Model Marketplace

Vidu Image Generation

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Overview

Input 0-14 reference images or text descriptions. Supports raw reference images, raw text images, and image editing. Offers accurate rendering of Chinese and English text, pixel-level reproduction of UI/chart design details, suitable for creating posters, infographics, etc.

Input

TextImage

Output

Image

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

  • Image Generation (1K)
    $0.1Per image
  • Image Generation (2K)
    $0.16Per image
  • Image Generation (4K)
    $0.24Per image

Rate Limits

  • Concurrency
    5concurrent
  • Async Queue Limit
    500tasks
  • RPMRequests Per Minute
    300

API Reference

Call API
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curl --location 'https://maas.qwencloudapi.com/api/v1/services/aigc/image-generation/generation' \
--header 'X-DashScope-Async: enable' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model": "vidu/vidu-image_reference2image",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "text": "A flower shop with exquisite windows, a beautiful wooden door, and flowers on display."
                    }
                ]
            }
        ]
    },
    "parameters": {
      "size":"1024*1024"
    }
}'