AI thumbnail maker for YouTube that remakes references around your title and persona
AI-powered video lip synchronization framework
Stage
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Founded
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Based in
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Pricing model
Freemium
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Pricing
Free: 2 credits. Starter: $12/month (40 credits) or $9/month billed yearly. Creator: $28/month (160 credits) or $21/month billed yearly. Studio: $56/month (400 credits) or $42/month billed yearly.
One-time payment plans: Starter $9.90 (500 credits), Pro $49.90 (2500 credits), Ultimate $99.90 (5000 credits). Average of 10 credits per second. All plans include high-quality generation, access to all major AI models, no watermark, and commercial use rights.
Key features
Reference-based thumbnail generation from YouTube links or uploaded images
Prompt-based thumbnail generation from video descriptions
Persona system with face generation or faceless options
Full HD+ output at 2048 × 1152 for 16:9 and 1152 × 2048 for 9:16
Edit thumbnails using plain text descriptions
Support for multiple languages in thumbnail text
Library of thousands of high-performing thumbnails from popular channels
No watermark on any plan including free credits
Automatic credit refund if thumbnail generation fails
Credit rollover option to carry unused credits to next month
Multi-language support for lip synchronization across different languages and accents
512x512 high-resolution video output
Real-time processing with efficient architecture
Temporal consistency mechanisms for smooth lip movements
Whisper integration for precise audio feature extraction
End-to-end latent diffusion without intermediate motion representations
Low VRAM requirements for accessible scaling
Flexible deployment with Gradio App and CLI interface
What makes it different
Reference-led approach gives a strong visual starting point without blank canvas
No design skills required, no layers or canvas tools
Same high quality generator on all plans including free tier
Personalized thumbnails with your face or faceless versions
Both landscape 16:9 and vertical 9:16 Shorts formats on every plan
Audio-conditioned latent diffusion without intermediate motion representations
Preserves original visual details and lighting in latent space
Language-agnostic processing works across different languages
Open source ecosystem with full access to code and checkpoints
Extensive research-backed algorithms for high-quality results
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