Qwen Image Text To Image 2512 API Documentation
Playground
Try it on WaveSpeedAI!Qwen Image 2512 is Qwen’s latest text-to-image model with enhanced prompt understanding, superior text rendering, and versatile aspect ratio support. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
Features
Qwen Image 2512 is latest text-to-image generation model from the Qwen AI family. It excels at understanding natural language prompts and producing high-quality images with exceptional text rendering capabilities — perfect for creating posters, signage, logos, and designs requiring readable text.
Why Choose This?
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Superior text rendering Accurately generates legible text within images, including multiple languages, fonts, and layouts. Ideal for designs requiring readable text elements.
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Enhanced prompt understanding Interprets complex, detailed prompts with better comprehension of subject relationships, spatial arrangements, and stylistic nuances.
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Flexible sizing Supports custom width and height configurations for various use cases — social media, presentations, print, and web content.
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Consistent quality across styles Produces high-quality results whether you’re creating photorealistic images, illustrations, concept art, or abstract designs.
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Prompt Enhancer Built-in tool to automatically improve your prompts for better generation results.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Describe the image you want to create |
| width | No | Image width in pixels (default: 1024) |
| height | No | Image height in pixels (default: 1024) |
| seed | No | Random seed for reproducible results (-1 for random) |
| output_format | No | Output format: jpeg, png, or webp |
Output Format Options
- jpeg — Smaller file size, good for photos and web use
- png — Lossless quality, supports transparency, best for graphics with text
- webp — Modern format with better compression, good browser support
How to Use
- Write your prompt — describe the image you want, including style, composition, lighting, and mood.
- Adjust size — set width and height for your desired dimensions.
- Set seed — use -1 for random results, or specify a number for reproducibility.
- Choose output format — select jpeg, png, or webp based on your needs.
- Run — click Run, preview the result, and iterate if needed.
Pricing
| Item | Cost |
|---|---|
| Per image | $0.02 |
Simple flat-rate pricing regardless of image size.
Best Use Cases
- Marketing and Advertising — Create eye-catching visuals with text for ads, posters, and promotional materials.
- Social Media Content — Generate engaging images optimized for different platform formats.
- Product Design — Visualize concepts, mockups, and packaging designs with integrated text.
- Branding and Identity — Design logos, signage, and branded visuals with readable text elements.
- Editorial and Publishing — Produce illustrations, cover art, and visual content for articles.
Pro Tips
- Be specific in your prompts — include subject, style, lighting, camera angle, and atmosphere for best results.
- For text in images, explicitly specify the exact text, font style, and placement (e.g., “poster with the text SUMMER SALE in bold red letters at the top”).
- Use the same seed with the same prompt to reproduce identical outputs.
- This model is specifically optimized for generating readable text within images.
Notes
- Please ensure your prompts comply with content guidelines. If an error occurs, review your prompt and try again.
Related Models
- Qwen Image Edit 2511 — Image editing model from the Qwen family for precise visual modifications.
- Qwen Image Edit Plus — Enhanced editing model with dual-mode editing and precise bilingual text editing.
- Qwen Image Edit 2511 LoRA — LoRA-enabled version for custom style and character fine-tuning.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic ocean wave at sunrise, highly detailed",
"size": "1024*1024",
"output_format": "jpeg"
}
JSON
)
# 1. Submit the prediction once. Never retry this request automatically:
# a retry after an unclear failure can create a second, billed task.
CHECK='The task may already exist. Check History or the predictions list before submitting again.'
if ! SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
--connect-timeout 10 --max-time 60 \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/qwen-image/text-to-image-2512" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
-H "Content-Type: application/json" \
-d "${REQUEST_BODY}"); then
printf 'Submit failed. %s\n' "${CHECK}" >&2
exit 1
fi
TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
printf 'Submission response did not contain a prediction id. %s\n' "${CHECK}" >&2
exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"
# 2. Poll until the prediction reaches a final status.
BODY_FILE=$(mktemp)
trap 'rm -f "${BODY_FILE}"' EXIT
while true; do
# Transient errors (429, 5xx) are retried, honoring Retry-After.
HTTP_CODE=$(curl --silent --show-error --fail-with-body \
--connect-timeout 10 --max-time 60 --retry 5 --retry-delay 2 \
--output "${BODY_FILE}" --write-out '%{http_code}' \
"${RESULT_URL}" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" || true)
case "${HTTP_CODE}" in
2??) ;;
000|429|5??) # dropped connection or temporary error: keep polling
printf 'Task %s: HTTP %s, polling again in 10s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
sleep 10; continue ;;
*) printf 'Task %s: HTTP %s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
cat "${BODY_FILE}" >&2; exit 1 ;;
esac
RESULT=$(jq 'if type == "object" and has("data") then .data else . end' "${BODY_FILE}")
STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')
case "${STATUS}" in
completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted)
printf 'Task %s ended with status %s\n' "${PREDICTION_ID}" "${STATUS}" >&2
printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneRetry temporary errors only while polling, never the submit request. Errors, retries and timeouts
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | Describe the image you want to create. Be specific about subject, style, composition, and mood for best results. | |
| size | string | No | 1024*1024 | 256 ~ 1536 | The size of the generated image in pixels (width*height) |
| seed | integer | No | - | - | Random seed for reproducible results (same seed + prompt = same output) |
| output_format | string | No | jpeg | jpeg, png, webp | The format of the generated image |
Every model also accepts the global request options enable_sync_mode and enable_base64_output; see their pages for details.
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Output values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.status | string | Task status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses. |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction |
| data.model | string | Model ID used for the prediction |
| data.outputs | array<string | object> | Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model. |
| data.urls | object | Object containing related API endpoints |
| data.status | string | Status: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses |
| data.created_at | string | ISO timestamp of when the request was created |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |