": false
    },
)
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/flux-2-flex

Request parameters

Required parameters

Field	Type	Default	Description
prompt	string	"Draw a parody of the Mona Lisa by Leonardo da Vinci with Bloxy, the cartoon ox in the reference image, as Lisa del Giocondo. Keep Bloxy in the original style of the reference image with the cartoon ox, but adapt its pose to the pose depicted in the Mona Lisa. Don't include its arms or legs in the painting."	Prompt for generated image
input_image	array<string>	["https://hub.oxen.ai/api/repos/elau/assets/file/main/bloxy/bloxy_cropped_512x512.png"]	Input images to transform or use as reference (supports multiple image urls)

Optional parameters

Field	Type	Default	Description
aspect_ratio	string	"2:3"	Aspect ratio for the generated image One of: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, match_input_image.
resolution	string	"1 MP"	Resolution for the generated image One of: 1 MP, 2 MP, 0.5 MP.
num_inference_steps	integer	30	Number of denoising steps. Recommended range is 28-50, and lower number of steps produce lower quality outputs, faster. Range: 1 – 50.
guidance	number	2	Guidance for generated image. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5 Range: 0 – 10.
seed	integer	—	Random seed. Set for reproducible generation
output_format	string	"webp"	Format of the output images One of: webp, jpg, png.
output_quality	integer	80	Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs Range: 0 – 100.
disable_safety_checker	boolean	false	Disable safety checker for generated images.