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Alibaba Cloud Model Studio:Qwen - image editing API reference

Last Updated:Dec 16, 2025

qwen-image-edit-plus supports multi-image input and output. It can accurately modify text in an image, add, delete, or move objects, change the action of a subject, transfer an image style, and enhance image details.

Model overview

Multi-image fusion

image99

image98

image89

image100

imageout2

Input image 1

Input image 2

Input image 3

Make the girl from Image 1 wear the black dress from Image 2 and sit in the pose from Image 3.

image83

image103

1

2

imageout2

Input image 1

Input image 2

Input image 3

Make the girl from Image 1 wear the necklace from Image 2 and carry the bag from Image 3 on her left shoulder.

Single-image editing

image36

image38

image

image

Original image

Generate an image that matches the depth map, following this description: A dilapidated red bicycle is parked on a muddy path with a dense primeval forest in the background.

Original image

Replace the words "HEALTH INSURANCE" on the letter blocks with "明天会更好".

5

5out

6

6out

Original image

Replace the dotted shirt with a light blue shirt.

Original image

Change the background of the image to Antarctica.

Model

Description

Output image specifications

qwen-image-edit-plusRecommended

Currently has the same capabilities as qwen-image-edit-plus-2025-10-30

The qwen-image-edit-plus series models support single-image editing and multi-image fusion.

  • Can generate 1-6 images.

  • Supports custom resolutions.

  • Supports intelligent prompt optimization.

Format: PNG
Resolution:

  • Custom: Use the parameters.size parameter to specify the width*height of the output image in pixels.

  • Default (if not specified): The total number of pixels is close to 1024*1024, and the aspect ratio is the same as the input image (or the last image in a multi-image input).

qwen-image-edit-plus-2025-12-15 Recommended

qwen-image-edit-plus-2025-10-30 Recommended

qwen-image-edit

Supports single-image editing and multi-image fusion.

  • Generates only 1 image.

  • Does not support custom resolutions.

Format: PNG

Resolution: Not customizable. The generation follows the same default rule as above.

Note

Before you make a call, see the models and pricing for each region.

Billing description:

  • You are charged based on the number of images that are successfully generated. If a single request returns n images, the charge for that request is n × the unit price. Failed model calls or processing errors do not incur fees or consume the free quota.

  • You can enable the "Free Quota Only" feature to avoid additional charges after your free quota is exhausted. For more information, see Free quota for new users.

HTTP

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. The SDK is available for Python and Java.

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.

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

Single-image editing

This example uses the qwen-image-edit-plus model to generate two images.

The URL in this example is for the Singapore region. If you use a model in the Beijing region, replace the URL with: https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

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": "qwen-image-edit-plus",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/fpakfo/image36.webp"
                    },
                    {
                        "text": "Generate an image that matches the depth map, following this description: A dilapidated red bicycle is parked on a muddy path with a dense primeval forest in the background."
                    }
                ]
            }
        ]
    },
    "parameters": {
        "n": 2,
        "negative_prompt": "low quality",
        "prompt_extend": true,
        "watermark": false
    }
}'

Multi-image fusion

This example uses the qwen-image-edit-plus model to generate two images.

The URL in this example is for the Singapore region. If you use a model in the Beijing region, replace the URL with: https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

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": "qwen-image-edit-plus",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/thtclx/input1.png"
                    },
                    {
                        "image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/iclsnx/input2.png"
                    },
                    {
                        "image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/gborgw/input3.png"
                    },
                    {
                        "text": "Make the girl from Image 1 wear the black dress from Image 2 and sit in the pose from Image 3."
                    }
                ]
            }
        ]
    },
    "parameters": {
        "n": 2,
        "negative_prompt": "low quality",
        "prompt_extend": true,
        "watermark": false
    }
}'
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 to use. The following models are available:

qwen-image-edit-plus series models: including qwen-image-edit-plus, qwen-image-edit-plus-2025-12-15, and qwen-image-edit-plus-2025-10-30, support generating 1 to 6 images.

qwen-image-edit: Supports generating only one image.

input object (Required)

The input object, which contains the following fields:

Properties

messages array (Required)

An array that contains the content of the request. Currently, only single-turn conversations are supported. Therefore, the array must contain exactly one object. This object contains the role and content properties.

Properties

role string (Required)

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

content array (Required)

The content of the message. It includes one to three images in the {"image": "..."} format and a single editing instruction in the {"text": "..."} format.

Properties

image string (Required)

The URL or Base64-encoded data of the input image. You can provide 1 to 3 images.

For multi-image input, the order of the images in the array defines their sequence. The aspect ratio of the output image is determined by the last image.

Image requirements:

  • Image formats: JPG, JPEG, PNG, BMP, TIFF, WEBP, and GIF.

    The output image is in the PNG format. For animated GIFs, only the first frame is processed.
  • Image resolution: For best results, the width and height of the image should both be between 384 and 3072 pixels. A resolution that is too low may result in a blurry image, while one that is too high increases processing time.

  • Image size: No larger than 10 MB.

Supported input formats:

  1. Publicly accessible URL

    • Supports HTTP or HTTPS protocols.

    • Example: https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/fpakfo/image36.webp

  2. Base64-encoded image string

    • Example: data:image/jpeg;base64,GDU7MtCZz... (This example is truncated for demonstration purposes.)

    • For Base64 encoding specifications, see Pass an image using Base64 encoding.

text string (Required)

The image editing instruction, also known as the positive prompt. It describes the elements and visual features you want in the generated image.

When you edit multiple images, you must use descriptions such as "Image 1", "Image 2", and "Image 3" in the editing instruction to refer to the corresponding images. Otherwise, the editing results may not meet your expectations.

This parameter supports Chinese and English. The maximum length is 800 characters. Each Chinese character or letter is counted as one character. Content that exceeds the limit is automatically truncated.

Example: Make the girl from Image 1 wear the black dress from Image 2 and sit in the pose from Image 3. Keep her clothing, hairstyle, and expression unchanged, and ensure the action is natural and smooth.

parameters object (Optional)

Additional parameters to control image generation.

Properties

n integer (Optional)

The number of images to generate. The default value is 1.

For qwen-image-edit-plus series models, you can generate 1 to 6 images.

For qwen-image-edit, only one image can be generated.

negative_prompt string (Optional)

The negative prompt. It describes the content you do not want to see in the image and can be used to constrain the output.

This parameter supports Chinese and English. The maximum length is 500 characters. Each Chinese character or letter is counted as one character. Content that exceeds the limit is automatically truncated.

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

size string (Optional)

Specifies the resolution of the output image in the width*height format, such as "1024*2048". The width and height values must be in the range of [512, 2048] pixels.

Default behavior: If you do not set this parameter, the output image maintains an aspect ratio similar to the input image (or the last image in a multi-image input), with a resolution close to 1024*1024.

Limits: This parameter is available only when the number of output images n is 1. Otherwise, an error is reported.

Supported models: Only the qwen-image-edit-plus series models support this parameter.

prompt_extend bool (Optional)

Specifies whether to enable prompt rewriting. When enabled, a large language model optimizes the positive prompt. This feature significantly improves results for simple or less descriptive prompts.

  • true: (Default)

  • false

Supported models: Only the qwen-image-edit-plus models support this parameter.

watermark bool (Optional)

Specifies whether to add a "Qwen-Image" watermark to the bottom-right corner of the image. The default value is false. Watermark:

1

seed integer (Optional)

The random number seed. The value must be an integer in the range of [0, 2147483647].

Using the same seed parameter value helps ensure the consistency of the generated content. If you do not specify this parameter, the algorithm uses a random number seed.

Note: The model generation process is probabilistic. Even if you use the same seed, the results are not guaranteed to be identical for each request.

Response parameters

Successful task execution

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": {
                    "role": "assistant",
                    "content": [
                        {
                            "image": "https://dashscope-result-sz.oss-cn-shenzhen.aliyuncs.com/xxx.png?Expires=xxx"
                        },
                        {
                            "image": "https://dashscope-result-sz.oss-cn-shenzhen.aliyuncs.com/xxx.png?Expires=xxx"
                        }
                    ]
                }
            }
        ]
    },
    "usage": {
        "width": 1248,
        "image_count": 2,
        "height": 832
    },
    "request_id": "bf37ca26-0abe-98e4-8065-xxxxxx"
}

Abnormal task execution

If a task fails, the response returns relevant information. You can identify the cause of the failure from the code and message fields. For more information about how to resolve errors, see Error codes.

{
    "request_id": "31f808fd-8eef-9004-xxxxx",
    "code": "InvalidApiKey",
    "message": "Invalid API-key provided."
}

output object

The results generated by the model.

Properties

choices array

A list of generated results.

Properties

finish_reason string

The reason the generation task stopped. A value of stop indicates that the task completed successfully.

message object

The message returned by the model.

Properties

role string

The role of the message sender. The value is assistant.

content array

The content of the message, which contains information about the generated image.

Properties

image string

The URL of the generated image, in PNG format. The link is valid for 24 hours. Download and save the image promptly.

usage object

The resource usage for this request. This parameter is returned only when the request is successful.

Properties

image_count integer

The number of generated images, which is the same as the number of output images specified in the request.

width integer

The width of the generated image in pixels.

height integer

The height of the generated image in pixels.

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.

DashScope SDK

The SDK parameter names are mostly consistent with the HTTP API. The parameter structure is adapted for each programming language. For a complete list of parameters, see the Qwen API reference.

Python SDK

Note
  • Install the latest version of the DashScope Python SDK. Otherwise, runtime errors may occur: Install or upgrade the SDK.

  • Asynchronous APIs are not supported.

Request examples

This example uses the qwen-image-edit-plus model to generate two images.

Pass an image using a public URL

import json
import os
import dashscope
from dashscope import MultiModalConversation

# 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'

# The model supports one to three input images.
messages = [
    {
        "role": "user",
        "content": [
            {"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/thtclx/input1.png"},
            {"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/iclsnx/input2.png"},
            {"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/gborgw/input3.png"},
            {"text": "Make the girl from Image 1 wear the black dress from Image 2 and sit in the pose from Image 3."}
        ]
    }
]

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

# qwen-image-edit-plus supports outputting 1 to 6 images. This example shows how to output 2 images.
response = MultiModalConversation.call(
    api_key=api_key,
    model="qwen-image-edit-plus",
    messages=messages,
    stream=False,
    n=2,
    watermark=False,
    negative_prompt="low quality",
    prompt_extend=True,
    # The size parameter is supported only when the number of output images n is 1. Otherwise, an error is reported.
    # size="1024*2048",
)

if response.status_code == 200:
    # To view the full response, uncomment the following line.
    # print(json.dumps(response, ensure_ascii=False))
    for i, content in enumerate(response.output.choices[0].message.content):
        print(f"URL of output image {i+1}: {content['image']}")
else:
    print(f"HTTP status code: {response.status_code}")
    print(f"Error code: {response.code}")
    print(f"Error message: {response.message}")
    print("For more information, see the documentation: https://www.alibabacloud.com/help/en/model-studio/error-code")

Pass an image using Base64 encoding

import json
import os
import dashscope
from dashscope import MultiModalConversation
import base64
import mimetypes

# 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'


# --- For Base64 encoding ---
# Format: data:{mime_type};base64,{base64_data}
def encode_file(file_path):
    mime_type, _ = mimetypes.guess_type(file_path)
    if not mime_type or not mime_type.startswith("image/"):
        raise ValueError("Unsupported or unrecognized image format")

    try:
        with open(file_path, "rb") as image_file:
            encoded_string = base64.b64encode(
                image_file.read()).decode('utf-8')
        return f"data:{mime_type};base64,{encoded_string}"
    except IOError as e:
        raise IOError(f"Error reading file: {file_path}, Error: {str(e)}")


# Get the Base64 encoding of the image.
# Call the encoding function. Replace "/path/to/your/image.png" with the path to your local image file. Otherwise, the code will not run.
image = encode_file("/path/to/your/image.png")

messages = [
    {
        "role": "user",
        "content": [
            {"image": image},
            {"text": "Generate an image that matches the depth map, following this description: A dilapidated red bicycle is parked on a muddy path with a dense primeval forest in the background."}
        ]
    }
]

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

# qwen-image-edit-plus supports outputting 1 to 6 images. This example shows how to output 2 images.
response = MultiModalConversation.call(
    api_key=api_key,
    model="qwen-image-edit-plus",
    messages=messages,
    stream=False,
    n=2,
    watermark=False,
    negative_prompt="low quality",
    prompt_extend=True,
    # The size parameter is supported only when the number of output images n is 1. Otherwise, an error is reported.
    # size="2048*1024",
)

if response.status_code == 200:
    # To view the full response, uncomment the following line.
    # print(json.dumps(response, ensure_ascii=False))
    for i, content in enumerate(response.output.choices[0].message.content):
        print(f"URL of output image {i+1}: {content['image']}")
else:
    print(f"HTTP status code: {response.status_code}")
    print(f"Error code: {response.code}")
    print(f"Error message: {response.message}")
    print("For more information, see the documentation: https://www.alibabacloud.com/help/en/model-studio/error-code")

Download an image from a URL

# You need to install requests to download the image: pip install requests
import requests


def download_image(image_url, save_path='output.png'):
    try:
        response = requests.get(image_url, stream=True, timeout=300)  # Set timeout
        response.raise_for_status()  # Raise an exception if the HTTP status code is not 200.
        with open(save_path, 'wb') as f:
            for chunk in response.iter_content(chunk_size=8192):
                f.write(chunk)
        print(f"Image downloaded successfully to: {save_path}")

    except requests.exceptions.RequestException as e:
        print(f"Image download failed: {e}")


image_url = "https://dashscope-result-sz.oss-cn-shenzhen.aliyuncs.com/xxx.png?Expires=xxx"
download_image(image_url, save_path='output.png')

Response example

The image link is valid for 24 hours. Download the image promptly.

input_tokens and output_tokens are compatibility fields. Their values are currently fixed at 0.
{
    "status_code": 200,
    "request_id": "121d8c7c-360b-4d22-a976-6dbb8bxxxxxx",
    "code": "",
    "message": "",
    "output": {
        "text": null,
        "finish_reason": null,
        "choices": [
            {
                "finish_reason": "stop",
                "message": {
                    "role": "assistant",
                    "content": [
                        {
                            "image": "https://dashscope-result-sz.oss-cn-shenzhen.aliyuncs.com/xxx.png?Expires=xxx"
                        },
                        {
                            "image": "https://dashscope-result-sz.oss-cn-shenzhen.aliyuncs.com/xxx.png?Expires=xxx"
                        }
                    ]
                }
            }
        ]
    },
    "usage": {
        "input_tokens": 0,
        "output_tokens": 0,
        "height": 1248,
        "image_count": 2,
        "width": 832
    }
}

Java SDK

Note

Install the latest version of the DashScope Java SDK. Otherwise, a runtime error may occur: Install or upgrade the SDK.

Request examples

The following example shows how to use the qwen-image-edit-plus model to generate two images.

Pass an image using a public URL

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.JsonUtils;
import com.alibaba.dashscope.utils.Constants;

import java.io.IOException;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
import java.util.List;

public class QwenImageEdit {

    static {
        // The following URL is 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";
    }
    
    // The API keys for the Singapore and Beijing regions are different. To obtain an API key, visit https://www.alibabacloud.com/help/en/model-studio/get-api-key.
    // If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey="sk-xxx"
    static String apiKey = System.getenv("DASHSCOPE_API_KEY");

    public static void call() throws ApiException, NoApiKeyException, UploadFileException, IOException {

        MultiModalConversation conv = new MultiModalConversation();

        // The model supports one to three input images.
        MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
                .content(Arrays.asList(
                        Collections.singletonMap("image", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/thtclx/input1.png"),
                        Collections.singletonMap("image", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/iclsnx/input2.png"),
                        Collections.singletonMap("image", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20250925/gborgw/input3.png"),
                        Collections.singletonMap("text", "Make the girl from Image 1 wear the black dress from Image 2 and sit in the pose from Image 3.")
                )).build();
        // qwen-image-edit-plus supports outputting 1 to 6 images. This example shows how to output 2 images.
        Map<String, Object> parameters = new HashMap<>();
        parameters.put("watermark", false);
        parameters.put("negative_prompt", "low quality");
        parameters.put("n", 2);
        parameters.put("prompt_extend", true);
        // The size parameter is supported only when the number of output images n is 1. Otherwise, an error is reported.
        // parameters.put("size", "1024*2048");

        MultiModalConversationParam param = MultiModalConversationParam.builder()
                .apiKey(apiKey)
                .model("qwen-image-edit-plus")
                .messages(Collections.singletonList(userMessage))
                .parameters(parameters)
                .build();

        MultiModalConversationResult result = conv.call(param);
        // To view the complete response, uncomment the following line.
        // System.out.println(JsonUtils.toJson(result));
        List<Map<String, Object>> contentList = result.getOutput().getChoices().get(0).getMessage().getContent();
        int imageIndex = 1;
        for (Map<String, Object> content : contentList) {
            if (content.containsKey("image")) {
                System.out.println("URL of output image " + imageIndex + ": " + content.get("image"));
                imageIndex++;
            }
        }
    }

    public static void main(String[] args) {
        try {
            call();
        } catch (ApiException | NoApiKeyException | UploadFileException | IOException e) {
            System.out.println(e.getMessage());
        }
    }
}

Pass an image using Base64 encoding

import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.JsonUtils;
import com.alibaba.dashscope.utils.Constants;

import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.Arrays;
import java.util.Base64;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
import java.util.List;

public class QwenImageEdit {

    static {
        // The following URL is 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";
    }
    
    // The API keys for the Singapore and Beijing regions are different. To obtain an API key, visit https://www.alibabacloud.com/help/en/model-studio/get-api-key.
    // If you have not configured the environment variable, replace the following line with your Model Studio API key: apiKey="sk-xxx"
    static String apiKey = System.getenv("DASHSCOPE_API_KEY");

    public static void call() throws ApiException, NoApiKeyException, UploadFileException, IOException {

        // Replace "/path/to/your/image.png" with the path to your local image file. Otherwise, the code will not run.
        String image = encodeFile("/path/to/your/image.png");

        MultiModalConversation conv = new MultiModalConversation();

        MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
                .content(Arrays.asList(
                        Collections.singletonMap("image", image),
                        Collections.singletonMap("text", "Generate an image that matches the depth map, following this description: A dilapidated red bicycle is parked on a muddy path with a dense primeval forest in the background.")
                )).build();
        // qwen-image-edit-plus supports outputting 1 to 6 images. This example shows how to output 2 images.
        Map<String, Object> parameters = new HashMap<>();
        parameters.put("watermark", false);
        parameters.put("negative_prompt", "low quality");
        parameters.put("n", 2);
        parameters.put("prompt_extend", true);
        // The size parameter is supported only when the number of output images n is 1. Otherwise, an error is reported.
        // parameters.put("size", "2048*1024");

        MultiModalConversationParam param = MultiModalConversationParam.builder()
                .apiKey(apiKey)
                .model("qwen-image-edit-plus")
                .messages(Collections.singletonList(userMessage))
                .parameters(parameters)
                .build();

        MultiModalConversationResult result = conv.call(param);
        // To view the complete response, uncomment the following line.
        // System.out.println(JsonUtils.toJson(result));
        List<Map<String, Object>> contentList = result.getOutput().getChoices().get(0).getMessage().getContent();
        int imageIndex = 1;
        for (Map<String, Object> content : contentList) {
            if (content.containsKey("image")) {
                System.out.println("URL of output image " + imageIndex + ": " + content.get("image"));
                imageIndex++;
            }
        }
    }

    /**
     * Encodes a file into a Base64 string.
     * @param filePath The file path.
     * @return A Base64 string in the format: data:{mime_type};base64,{base64_data}
     */
    public static String encodeFile(String filePath) {
        Path path = Paths.get(filePath);
        if (!Files.exists(path)) {
            throw new IllegalArgumentException("File does not exist: " + filePath);
        }
        // Detect the MIME type.
        String mimeType = null;
        try {
            mimeType = Files.probeContentType(path);
        } catch (IOException e) {
            throw new IllegalArgumentException("Cannot detect the file type: " + filePath);
        }
        if (mimeType == null || !mimeType.startsWith("image/")) {
            throw new IllegalArgumentException("Unsupported or unrecognized image format.");
        }
        // Read the file content and encode it.
        byte[] fileBytes = null;
        try{
            fileBytes = Files.readAllBytes(path);
        } catch (IOException e) {
            throw new IllegalArgumentException("Cannot read the file content: " + filePath);
        }

        String encodedString = Base64.getEncoder().encodeToString(fileBytes);
        return "data:" + mimeType + ";base64," + encodedString;
    }

    public static void main(String[] args) {
        try {
            call();
        } catch (ApiException | NoApiKeyException | UploadFileException | IOException e) {
            System.out.println(e.getMessage());
        }
    }
}

Download an image from a URL

import java.io.FileOutputStream;
import java.io.InputStream;
import java.net.HttpURLConnection;
import java.net.URL;
 
public class ImageDownloader {
    public static void downloadImage(String imageUrl, String savePath) {
        try {
            URL url = new URL(imageUrl);
            HttpURLConnection connection = (HttpURLConnection) url.openConnection();
            connection.setConnectTimeout(5000);
            connection.setReadTimeout(300000);
            connection.setRequestMethod("GET");
            InputStream inputStream = connection.getInputStream();
            FileOutputStream outputStream = new FileOutputStream(savePath);
            byte[] buffer = new byte[8192];
            int bytesRead;
            while ((bytesRead = inputStream.read(buffer)) != -1) {
                outputStream.write(buffer, 0, bytesRead);
            }
            inputStream.close();
            outputStream.close();
 
            System.out.println("Image downloaded successfully to: " + savePath);
        } catch (Exception e) {
            System.err.println("Image download failed: " + e.getMessage());
        }
    }
 
    public static void main(String[] args) {
        String imageUrl = "http://dashscope-result-bj.oss-cn-beijing.aliyuncs.com/xxx?Expires=xxx";
        String savePath = "output.png";
        downloadImage(imageUrl, savePath);
    }
}

Response example

The image link is valid for 24 hours. Download the image promptly.

{
    "requestId": "46281da9-9e02-941c-ac78-be88b8xxxxxx",
    "usage": {
        "image_count": 2,
        "width": 1216,
        "height": 864
    },
    "output": {
        "choices": [
            {
                "finish_reason": "stop",
                "message": {
                    "role": "assistant",
                    "content": [
                        {
                            "image": "https://dashscope-result-sz.oss-cn-shenzhen.aliyuncs.com/xxx.png?Expires=xxx"
                        },
                        {
                            "image": "https://dashscope-result-sz.oss-cn-shenzhen.aliyuncs.com/xxx.png?Expires=xxx"
                        }
                    ]
                }
            }
        ]
    }
}

Configure image access permissions

Images generated by the model are stored in Object Storage Service (OSS). Each image is assigned a publicly accessible OSS link, such as https://dashscope-result-xx.oss-cn-xxxx.aliyuncs.com/xxx.png. You can use this link to view or download the image. The link is valid for only 24 hours.

If your business has high security requirements and you cannot access public OSS links, you can configure an access whitelist. Add the following domain names to your whitelist to ensure that you can access the image links.

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

Error codes

If a call fails, see Error messages for troubleshooting.

FAQ

Q: Does qwen-image-edit support multi-turn conversational editing?

A: No, it does not. The model only supports single-turn execution. Each call is an independent, stateless task. To perform continuous edits, you can use the generated image as a new input for another call.

Q: What languages do the qwen-image-edit and qwen-image-edit-plus series models support?

A: They officially support Simplified Chinese and English. You can try other languages, but their performance has not been fully verified and is not guaranteed.

Q: If I upload multiple reference images with different aspect ratios, which one determines the aspect ratio of the output image?

A: The output image will match the aspect ratio of the last uploaded reference image.

Q: How do I view model usage?

A: Model call data is available after a one-hour delay. You can go to the Model Observation (Singapore or Beijing) page to view metrics such as call usage, number of calls, and success rate. For more information, see How to view model call records.