FLUX.2 [flex] - Oxen.ai

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
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": "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"
  ]
}'

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
}'

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": "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."

# 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."

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": "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 .

# 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 .

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.

Inference API

Try FLUX.2 [flex] 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