qwen-image-2-pro

$27

Pro Model Capabilities

• Professional Text Rendering: Multi-line and paragraph-level text with fine-grained detail

• Fine-grained Realism: Better textures and photorealistic scenes

• Stronger Semantic Adherence: More accurately follows complex prompts

• Complex Designs: Ideal for text + image combinations

Examples

Basic Text-to-Image

belt app run alibaba/qwen-image-2-pro --input '{

  "prompt": "A futuristic cityscape at sunset with flying cars"

}'

Text-Heavy Poster

belt app run alibaba/qwen-image-2-pro --input '{

  "prompt": "Healing-style hand-drawn poster featuring three puppies playing with a ball. The main title \"Come Play Ball!\" is prominently displayed at the top in bold, blue cartoon font. Below, the subtitle \"Join the Fun!\" appears in green font.",

  "width": 1024,

  "height": 1536,

  "prompt_extend": false

}'

Marketing Banner

belt app run alibaba/qwen-image-2-pro --input '{

  "prompt": "Professional marketing banner for summer sale. Large text \"SUMMER SALE\" in white on gradient sunset background. \"50% OFF\" in yellow below. Clean, modern design.",

  "width": 1920,

  "height": 1080,

  "prompt_extend": false,

  "negative_prompt": "blurry text, distorted text, low quality"

}'

Multiple Variations

belt app run alibaba/qwen-image-2-pro --input '{

  "prompt": "Minimalist logo design for a coffee shop called \"Bean & Brew\"",

  "num_images": 4

}'

Image Editing (Style Transfer)

belt app run alibaba/qwen-image-2-pro --input '{

  "prompt": "Make the person from Image 1 wear the outfit from Image 2",

  "reference_images": [

    {"uri": "https://example.com/person.jpg"},

    {"uri": "https://example.com/outfit.jpg"}

  ],

  "num_images": 2

}'

Reproducible Generation

belt app run alibaba/qwen-image-2-pro --input '{

  "prompt": "Abstract geometric art in blue and gold",

  "seed": 12345

}'

Input Options

Parameter

Type

Description

prompt

string

Required. What to generate or edit (max 800 chars)

reference_images

array

Input images for editing (1-3 images)

num_images

integer

Number of images to generate (1-6)

width

integer

Output width in pixels (512-2048)

height

integer

Output height in pixels (512-2048)

watermark

boolean

Add "Qwen-Image" watermark

negative_prompt

string

Content to avoid (max 500 chars)

prompt_extend

boolean

Enable prompt rewriting (default: true)

seed

integer

Random seed for reproducibility (0-2147483647)

Size constraint: Total pixels must be between 512×512 and 2048×2048.

Output

Field

Type

Description

images

array

The generated or edited images (PNG format)

output_meta

object

Metadata with dimensions and count

Text Rendering Tips

For best text results with the Pro model:

• Use quotes around exact text: "Title: \"Hello World!\""

• Specify font details: color, style, size, position

• Disable prompt_extend: Set prompt_extend: false for precise control

• Use negative prompts: "blurry text, distorted text, low quality"

Example prompt structure:

Poster with the title "GRAND OPENING" in large red serif font at the top center.

Below, the date "March 15, 2024" in smaller black text.

Background: elegant gold and white gradient.

Style: professional, clean, modern.

Recommended Negative Prompt

{

  "negative_prompt": "low resolution, low quality, deformed limbs, deformed fingers, oversaturated, waxy, no facial details, overly smooth, AI-like, chaotic composition, blurry text, distorted text"

}

Sample Workflow

# 1. Generate sample input to see all options

belt app sample alibaba/qwen-image-2-pro --save input.json

# 2. Edit the prompt

# 3. Run

belt app run alibaba/qwen-image-2-pro --input input.json

Python SDK

from inferencesh import inference

client = inference()

# Text-heavy poster

result = client.run({

    "app": "alibaba/qwen-image-2-pro",

    "input": {

        "prompt": "Poster with title \"Welcome!\" in bold blue text at top",

        "width": 1024,

        "height": 1536,

        "prompt_extend": False

    }

})

print(result["output"])

# Stream live updates

for update in client.run({

    "app": "alibaba/qwen-image-2-pro",

    "input": {

        "prompt": "Professional product photography of a watch"

    }

}, stream=True):

    if update.get("progress"):

        print(f"progress: {update['progress']}%")

    if update.get("output"):

        print(f"output: {update['output']}")

Related Skills

# Standard Qwen-Image (faster, general use)

npx skills add inference-sh/skills@qwen-image

# Full platform skill (all 250+ apps)

npx skills add inference-sh/skills@infsh-cli

# All image generation models

npx skills add inference-sh/skills@ai-image-generation

Browse all image apps: belt app store --category image

Documentation

• Running Apps - How to run apps via CLI

• Streaming Results - Real-time progress updates

• File Handling - Working with images