Alibaba Wan 2.7 Text To Image Pro
Playground
Try it on WavespeedAI!Alibaba WAN 2.7 Text-to-Image Pro generates high-quality images up to 4K from text prompts with thinking mode for enhanced image quality. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
Features
Alibaba Wan 2.7 Text-to-Image Pro
Alibaba Wan 2.7 Text-to-Image Pro (alibaba/wan-2.7/text-to-image-pro) is the professional tier of Alibaba’s WanXiang 2.7 text-to-image generation model, supporting output resolutions up to 4K (4096×4096). Combined with built-in thinking mode for enhanced reasoning, it delivers higher-fidelity compositions ideal for print-ready assets, large-format posters, detailed product visuals, and any workflow where resolution and quality are the priority.
Why it stands out
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Up to 4K resolution output Generate images up to 4096×4096 pixels—ideal for print, large-format displays, and high-DPI screens where standard 1024px output falls short.
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Thinking mode for smarter generation Built-in thinking mode enables the model to reason about prompt intent before generating, producing more coherent compositions and better prompt adherence.
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Fast, one-shot text-to-image generation Generate an image in a single run for quick ideation and production workflows.
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Custom size output Set output size directly (768–4096 per dimension) to match banners, thumbnails, posters, or social formats.
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Seeded iteration Use a fixed seed to refine style and layout with more repeatable variations.
Parameters
| Parameter | Description |
|---|---|
| prompt* | Text description of the image you want to generate. |
| size | Output size in pixels (widthheight). Range: 768–4096 per dimension. Default: 10241024. |
| thinking_mode | Enable thinking mode for enhanced reasoning and better image quality (default: true). Increases generation time. |
| seed | Set a fixed seed for more repeatable iterations (-1 for random). |
How to use
- Write a clear prompt (subject + setting + style).
- Choose a size that matches your target aspect ratio and resolution needs (e.g. 20482048, 40962048 for ultra-wide, 2048*4096 for tall posters).
- Leave thinking_mode enabled (default) for best quality, or disable it for faster generation.
- Set a seed if you want repeatable iterations (keep the same seed while you tweak the prompt).
- Click Run, review the result, and iterate.
Prompt tips
- Start with subject + environment + style: “A modern tea shop interior, warm afternoon light, minimalist wood design, cinematic photography.”
- Add camera / composition when framing matters: “wide shot, shallow depth of field, 35mm film look.”
- Keep instructions positive and specific (what you want to see, not what you fear).
- With thinking mode enabled, the model handles short or ambiguous prompts better—but detailed prompts still yield the best results.
- For 4K outputs, include fine detail cues (textures, materials, lighting) to take full advantage of the higher resolution.
Pricing
- $0.075 per generated image
Notes
- Output size is limited to 768–4096 pixels per dimension. If a size fails, reduce resolution or choose a more standard aspect ratio.
- Thinking mode is enabled by default and improves quality, but adds some latency. Disable it if speed is the priority.
- Higher resolutions (e.g. 4096×4096) will take longer to generate than standard sizes.
- Returned image URLs may be time-limited—save outputs if you need long-term storage.
Related Models
- Wan 2.7 Text-to-Image — Standard version at lower cost for everyday generation needs.
- Alibaba Wan 2.6 Text-to-Image — Previous generation Wan text-to-image model with prompt expansion support.
- ByteDance Seedream V4 Text-to-Image — A style-consistent text-to-image generator for posters, campaigns, and high-volume brand-friendly illustration batches.
- FLUX.2 Dev Text-to-Image — A high-quality text-to-image model with strong prompt adherence and fine detail for creative and production workflows.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/alibaba/wan-2.7/text-to-image-pro" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"size": "1024*1024",
"thinking_mode": true,
"seed": -1
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| size | string | No | 1024*1024 | 768 ~ 4096 per dimension | The size of the generated image in pixels (width*height). Pro supports up to 4096*4096 for text-to-image. |
| thinking_mode | boolean | No | true | - | Enable thinking mode for enhanced reasoning and better image quality. Increases generation time. |
| seed | integer | No | -1 | -1 ~ 2147483647 | The random seed to use for the generation. -1 means a random seed will be used. |
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 | Array of URLs to the generated content (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
| data.status | string | Status of the task: created, processing, completed, or failed |
| 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, the ID of the prediction to get |
| data.model | string | Model ID used for the prediction |
| data.outputs | object | Array of URLs to the generated content. |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| 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 |