AI thumbnail maker for YouTube that generates scroll-stopping covers in seconds
Professional image generation and editing platform powered by Alibaba Tongyi's Z-Image series models
Stage
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Founded
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Based in
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Pricing model
Freemium
Freemium
Pricing
Lite: $19/month (or $14/month annually) for 35 thumbnails per month. Starter (most popular): $39/month (or $29/month annually) for 75 thumbnails per month. Pro: $79/month (or $59/month annually) for 200 thumbnails per month. All plans include a 7-day free trial and full access to 50+ style packs. Fr
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Key features
50+ pre-made Style Packs for different niches
Copy the visual style of any YouTube video or channel
Custom persona from 1-3 photos for consistent facial appearance
Plain-language editing with natural text commands
2K resolution thumbnails in 16:9 and 9:16 formats
Automatic video analysis from YouTube links
Video caption support up to 40 characters
Faceless channel support
Free tools including YouTube thumbnail downloader and resizer
Version history to revert to earlier thumbnail versions
Text-to-image generation
Image-to-image editing with natural language instructions
Bilingual Chinese and English text rendering
Sub-second latency generation with Z-Image-Turbo
6 billion parameter efficient model architecture
Photorealistic image generation
Commercial use license
No watermark output
Access to prompts gallery
What makes it different
Generate finished thumbnails in 30 seconds without designer experience
No complex prompts required—choose from proven style packs instead
Automatically reads video content to suggest appropriate thumbnail designs
Consistent facial appearance across all thumbnails via persona feature
2K resolution exports optimized for YouTube that stay under 2MB file limit
Supports both Chinese and English text rendering for multilingual image generation
Sub-second image generation speed with Z-Image-Turbo
Precise instruction-guided image editing based on natural language
Open-source Z-Image-Base model available for fine-tuning and custom development
Multiple model variants for different use cases and performance needs
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