qwen-image-pro
Generate images with Alibaba Qwen-Image-2.0-Pro via inference.sh CLI. Professional text rendering, fine-grained realism, enhanced semantic adherence. Ideal for posters, banners, and text-heavy designs. Triggers: qwen image pro, qwen-image-pro, qwen 2 pro, alibaba image pro, dashscope pro, professional text rendering
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/qwen-image-pro/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How qwen-image-pro Compares
| Feature / Agent | qwen-image-pro | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Generate images with Alibaba Qwen-Image-2.0-Pro via inference.sh CLI. Professional text rendering, fine-grained realism, enhanced semantic adherence. Ideal for posters, banners, and text-heavy designs. Triggers: qwen image pro, qwen-image-pro, qwen 2 pro, alibaba image pro, dashscope pro, professional text rendering
Which AI agents support this skill?
This skill is compatible with multi.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Qwen-Image Pro - Professional Image Generation
Generate images with Alibaba Qwen-Image-2.0-Pro via [inference.sh](https://inference.sh) CLI. Best for professional text rendering and complex designs.

## Quick Start
> Requires inference.sh CLI (`infsh`). Get installation instructions: `npx skills add inference-sh/skills@agent-tools`
```bash
infsh login
infsh app run alibaba/qwen-image-2-pro --input '{"prompt": "Poster with title \"Welcome!\" in bold blue text"}'
```
## 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
```bash
infsh app run alibaba/qwen-image-2-pro --input '{
"prompt": "A futuristic cityscape at sunset with flying cars"
}'
```
### Text-Heavy Poster
```bash
infsh 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
```bash
infsh 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
```bash
infsh 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)
```bash
infsh 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
```bash
infsh 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:
1. **Use quotes** around exact text: `"Title: \"Hello World!\""`
2. **Specify font details**: color, style, size, position
3. **Disable prompt_extend**: Set `prompt_extend: false` for precise control
4. **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
```json
{
"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
```bash
# 1. Generate sample input to see all options
infsh app sample alibaba/qwen-image-2-pro --save input.json
# 2. Edit the prompt
# 3. Run
infsh app run alibaba/qwen-image-2-pro --input input.json
```
## Python SDK
```python
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
```bash
# Standard Qwen-Image (faster, general use)
npx skills add inference-sh/skills@qwen-image
# Full platform skill (all 150+ apps)
npx skills add inference-sh/skills@agent-tools
# All image generation models
npx skills add inference-sh/skills@ai-image-generation
```
Browse all image apps: `infsh app list --category image`
## Documentation
- [Running Apps](https://inference.sh/docs/apps/running) - How to run apps via CLI
- [Streaming Results](https://inference.sh/docs/api/sdk/streaming) - Real-time progress updates
- [File Handling](https://inference.sh/docs/api/sdk/files) - Working with images