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Alibaba Cloud Model Studio:Wan - text-to-image V2 API reference

Last Updated:Dec 25, 2025

The Wan text-to-image model generates images from text. It supports various artistic styles and realistic photographic effects to meet diverse creative needs.

Quick links: Try online (Singapore | Beijing) | Wan official website

Note

The features on the Wan official website may differ from the capabilities of the API. This document describes the actual capabilities of the API and is updated accordingly.

Prerequisites

Before making a call, obtain an API key and set the API key as an environment variable. To make calls using the SDK, install the DashScope SDK.

Important

The Beijing and Singapore regions have separate API keys and request endpoints. Do not use them interchangeably. Cross-region calls cause authentication failures or service errors.

HTTP synchronous call (wan2.6)

Important

This section uses a new protocol and supports only the wan2.6 model.

You can retrieve the result in a single request. This process is simple and recommended for most scenarios.

Singapore region: POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

Beijing region: POST https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

Request parameters

Text-to-image

curl --location 'https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation' \
--header 'Content-Type: application/json' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--data '{
    "model": "wan2.6-t2i",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "text": "A flower shop with exquisite windows, a beautiful wooden door, and flowers on display"
                    }
                ]
            }
        ]
    },
    "parameters": {
        "prompt_extend": true,
        "watermark": false,
        "n": 1,
        "negative_prompt": "",
        "size": "1280*1280"
    }
}'

Request headers

Content-Type string (Required)

The content type of the request. Set this parameter to application/json.

Authorization string (Required)

The identity authentication credentials for the request. This API uses an Model Studio API key for identity authentication. Example: Bearer sk-xxxx.

Request body

model string (Required)

The model name. Example: wan2.6-t2i.

Note

For information about HTTP calls for wan2.5 and earlier models, see HTTP asynchronous call.

input object (Required)

The basic input information.

Properties

messages array (Required)

An array for the request content. Currently, only single-turn conversations are supported. This means you can pass only one set of role and content parameters. Multi-turn conversations are not supported.

Properties

role string (Required)

The role of the message. This parameter must be set to user.

content array (Required)

An array for the message content.

Properties

text string (Required)

The positive prompt. It describes the content, style, and composition of the image that you want to generate.

Chinese and English are supported. The length cannot exceed 2,100 characters. Each Chinese character, letter, number, or symbol counts as one character. Any excess is automatically truncated.

Example: A sitting orange cat with a happy expression, lively and cute, realistic, and accurate.

Note: You can pass only one text. If you do not pass a text or if you pass multiple texts, an error is returned.

parameters object (Optional)

Image editing parameters.

Properties

negative_prompt string (Optional)

A negative prompt that describes the content that you do not want to see in the image. It can be used to constrain the image.

The maximum length is 500 characters. This parameter supports both Chinese and English. Excess characters are automatically truncated.

Example: low resolution, error, worst quality, low quality, deformed, extra fingers, bad proportions.

size string (Optional)

The resolution of the output image, in the format of width*height.

  • The default is 1280*1280.

  • The total number of pixels must be between 768*768 and 1440*1440, and the aspect ratio must be within the range of [1:4, 4:1]. For example, 768*2700 is a valid resolution.

Example: 1280*1280.

Recommended resolutions for common aspect ratios

  • 1:1: 1280*1280

  • 2:3: 800*1200

  • 3:2: 1200*800

  • 3:4: 960*1280

  • 4:3: 1280*960

  • 9:16: 720*1280

  • 16:9: 1280*720

  • 21:9: 1344*576

n integer (Optional)

Important

The value of `n` directly affects the cost. The cost is calculated as follows: Unit price × Number of images. Before making a call, confirm the model pricing.

The number of images to generate. The value must be an integer from 1 to 4. The default is 4.

Note: Billing is per image. We recommend that you set this to 1 for testing.

prompt_extend bool (Optional)

Specifies whether to enable prompt rewriting. If this parameter is enabled, a large language model optimizes the positive prompt. This significantly improves results for shorter prompts but adds 3 to 4 seconds to the processing time.

  • true (Default)

  • false

watermark bool (Optional)

Specifies whether to add a watermark. The watermark is placed in the lower-right corner of the image with the fixed text "AI-generated".

  • false (Default)

  • true

seed integer (Optional)

The random number seed is used to control the randomness of the content generated by the model, with a value range of [0, 2147483647].

Using the same seed value produces more consistent results. If you do not provide a seed, the algorithm uses a random number.

Note: The model generation process is probabilistic. Even with the same seed, the results are not guaranteed to be identical for every call.

Response parameters

Task successful

Task data, such as the task status and image URLs, is retained for only 24 hours and is automatically purged after this period. You must save the generated images promptly.

{
    "output": {
        "choices": [
            {
                "finish_reason": "stop",
                "message": {
                    "content": [
                        {
                            "image": "https://dashscope-result-bj.oss-cn-beijing.aliyuncs.com/xxxx.png?Expires=xxx",
                            "type": "image"
                        }
                    ],
                    "role": "assistant"
                }
            }
        ],
        "finished": true
    },
    "usage": {
        "image_count": 1,
        "input_tokens": 0,
        "output_tokens": 0,
        "size": "1280*1280",
        "total_tokens": 0
    },
    "request_id": "815505c6-7c3d-49d7-b197-xxxxx"
}

Task abnormal

If the task fails, relevant information is returned. The code and message fields indicate the cause of the error. For more information, see Error messages to resolve the issue.

{
    "request_id": "a4d78a5f-655f-9639-8437-xxxxxx",
    "code": "InvalidParameter",
    "message": "num_images_per_prompt must be 1"
}

output object

The task output information.

Properties

choices array

The output content generated by the model.

Properties

finish_reason string

The reason why the task stopped. A value of stop indicates that the task completed normally.

message object

The message returned by the model.

Properties

role string

The role of the message. The value is fixed as assistant.

content array

Properties

image string

The URL of the generated image. The image is in PNG format. The link is valid for 24 hours. You must download and save the image promptly.

type string

The type of the output. The value is fixed as image.

finished boolean

Indicates whether the task is complete.

  • true

  • false

usage object

Statistics for the output. Only successful results are counted.

Properties

image_count integer

The number of images generated by the model.

size string

The resolution of the generated image. Example: 1280*1280.

input_tokens integer

The number of input tokens. Text-to-image is billed by the number of images. This value is currently fixed at 0.

output_tokens integer

The number of output tokens. Text-to-image is billed by the number of images. This value is currently fixed at 0.

total_tokens integer

The total number of tokens. Text-to-image is billed by the number of images. This value is currently fixed at 0.

request_id string

The unique request ID. You can use this ID to trace and troubleshoot issues.

code string

The error code for a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

message string

The detailed information about a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

HTTP asynchronous call (wan2.6)

Important

The API in this section uses a new protocol and supports only the wan2.6 model.

This method is suitable for scenarios that are sensitive to timeouts. The process involves two core steps: Create a task and then poll for the result. The steps are as follows:

Step 1: Create a task to get a task ID

Singapore region: POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/image-generation/generation

Beijing region: POST https://dashscope.aliyuncs.com/api/v1/services/aigc/image-generation/generation

Note
  • After the task is created, use the returned task_id to query the result. The task_id is valid for 24 hours. Do not create duplicate tasks. Use polling to retrieve the result.

Request parameters

Text-to-image

curl --location 'https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/image-generation/generation' \
--header 'Content-Type: application/json' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'X-DashScope-Async: enable' \
--data '{
    "model": "wan2.6-t2i",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "text": "A flower shop with exquisite windows, a beautiful wooden door, and flowers on display"
                    }
                ]
            }
        ]
    },
    "parameters": {
        "prompt_extend": true,
        "watermark": false,
        "n": 1,
        "negative_prompt": "",
        "size": "1280*1280"
    }
}'
Request headers

Content-Type string (Required)

The content type of the request. Set this parameter to application/json.

Authorization string (Required)

The identity authentication credentials for the request. This API uses an Model Studio API key for identity authentication. Example: Bearer sk-xxxx.

X-DashScope-Async string (Required)

The asynchronous processing configuration parameter. For HTTP asynchronous calls, this must be set to enable.

Important

If this request header is missing, the error "current user api does not support synchronous calls" is returned.

Request body

model string (Required)

The model name. Example: wan2.6-t2i.

Note

For information about HTTP calls for wan2.5 and earlier models, see HTTP asynchronous call.

input object (Required)

The basic input information.

Properties

messages array (Required)

An array for the request content. Currently, only single-turn conversations are supported. This means you can pass only one set of role and content parameters. Multi-turn conversations are not supported.

Properties

role string (Required)

The role of the message. This parameter must be set to user.

content array (Required)

An array for the message content.

Properties

text string (Required)

The positive prompt. It describes the content, style, and composition of the image that you want to generate.

Chinese and English are supported. The length cannot exceed 2,100 characters. Each Chinese character, letter, number, or symbol counts as one character. Any excess is automatically truncated.

Example: A flower shop with exquisite windows, a beautiful wooden door, and flowers on display.

Note: You can pass only one text. If you do not pass a text or if you pass multiple texts, an error is returned.

parameters object (Optional)

Image editing parameters.

Properties

negative_prompt string (Optional)

A negative prompt that describes the content that you do not want to see in the image. It can be used to constrain the image.

The maximum length is 500 characters. This parameter supports both Chinese and English. Excess characters are automatically truncated.

Example: low resolution, error, worst quality, low quality, deformed, extra fingers, bad proportions.

size string (Optional)

The resolution of the output image, in the format of width*height.

  • The default is 1280*1280.

  • The total number of pixels must be between 768*768 and 1440*1440, and the aspect ratio must be within the range of [1:4, 4:1]. For example, 768*2700 is a valid resolution.

Example: 1280*1280.

Recommended resolutions for common aspect ratios

  • 1:1: 1280*1280

  • 2:3: 800*1200

  • 3:2: 1200*800

  • 3:4: 960*1280

  • 4:3: 1280*960

  • 9:16: 720*1280

  • 16:9: 1280*720

  • 21:9: 1344*576

n integer (Optional)

Important

The value of `n` directly affects the cost. The cost is calculated as follows: Unit price × Number of images. Before making a call, confirm the model pricing.

The number of images to generate. The value must be an integer from 1 to 4. The default is 4.

Note: Billing is per image. We recommend that you set this to 1 for testing.

prompt_extend bool (Optional)

Specifies whether to enable prompt rewriting. If this parameter is enabled, a large language model optimizes the positive prompt. This significantly improves results for shorter prompts but adds 3 to 4 seconds to the processing time.

  • true (Default)

  • false

watermark bool (Optional)

Specifies whether to add a watermark. The watermark is placed in the lower-right corner of the image with the fixed text "AI-generated".

  • false (Default)

  • true

seed integer (Optional)

The random number seed is used to control the randomness of the content generated by the model, with a value range of [0, 2147483647].

Using the same seed value produces more consistent results. If you do not provide a seed, the algorithm uses a random number.

Note: The model generation process is probabilistic. Even with the same seed, the results are not guaranteed to be identical for every call.

Response parameters

Successful response

Save the task_id to query the task status and result.

{
    "output": {
        "task_status": "PENDING",
        "task_id": "0385dc79-5ff8-4d82-bcb6-xxxxxx"
    },
    "request_id": "4909100c-7b5a-9f92-bfe5-xxxxxx"
}

Error response

The task creation failed. For more information, see Error messages to resolve the issue.

{
    "code":"InvalidApiKey",
    "message":"Invalid API-key provided.",
    "request_id":"fb53c4ec-1c12-4fc4-a580-xxxxxx"
}

output object

The task output information.

Properties

task_id string

The task ID. The query is valid for 24 hours.

task_status string

The task status.

Enumeration

  • PENDING

  • RUNNING

  • SUCCEEDED

  • FAILED

  • CANCELED

  • UNKNOWN: The task does not exist or its status cannot be determined.

request_id string

The unique request ID. You can use this ID to trace and troubleshoot issues.

code string

The error code for a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

message string

The detailed information about a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

Step 2: Query the result by task ID

Singapore region: GET https://dashscope-intl.aliyuncs.com/api/v1/tasks/{task_id}

Beijing region: GET https://dashscope.aliyuncs.com/api/v1/tasks/{task_id}

Note
  • Polling suggestion: Image generation takes several minutes. Use a polling mechanism and set a reasonable query interval, such as 10 seconds, to retrieve the result.

  • Task status transition: PENDING → RUNNING → SUCCEEDED or FAILED.

  • Result link: After the task is successful, an image link is returned. The link is valid for 24 hours. After you retrieve the link, immediately download and save the image to a permanent storage service, such as Object Storage Service.

Request parameters

Query task result

Replace 86ecf553-d340-4e21-xxxxxxxxx with the actual task ID.

The API keys for the Singapore and Beijing regions are different. Create an API key.
The following `base_url` is for the Singapore region. For models in the Beijing region, replace the `base_url` with `https://dashscope.aliyuncs.com/api/v1/tasks/86ecf553-d340-4e21-xxxxxxxxx`.
curl -X GET https://dashscope-intl.aliyuncs.com/api/v1/tasks/86ecf553-d340-4e21-xxxxxxxxx \
--header "Authorization: Bearer $DASHSCOPE_API_KEY"
Request headers

Authorization string (Required)

The identity authentication credentials for the request. This API uses an Model Studio API key for identity authentication. Example: Bearer sk-xxxx.

URL path parameters

task_id string (Required)

The task ID.

Response parameters

Task successful

Task data, such as the task status and image URLs, is retained for only 24 hours and is automatically purged after this period. You must save the generated images promptly.

{
    "request_id": "2ddf53fa-699a-4267-9446-xxxxxx",
    "output": {
        "task_id": "3cd3fa4e-53ee-4136-9cab-xxxxxx",
        "task_status": "SUCCEEDED",
        "submit_time": "2025-12-18 20:03:01.802",
        "scheduled_time": "2025-12-18 20:03:01.834",
        "end_time": "2025-12-18 20:03:29.260",
        "finished": true,
        "choices": [
            {
                "finish_reason": "stop",
                "message": {
                    "role": "assistant",
                    "content": [
                        {
                            "image": "https://dashscope-result-bj.oss-cn-beijing.aliyuncs.com/xxx.png?Expires=xxx",
                            "type": "image"
                        }
                    ]
                }
            }
        ]
    },
    "usage": {
        "size": "1280*1280",
        "total_tokens": 0,
        "image_count": 1,
        "output_tokens": 0,
        "input_tokens": 0
    }
}

Task abnormal

If the task fails for any reason, relevant information is returned. The code and message fields indicate the cause of the error. For more information, see Error messages to resolve the issue.

{
    "code":"InvalidApiKey",
    "message":"Invalid API-key provided.",
    "request_id":"fb53c4ec-1c12-4fc4-a580-xxxxxx"
}

output object

The task output information.

Properties

task_id string

The task ID. The query is valid for 24 hours.

task_status string

The task status.

Enumeration

  • PENDING

  • RUNNING

  • SUCCEEDED

  • FAILED

  • CANCELED

  • UNKNOWN: The task does not exist or its status cannot be determined.

Status transitions during polling:

  • PENDING → RUNNING → SUCCEEDED or FAILED.

  • The status of the first query is usually PENDING or RUNNING.

  • If the status changes to SUCCEEDED, the response contains the generated image URL.

  • If the status is FAILED, check the error message and retry.

submit_time string

The time when the task was submitted. The time is in the UTC+8 time zone. The format is YYYY-MM-DD HH:mm:ss.SSS.

scheduled_time string

The time when the task started running. The time is in the UTC+8 time zone. The format is YYYY-MM-DD HH:mm:ss.SSS.

end_time string

The time when the task was completed. The time is in the UTC+8 time zone. The format is YYYY-MM-DD HH:mm:ss.SSS.

finished boolean

Indicates whether the task is complete.

  • true

  • false

choices array

The output content generated by the model.

Properties

finish_reason string

The reason why the task stopped. A value of stop indicates normal completion.

message object

The message returned by the model.

Properties

role string

The role of the message. The value is fixed as assistant.

content array

Properties

image string

The URL of the generated image. The image is in PNG format.

The link is valid for 24 hours. You must download and save the image promptly.

type string

The type of the output. The value is fixed as image.

usage object

Statistics for the output. Only successful results are counted.

Properties

image_count integer

The number of generated images.

size string

The resolution of the generated image. Example: 1280*1280.

input_tokens integer

The number of input tokens. The value is currently fixed at 0.

output_tokens integer

The number of output tokens. The value is currently fixed at 0.

total_tokens integer

The total number of tokens. The value is currently fixed at 0.

request_id string

The unique request ID. You can use this ID to trace and troubleshoot issues.

code string

The error code for a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

message string

The detailed information about a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

HTTP asynchronous call (wan2.5 and earlier models)

Important

This API uses the old protocol and supports only wan2.5 and earlier models.

Because text-to-image tasks are time-consuming, typically taking 1 to 2 minutes, the API uses asynchronous invocation. The process involves two core steps: Create a task and then poll for the result. The steps are as follows:

The actual time required depends on the number of tasks in the queue and the service execution status. Be patient while you retrieve the result.

Step 1: Create a task to get a task ID

Singapore region: POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text2image/image-synthesis

Beijing region: POST https://dashscope.aliyuncs.com/api/v1/services/aigc/text2image/image-synthesis

Note
  • After the task is created, use the returned task_id to query the result. The task_id is valid for 24 hours. Do not create duplicate tasks. Use polling to retrieve the result.

Request parameters

Text-to-image

The API keys for the Singapore and Beijing regions are different. For more information, see Obtain and configure an API key
The following URL is for the Singapore region. If you use a model in the Beijing region, replace the URL with the following one: https://dashscope.aliyuncs.com/api/v1/services/aigc/video-generation/video-synthesis
curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text2image/image-synthesis \
    -H 'X-DashScope-Async: enable' \
    -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
    -H 'Content-Type: application/json' \
    -d '{
    "model": "wan2.5-t2i-preview",
    "input": {
        "prompt": "A flower shop with exquisite windows, a beautiful wooden door, and flowers on display"
    },
    "parameters": {
        "size": "1280*1280",
        "n": 1
    }
}'    

Text-to-image (using a negative prompt)

You can use the negative_prompt parameter to prevent the "person" element from appearing in the generated image.

The API keys for the Singapore and Beijing regions are different. For more information, see Obtain and configure an API key
The following URL is for the Singapore region. If you use a model in the Beijing region, replace the URL with the following one: https://dashscope.aliyuncs.com/api/v1/services/aigc/video-generation/video-synthesis
curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text2image/image-synthesis \
    -H 'X-DashScope-Async: enable' \
    -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
    -H 'Content-Type: application/json' \
    -d '{
    "model": "wan2.2-t2i-flash",
    "input": {
        "prompt": "Snowy ground, a small white chapel, aurora borealis, winter scene, soft light.",
        "negative_prompt": "person"
    },
    "parameters": {
        "size": "1024*1024",
        "n": 1
    }
}'
Request headers

Content-Type string (Required)

The content type of the request. Set this parameter to application/json.

Authorization string (Required)

The identity authentication credentials for the request. This API uses an Model Studio API key for identity authentication. Example: Bearer sk-xxxx.

X-DashScope-Async string (Required)

The asynchronous processing configuration parameter. HTTP requests support only asynchronous processing. You must set this parameter to enable.

Important

If this request header is missing, the error message "current user api does not support synchronous calls" is returned.

Request body

model string (Required)

The model name. For text-to-image models, see the Model list.

Example: wan2.5-t2i-preview.

Note

For information about HTTP calls for the wan2.6 model, see HTTP synchronous call and HTTP asynchronous call.

input object (Required)

The basic input information, such as the prompt.

Properties

prompt string (Required)

The positive prompt. It describes the desired elements and visual features in the generated image.

Chinese and English are supported. Each Chinese character, letter, or punctuation mark counts as one character. Any excess is automatically truncated. The length limit varies based on the model version:

  • wan2.5-t2i-preview: The length cannot exceed 2,000 characters.

  • Models of version 2.2 and earlier: The length cannot exceed 800 characters.

Example: A sitting orange cat, with a happy expression, lively and cute, realistic and accurate.

For more information about how to use prompts, see the Text-to-image prompt guide.

negative_prompt string (Optional)

The negative prompt. It describes content that you do not want to appear in the image to constrain the output.

Chinese and English are supported. The length cannot exceed 500 characters. Any excess is automatically truncated.

Example: low resolution, error, worst quality, low quality, deformed, extra fingers, bad proportions.

parameters object (Optional)

Image editing parameters. You can set the image resolution, enable prompt rewriting, add a watermark, and more.

Properties

size string (Optional)

The resolution of the output image, in the format of width*height. The default value and constraints vary based on the model version:

  • wan2.5-t2i-preview: The default is 1280*1280. The total number of pixels must be between 768*768 and 1440*1440, and the aspect ratio must be within the range of [1:4, 4:1]. For example, 768*2700 is a valid resolution.

  • Models of version 2.2 and earlier: The default is 1024*1024. The image width and height must be between 512 and 1,440 pixels, with a maximum resolution of 1,440*1,440. For example, 768*2700 exceeds the single-side limit and is not supported.

Example: 1280*1280.

Recommended resolutions for common aspect ratios

  • 1:1: 1280*1280 or 1024*1024

  • 2:3: 800*1200

  • 3:2: 1200*800

  • 3:4: 960*1280

  • 4:3: 1280*960

  • 9:16: 720*1280

  • 16:9: 1280*720

  • 21:9: 1344*576

n integer (Optional)

Important

The value of `n` directly affects the cost. The cost is calculated as follows: Unit price × Number of images. Before making a call, confirm the model pricing.

The number of images to generate. The value must be an integer from 1 to 4. The default is 4. During testing, you can set this to 1 for low-cost validation.

prompt_extend boolean (Optional)

Specifies whether to enable prompt rewriting. If this parameter is enabled, a large language model rewrites the input prompt. This significantly improves results for shorter prompts but increases the processing time.

  • true (Default)

  • false

Example: true.

watermark boolean (Optional)

Specifies whether to add a watermark. The watermark is placed in the lower-right corner of the image with the fixed text "AI-generated".

  • false (Default)

  • true

seed integer (Optional)

The random number seed. The value must be an integer from [0, 2147483647].

If you do not provide a seed, the algorithm automatically generates a random number to use as the seed. If you provide a seed, the algorithm generates a unique seed parameter for each of the n images. The total number of images is specified by n. For example, if n is 4, the algorithm generates the images using seed, seed+1, seed+2, and seed+3 as their respective seed parameters.

To improve the reproducibility of the results, we recommend that you use a fixed seed value.

Note that because the model generation is probabilistic, using the same seed does not guarantee identical results every time.

Response parameters

Successful response

Save the task_id to query the task status and result.

{
    "output": {
        "task_status": "PENDING",
        "task_id": "0385dc79-5ff8-4d82-bcb6-xxxxxx"
    },
    "request_id": "4909100c-7b5a-9f92-bfe5-xxxxxx"
}

Error response

The task creation failed. For more information, see Error messages to resolve the issue.

{
    "code":"InvalidApiKey",
    "message":"Invalid API-key provided.",
    "request_id":"fb53c4ec-1c12-4fc4-a580-xxxxxx"
}

output object

The task output information.

Properties

task_id string

The task ID. The query is valid for 24 hours.

task_status string

The task status.

Enumeration

  • PENDING

  • RUNNING

  • SUCCEEDED

  • FAILED

  • CANCELED

  • UNKNOWN: The task does not exist or its status cannot be determined.

request_id string

The unique request ID. You can use this ID to trace and troubleshoot issues.

code string

The error code for a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

message string

The detailed information about a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

Step 2: Query the result by task ID

Singapore region: GET https://dashscope-intl.aliyuncs.com/api/v1/tasks/{task_id}

Beijing region: GET https://dashscope.aliyuncs.com/api/v1/tasks/{task_id}

Note
  • Polling suggestion: Image generation takes several minutes. Use a polling mechanism and set a reasonable query interval, such as 10 seconds, to retrieve the result.

  • Task status transition: PENDING → RUNNING → SUCCEEDED or FAILED.

  • Result link: After the task is successful, an image link is returned. The link is valid for 24 hours. After you retrieve the link, immediately download and save the image to a permanent storage service, such as Object Storage Service.

Request parameters

Query task result

Replace 86ecf553-d340-4e21-xxxxxxxxx with the actual task ID.

The API keys for the Singapore and Beijing regions are different. Create an API key.
The following `base_url` is for the Singapore region. For models in the Beijing region, replace the `base_url` with `https://dashscope.aliyuncs.com/api/v1/tasks/86ecf553-d340-4e21-xxxxxxxxx`.
curl -X GET https://dashscope-intl.aliyuncs.com/api/v1/tasks/86ecf553-d340-4e21-xxxxxxxxx \
--header "Authorization: Bearer $DASHSCOPE_API_KEY"
Request headers

Authorization string (Required)

The identity authentication credentials for the request. This API uses an Model Studio API key for identity authentication. Example: Bearer sk-xxxx.

URL path parameters

task_id string (Required)

The task ID.

Response parameters

Task successful

Image URLs are retained for only 24 hours and are automatically purged after this period. You must save the generated images promptly.

{
    "request_id": "f767d108-7d50-908b-a6d9-xxxxxx",
    "output": {
        "task_id": "d492bffd-10b5-4169-b639-xxxxxx",
        "task_status": "SUCCEEDED",
        "submit_time": "2025-01-08 16:03:59.840",
        "scheduled_time": "2025-01-08 16:03:59.863",
        "end_time": "2025-01-08 16:04:10.660",
        "results": [
            {
                "orig_prompt": "A flower shop with exquisite windows, a beautiful wooden door, and flowers on display",
                "actual_prompt": "A flower shop with exquisitely carved windows and a beautiful dark wooden door with a brass handle. Inside, a variety of colorful and vibrant flowers, including roses, lilies, and sunflowers, are on display. The background is a warm indoor scene, with the street visible through the window. High-definition realistic photography, medium shot composition.",
                "url": "https://dashscope-result-wlcb.oss-cn-wulanchabu.aliyuncs.com/1.png"
            }
        ],
        "task_metrics": {
            "TOTAL": 1,
            "SUCCEEDED": 1,
            "FAILED": 0
        }
    },
    "usage": {
        "image_count": 1
    }
}

Task failed

If a task fails, task_status is set to FAILED, and an error code and message are provided. For more information, see Error messages to resolve the issue.

{
    "request_id": "e5d70b02-ebd3-98ce-9fe8-759d7d7b107d",
    "output": {
        "task_id": "86ecf553-d340-4e21-af6e-xxxxxx",
        "task_status": "FAILED",
        "code": "InvalidParameter",
        "message": "xxxxxx",
        "task_metrics": {
            "TOTAL": 4,
            "SUCCEEDED": 0,
            "FAILED": 4
        }
    }
}

Partial task failure

The model can generate multiple images in a single task. If at least one image is generated successfully, the task status is marked as SUCCEEDED, and the corresponding image URL is returned. For images that fail to generate, the result contains the reason for the failure. In addition, only successful results are counted in usage statistics. For more information, see Error messages to resolve the issue.

{
    "request_id": "85eaba38-0185-99d7-8d16-xxxxxx",
    "output": {
        "task_id": "86ecf553-d340-4e21-af6e-xxxxxx",
        "task_status": "SUCCEEDED",
        "results": [
            {
                "url": "https://dashscope-result-bj.oss-cn-beijing.aliyuncs.com/123/a1.png"
            },
            {
                "code": "InternalError.Timeout",
                "message": "An internal timeout error has occurred during execution, please try again later or contact service support."
            }
        ],
        "task_metrics": {
            "TOTAL": 2,
            "SUCCEEDED": 1,
            "FAILED": 1
        }
    },
    "usage": {
        "image_count": 1
    }
}

Expired task query

The task_id is valid for 24 hours. After this period, the query fails and the following error message is returned.

{
    "request_id": "a4de7c32-7057-9f82-8581-xxxxxx",
    "output": {
        "task_id": "502a00b1-19d9-4839-a82f-xxxxxx",
        "task_status": "UNKNOWN"
    }
}

output object

The task output information.

Properties

task_id string

The task ID. The query is valid for 24 hours.

task_status string

The task status.

Enumeration

  • PENDING

  • RUNNING

  • SUCCEEDED

  • FAILED

  • CANCELED

  • UNKNOWN: The task does not exist or its status cannot be determined.

Status transitions during polling:

  • PENDING → RUNNING → SUCCEEDED or FAILED.

  • The status of the first query is usually PENDING or RUNNING.

  • If the status changes to SUCCEEDED, the response contains the generated image URL.

  • If the status is FAILED, check the error message and retry.

submit_time string

The time when the task was submitted. The time is in the UTC+8 time zone. The format is YYYY-MM-DD HH:mm:ss.SSS.

scheduled_time string

The time when the task started running. The time is in the UTC+8 time zone. The format is YYYY-MM-DD HH:mm:ss.SSS.

end_time string

The time when the task was completed. The time is in the UTC+8 time zone. The format is YYYY-MM-DD HH:mm:ss.SSS.

results array of object

A list of task results, including the image URL, prompt, and error information for partially failed tasks.

Data structure

{
    "results": [
        {
            "orig_prompt": "",
            "actual_prompt": "",
            "url": ""
        },
        {
            "code": "",
            "message": ""
        }
    ]
}

Properties

orig_prompt string

The original input prompt. This corresponds to the prompt request parameter.

actual_prompt string

If prompt rewriting is enabled, this parameter returns the actual optimized prompt that is used. If this feature is disabled, this parameter is not returned.

url string

The image URL. This is returned only when `task_status` is SUCCEEDED. The link is valid for 24 hours. You can use this URL to download the image.

code string

The error code for a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

message string

The detailed information about a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

task_metrics object

The task result statistics.

Properties

TOTAL integer

The total number of tasks.

SUCCEEDED integer

The number of successful tasks.

FAILED integer

The number of failed tasks.

code string

The error code for a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

message string

The detailed information about a failed request. This parameter is not returned if the request is successful. For more information, see Error messages.

usage object

Statistics for the output. Only successful results are counted.

Properties

image_count integer

The number of images successfully generated by the model. Billing formula: Fee = Number of images × Unit price.

request_id string

The unique request ID. You can use this ID to trace and troubleshoot issues.

DashScope SDK

The parameter names in the SDK are mostly consistent with those in the HTTP API. The parameter structure is encapsulated based on the features of the programming language.

Because text-to-image tasks are time-consuming, typically taking 1 to 2 minutes, the SDK encapsulates the HTTP asynchronous call process at the underlying layer and supports both synchronous and asynchronous invocation methods.

The actual time required depends on the number of tasks in the queue and the service execution status. Be patient while you retrieve the result.

Python SDK

Important
  • The wan2.6-t2i model does not support SDK calls. The following code is only for wan2.5 and earlier models.

  • Before you run the following code, make sure that your DashScope Python SDK version is 1.25.2 or later.

    Older versions may trigger errors such as "url error, please check url!". For more information about how to update the SDK, see Install the SDK.

Synchronous invocation

Request example
from http import HTTPStatus
from urllib.parse import urlparse, unquote
from pathlib import PurePosixPath
import requests
from dashscope import ImageSynthesis
import os
import dashscope

# The following is the URL for the Singapore region. If you use a model in the Beijing region, replace the URL with: https://dashscope.aliyuncs.com/api/v1
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
# The API keys for the Singapore and Beijing regions are different. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key = os.getenv("DASHSCOPE_API_KEY")

print('----sync call, please wait a moment----')
rsp = ImageSynthesis.call(api_key=api_key,
                          model="wan2.5-t2i-preview",
                          prompt="A flower shop with exquisite windows, a beautiful wooden door, and flowers on display",
                          negative_prompt="",
                          n=1,
                          size='1280*1280',
                          prompt_extend=True,
                          watermark=False,
                          seed=12345)
print('response: %s' % rsp)
if rsp.status_code == HTTPStatus.OK:
    # Save the image to the current directory
    for result in rsp.output.results:
        file_name = PurePosixPath(unquote(urlparse(result.url).path)).parts[-1]
        with open('./%s' % file_name, 'wb+') as f:
            f.write(requests.get(result.url).content)
else:
    print('sync_call Failed, status_code: %s, code: %s, message: %s' %
          (rsp.status_code, rsp.code, rsp.message))
Response example
The URL is valid for 24 hours. You must download the image promptly.
{
    "status_code": 200,
    "request_id": "9d634fda-5fe9-9968-a908-xxxxxx",
    "code": null,
    "message": "",
    "output": {
        "task_id": "d35658e4-483f-453b-b8dc-xxxxxx",
        "task_status": "SUCCEEDED",
        "results": [{
            "url": "https://dashscope-result-wlcb.oss-cn-wulanchabu.aliyuncs.com/1.png",
            "orig_prompt": "A flower shop with exquisite windows, a beautiful wooden door, and flowers on display",
            "actual_prompt": "An exquisite flower shop, with windows decorated with elegant carvings and a beautiful wooden door with a brass handle. Inside, various colorful flowers such as roses, tulips, and lilies are on display. The background is a warm indoor scene with soft light, creating a quiet and comfortable atmosphere. High-definition realistic photography, close-up center composition."
        }],
        "submit_time": "2025-01-08 19:36:01.521",
        "scheduled_time": "2025-01-08 19:36:01.542",
        "end_time": "2025-01-08 19:36:13.270",
        "task_metrics": {
            "TOTAL": 1,
            "SUCCEEDED": 1,
            "FAILED": 0
        }
    },
    "usage": {
        "image_count": 1
    }
}

Asynchronous invocation

Request example
from http import HTTPStatus
from urllib.parse import urlparse, unquote
from pathlib import PurePosixPath
import requests
from dashscope import ImageSynthesis
import os
import dashscope

# The following is the URL for the Singapore region. If you use a model in the Beijing region, replace the URL with: https://dashscope.aliyuncs.com/api/v1
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

# If you have not configured the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx"
# The API keys for the Singapore and Beijing regions are different. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key = os.getenv("DASHSCOPE_API_KEY")

def async_call():
    print('----create task----')
    task_info = create_async_task()
    print('----wait task done then save image----')
    wait_async_task(task_info)


# Create an asynchronous task
def create_async_task():
    rsp = ImageSynthesis.async_call(api_key=api_key,
                                    model="wan2.5-t2i-preview",
                                    prompt="A flower shop with exquisite windows, a beautiful wooden door, and flowers on display",
                                    negative_prompt="",
                                    n=1,
                                    size='1280*1280',
                                    prompt_extend=True,
                                    watermark=False,
                                    seed=12345)
    print(rsp)
    if rsp.status_code == HTTPStatus.OK:
        print(rsp.output)
    else:
        print('Failed, status_code: %s, code: %s, message: %s' %
              (rsp.status_code, rsp.code, rsp.message))
    return rsp


# Wait for the asynchronous task to complete
def wait_async_task(task):
    rsp = ImageSynthesis.wait(task=task, api_key=api_key)
    print(rsp)
    if rsp.status_code == HTTPStatus.OK:
        print(rsp.output)
        # save file to current directory
        for result in rsp.output.results:
            file_name = PurePosixPath(unquote(urlparse(result.url).path)).parts[-1]
            with open('./%s' % file_name, 'wb+') as f:
                f.write(requests.get(result.url).content)
    else:
        print('Failed, status_code: %s, code: %s, message: %s' %
              (rsp.status_code, rsp.code, rsp.message))


# Get asynchronous task information
def fetch_task_status(task):
    status = ImageSynthesis.fetch(task=task, api_key=api_key)
    print(status)
    if status.status_code == HTTPStatus.OK:
        print(status.output.task_status)
    else:
        print('Failed, status_code: %s, code: %s, message: %s' %
              (status.status_code, status.code, status.message))


# Cancel the asynchronous task. Only tasks in the PENDING state can be canceled.
def cancel_task(task):
    rsp = ImageSynthesis.cancel(task=task, api_key=api_key)
    print(rsp)
    if rsp.status_code == HTTPStatus.OK:
        print(rsp.output.task_status)
    else:
        print('Failed, status_code: %s, code: %s, message: %s' %
              (rsp.status_code, rsp.code, rsp.message))


if __name__ == '__main__':
    async_call()
Response example

1. Example of a response for creating a task

{
	"status_code": 200,
	"request_id": "31b04171-011c-96bd-ac00-f0383b669cc7",
	"code": "",
	"message": "",
	"output": {
		"task_id": "4f90cf14-a34e-4eae-xxxxxxxx",
		"task_status": "PENDING",
		"results": []
	},
	"usage": null
}

2. Example of a response for querying a task result

The URL is valid for 24 hours. You must download the image promptly.
{
    "status_code": 200,
    "request_id": "9d634fda-5fe9-9968-a908-xxxxxx",
    "code": null,
    "message": "",
    "output": {
        "task_id": "d35658e4-483f-453b-b8dc-xxxxxx",
        "task_status": "SUCCEEDED",
        "results": [{
            "url": "https://dashscope-result-wlcb.oss-cn-wulanchabu.aliyuncs.com/xxx.png",
            "orig_prompt": "A flower shop with exquisite windows, a beautiful wooden door, and flowers on display",
            "actual_prompt": "An exquisite flower shop, with windows decorated with elegant carvings and a beautiful wooden door with a brass handle. Inside, various colorful flowers such as roses, tulips, and lilies are on display. The background is a warm indoor scene with soft light, creating a quiet and comfortable atmosphere. High-definition realistic photography, close-up center composition."
        }],
        "submit_time": "2025-01-08 19:36:01.521",
        "scheduled_time": "2025-01-08 19:36:01.542",
        "end_time": "2025-01-08 19:36:13.270",
        "task_metrics": {
            "TOTAL": 1,
            "SUCCEEDED": 1,
            "FAILED": 0
        }
    },
    "usage": {
        "image_count": 1
    }
}

Java SDK

Important
  • The wan2.6-t2i model does not support SDK calls. The following code is only for wan2.5 and earlier models.

  • Before you run the following code, make sure that your DashScope Java SDK version is 2.22.2 or later.

    Older versions may trigger errors such as "url error, please check url!". For more information about how to update the SDK, see Install the SDK.

Synchronous invocation

Request example
// Copyright (c) Alibaba, Inc. and its affiliates.

import com.alibaba.dashscope.aigc.imagesynthesis.ImageSynthesis;
import com.alibaba.dashscope.aigc.imagesynthesis.ImageSynthesisListResult;
import com.alibaba.dashscope.aigc.imagesynthesis.ImageSynthesisParam;
import com.alibaba.dashscope.aigc.imagesynthesis.ImageSynthesisResult;
import com.alibaba.dashscope.task.AsyncTaskListParam;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.utils.Constants;
import com.alibaba.dashscope.utils.JsonUtils;

import java.util.HashMap;
import java.util.Map;

public class Main {

  static {
     // The following is the URL for the Singapore region. If you use a model in the Beijing region, replace the URL with: https://dashscope.aliyuncs.com/api/v1
     Constants.baseHttpApiUrl = "https://dashscope-intl.aliyuncs.com/api/v1";  
  }
  
  // If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey="sk-xxx"
  // The API keys for the Singapore and Beijing regions are different. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
  static String apiKey = System.getenv("DASHSCOPE_API_KEY");
  
  public static void basicCall() throws ApiException, NoApiKeyException {
        // Set parameters
        Map<String, Object> parameters = new HashMap<>();
        parameters.put("prompt_extend", true);
        parameters.put("watermark", false);
        parameters.put("seed", 12345);

        ImageSynthesisParam param =
                ImageSynthesisParam.builder()
                        .apiKey(apiKey)
                        .model("wan2.5-t2i-preview")
                        .prompt("A flower shop with exquisite windows, a beautiful wooden door, and flowers on display")
                        .n(1)
                        .size("1280*1280")
                        .negativePrompt("")
                        .parameters(parameters)
                        .build();

        ImageSynthesis imageSynthesis = new ImageSynthesis();
        ImageSynthesisResult result = null;
        try {
            System.out.println("---sync call, please wait a moment----");
            result = imageSynthesis.call(param);
        } catch (ApiException | NoApiKeyException e){
            throw new RuntimeException(e.getMessage());
        }
        System.out.println(JsonUtils.toJson(result));
    }

    public static void listTask() throws ApiException, NoApiKeyException {
        ImageSynthesis is = new ImageSynthesis();
        AsyncTaskListParam param = AsyncTaskListParam.builder().build();
        param.setApiKey(apiKey);
        ImageSynthesisListResult result = is.list(param);
        System.out.println(result);
    }

    public static void fetchTask(String taskId) throws ApiException, NoApiKeyException {
        ImageSynthesis is = new ImageSynthesis();
        // If set DASHSCOPE_API_KEY environment variable, apiKey can null.
        ImageSynthesisResult result = is.fetch(taskId, apiKey);
        System.out.println(result.getOutput());
        System.out.println(result.getUsage());
    }

    public static void main(String[] args){
        try{
            basicCall();
            //listTask();
        }catch(ApiException|NoApiKeyException e){
            System.out.println(e.getMessage());
        }
    }
}
Response example
The URL is valid for 24 hours. You must download the image promptly.
{
    "request_id": "22f9c744-206c-9a78-899a-xxxxxx",
    "output": {
        "task_id": "4a0f8fc6-03fb-4c44-a13a-xxxxxx",
        "task_status": "SUCCEEDED",
        "results": [{
           "orig_prompt": "A flower shop with exquisite windows, a beautiful wooden door, and flowers on display",
            "actual_prompt": "A flower shop with exquisitely carved windows and a beautiful dark wooden door slightly ajar. Inside, a variety of colorful and fragrant flowers, including roses, lilies, and sunflowers, are on display. The background is a warm indoor scene with soft light shining on the flowers through the window. High-definition realistic photography, medium shot composition.",
            "url": "https://dashscope-result-wlcb.oss-cn-wulanchabu.aliyuncs.com/1.png"
        }],
        "task_metrics": {
            "TOTAL": 1,
            "SUCCEEDED": 1,
            "FAILED": 0
        }
    },
    "usage": {
        "image_count": 1
    }
}

Asynchronous invocation

Request example
// Copyright (c) Alibaba, Inc. and its affiliates.

import com.alibaba.dashscope.aigc.imagesynthesis.ImageSynthesis;
import com.alibaba.dashscope.aigc.imagesynthesis.ImageSynthesisParam;
import com.alibaba.dashscope.aigc.imagesynthesis.ImageSynthesisResult;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.utils.Constants;
import com.alibaba.dashscope.utils.JsonUtils;

import java.util.HashMap;
import java.util.Map;

public class Main {
    static {
        // The following is the URL for the Singapore region. If you use a model in the Beijing region, replace the URL with: https://dashscope.aliyuncs.com/api/v1
        Constants.baseHttpApiUrl = "https://dashscope-intl.aliyuncs.com/api/v1";
    }
    
    // If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey="sk-xxx"
    // The API keys for the Singapore and Beijing regions are different. To obtain an API key, see https://www.alibabacloud.com/help/zh/model-studio/get-api-key
    static String apiKey = System.getenv("DASHSCOPE_API_KEY");
    
    public void asyncCall() {
        System.out.println("---create task----");
        String taskId = this.createAsyncTask();
        System.out.println("---wait task done then return image url----");
        this.waitAsyncTask(taskId);
    }


    /**
     * Create an asynchronous task
     * @return taskId
     */
    public String createAsyncTask() {
        // Set parameters
        Map<String, Object> parameters = new HashMap<>();
        parameters.put("prompt_extend", true);
        parameters.put("watermark", false);
        parameters.put("seed", 12345);

        ImageSynthesisParam param =
                ImageSynthesisParam.builder()
                        .apiKey(apiKey)
                        .model("wan2.5-t2i-preview")
                        .prompt("A flower shop with exquisite windows, a beautiful wooden door, and flowers on display")
                        .n(1)
                        .size("1280*1280)
                        .negativePrompt("")
                        .parameters(parameters)
                        .build();

        ImageSynthesis imageSynthesis = new ImageSynthesis();
        ImageSynthesisResult result = null;
        try {
            result = imageSynthesis.asyncCall(param);
        } catch (Exception e){
            throw new RuntimeException(e.getMessage());
        }
        System.out.println(JsonUtils.toJson(result));
        String taskId = result.getOutput().getTaskId();
        System.out.println("taskId=" + taskId);
        return taskId;
    }


    /**
     * Wait for the asynchronous task to complete
     * @param taskId The task ID
     * */
    public void waitAsyncTask(String taskId) {
        ImageSynthesis imageSynthesis = new ImageSynthesis();
        ImageSynthesisResult result = null;
        try {
            // After configuring the environment variable, you can set apiKey to null here
            result = imageSynthesis.wait(taskId, apiKey);
        } catch (ApiException | NoApiKeyException e){
            throw new RuntimeException(e.getMessage());
        }
        System.out.println(JsonUtils.toJson(result));
        System.out.println(JsonUtils.toJson(result.getOutput()));
    }


    public static void main(String[] args){
        Main main = new Main();
        main.asyncCall();
    }

}
Response example

1. Example of a response for creating a task

{
	"request_id": "5dbf9dc5-4f4c-9605-85ea-542f97709ba8",
	"output": {
		"task_id": "7277e20e-aa01-4709-xxxxxxxx",
		"task_status": "PENDING"
	}
}

2. Example of a response for querying a task result

{
    "request_id": "22f9c744-206c-9a78-899a-xxxxxx",
    "output": {
        "task_id": "4a0f8fc6-03fb-4c44-a13a-xxxxxx",
        "task_status": "SUCCEEDED",
        "results": [{
           "orig_prompt": "A flower shop with exquisite windows, a beautiful wooden door, and flowers on display",
            "actual_prompt": "A flower shop with exquisitely carved windows and a beautiful dark wooden door slightly ajar. Inside, a variety of colorful and fragrant flowers, including roses, lilies, and sunflowers, are on display. The background is a warm indoor scene with soft light shining on the flowers through the window. High-definition realistic photography, medium shot composition.",
            "url": "https://dashscope-result-wlcb.oss-cn-wulanchabu.aliyuncs.com/1.png"
        }],
        "task_metrics": {
            "TOTAL": 1,
            "SUCCEEDED": 1,
            "FAILED": 0
        }
    },
    "usage": {
        "image_count": 1
    }
}

Limitations

  • Data validity: The task_id and image url are retained for only 24 hours. After this period, they cannot be queried or downloaded.

  • Content moderation: The input prompt and the output image are both subject to content moderation review. Requests that contain prohibited content result in an `IPInfringementSuspect` or `DataInspectionFailed` error. For more information, see Error messages.

  • Network access configuration: Image URLs are stored in Object Storage Service. If your business system cannot access external OSS URLs due to security policies, you must add the following OSS domain names to the whitelist.

    # List of OSS domain names
    dashscope-result-bj.oss-cn-beijing.aliyuncs.com
    dashscope-result-hz.oss-cn-hangzhou.aliyuncs.com
    dashscope-result-sh.oss-cn-shanghai.aliyuncs.com
    dashscope-result-wlcb.oss-cn-wulanchabu.aliyuncs.com
    dashscope-result-zjk.oss-cn-zhangjiakou.aliyuncs.com
    dashscope-result-sz.oss-cn-shenzhen.aliyuncs.com
    dashscope-result-hy.oss-cn-heyuan.aliyuncs.com
    dashscope-result-cd.oss-cn-chengdu.aliyuncs.com
    dashscope-result-gz.oss-cn-guangzhou.aliyuncs.com
    dashscope-result-wlcb-acdr-1.oss-cn-wulanchabu-acdr-1.aliyuncs.com

Billing and rate limiting

  • For information about the model free quota and unit price, see Model list.

  • For information about model rate limits, see Wan.

  • Billing details:

    • Billing is based on the number of successfully generated images. You are charged only when the query result API returns a task_status of SUCCEEDED and an image is successfully generated.

    • Failed model calls or processing errors do not incur fees or consume the free quota.

Error codes

If a call fails, see Error messages for troubleshooting.

FAQ

Q: How do I view my model usage?

A: One hour after the model call is complete, you can go to the Model Observation (Singapore) or Model Observation (Beijing) page to view metrics such as the number of calls and the success rate. For more information, see How do I view model call records?