Qwen Image - Oxen.ai

Try Qwen Image in the Workbench

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

Model ID: qwen-image Qwen/Qwen-Image is an image generation model that excels in complex text rendering—including for both alphabetic and logographic languages such as English and Chinese—and precise image editing. It is particularly strong in producing images with high-fidelity embedded text, making it well-suited for tasks where maintaining the integrity and clarity of text within generated images is critical. The model also provides consistent and realistic editing capabilities, such as style transfer, object addition/removal, and detailed attribute editing, with improved preservation of identity for people and products. Some other noteworthy features of Qwen/Qwen-Image include robust support for image understanding tasks—such as object detection, semantic segmentation, depth and edge estimation, novel view synthesis, and super-resolution—and native integration with ControlNet for enhanced conditioning and control of outputs.

Metric	Value
Parameter Count	20 billion
Mixture of Experts	No
Context Length	Unknown
Multilingual	Yes
Quantized*	No

*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 generation reference for more details.

Minimal
All parameters

curl -X POST https://hub.oxen.ai/api/ai/images/generate \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "qwen-image",
  "prompt": "A beautiful landscape painting of a serene lake with mountains in the background"
}'

curl -X POST https://hub.oxen.ai/api/ai/images/generate \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "qwen-image",
  "prompt": "A beautiful landscape painting of a serene lake with mountains in the background",
  "negative_prompt": " ",
  "aspect_ratio": "16:9",
  "image_size": "optimize_for_quality",
  "num_inference_steps": 30,
  "guidance": 3,
  "output_format": "jpg",
  "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": "qwen-image",
  "prompt": "A beautiful landscape painting of a serene lake with mountains in the background"
}' | 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": "qwen-image",
  "prompt": "A beautiful landscape painting of a serene lake with mountains in the background",
  "negative_prompt": " ",
  "aspect_ratio": "16:9",
  "image_size": "optimize_for_quality",
  "num_inference_steps": 30,
  "guidance": 3,
  "output_format": "jpg",
  "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": "qwen-image",
  "prompt": "A beautiful landscape painting of a serene lake with mountains in the background"
}' | 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": "qwen-image",
  "prompt": "A beautiful landscape painting of a serene lake with mountains in the background",
  "negative_prompt": " ",
  "aspect_ratio": "16:9",
  "image_size": "optimize_for_quality",
  "num_inference_steps": 30,
  "guidance": 3,
  "output_format": "jpg",
  "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/qwen-image

Request parameters

Required parameters

Field	Type	Default	Description
`prompt`	`string`	`"A beautiful landscape painting of a serene lake with mountains in the background"`	Prompt for generated image

Optional parameters

Field	Type	Default	Description
`negative_prompt`	`string`	`" "`	Negative prompt for generated image
`aspect_ratio`	`string`	`"16:9"`	Aspect ratio for the generated image One of: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3.
`image_size`	`string`	`"optimize_for_quality"`	Image size for the generated image One of: optimize_for_quality, optimize_for_speed.
`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`	`3`	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`	`"jpg"`	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 Qwen Image 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