Z-Image-Turbo - Oxen.ai

Try Z-Image-Turbo in the Workbench

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

Model ID: z-image-turbo Tongyi-MAI/Z-Image-Turbo is an image generation model that excels in fast text-to-image generation with photorealistic outputs and accurate bilingual (English & Chinese) text rendering, while running efficiently on 16 GB VRAM devices. Some other noteworthy features of Tongyi-MAI/Z-Image-Turbo include strong instruction adherence for prompt-following and an 8-step inference design that enables sub-second latency on data-center GPUs.

Metric	Value
Parameter Count	6 billion
Mixture of Experts	No
Context Length	Unknown
Multilingual	Yes
Quantized*	Yes
Precision*	Unknown

*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": "z-image-turbo",
  "prompt": "A woman with red curly hair wearing a red flannel shirt, sitting in front of a campfire, night-time, photorealistic, indy folk vibes."
}'

curl -X POST https://hub.oxen.ai/api/ai/images/generate \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OXEN_API_KEY" \
  -d '{
  "model": "z-image-turbo",
  "prompt": "A woman with red curly hair wearing a red flannel shirt, sitting in front of a campfire, night-time, photorealistic, indy folk vibes.",
  "num_inference_steps": 8,
  "output_format": "webp"
}'

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": "z-image-turbo",
  "prompt": "A woman with red curly hair wearing a red flannel shirt, sitting in front of a campfire, night-time, photorealistic, indy folk vibes."
}' | 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": "z-image-turbo",
  "prompt": "A woman with red curly hair wearing a red flannel shirt, sitting in front of a campfire, night-time, photorealistic, indy folk vibes.",
  "num_inference_steps": 8,
  "output_format": "webp"
}' | 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": "z-image-turbo",
  "prompt": "A woman with red curly hair wearing a red flannel shirt, sitting in front of a campfire, night-time, photorealistic, indy folk vibes."
}' | 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": "z-image-turbo",
  "prompt": "A woman with red curly hair wearing a red flannel shirt, sitting in front of a campfire, night-time, photorealistic, indy folk vibes.",
  "num_inference_steps": 8,
  "output_format": "webp"
}' | 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/z-image-turbo

Request parameters

Required parameters

Field	Type	Default	Description
`prompt`	`string`	`"A woman with red curly hair wearing a red flannel shirt, sitting in front of a campfire, night-time, photorealistic, indy folk vibes."`	Prompt for generated image

Optional parameters

Field	Type	Default	Description
`num_inference_steps`	`integer`	`8`	Number of denoising steps. Recommended range is 28-50, and lower number of steps produce lower quality outputs, faster. Range: 1 – 50.
`seed`	`integer`	—	Random seed. Set for reproducible generation
`output_format`	`string`	`"webp"`	Format of the output images One of: webp, jpg, png.

Inference API

Try Z-Image-Turbo 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