AI image and video upscaler with 14 specialized models, up to 8K output
Open-source SDXL-based AI model for native high-resolution anime art generation
Stage
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Founded
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Based in
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Pricing model
Freemium
Open source
Pricing
Free: 5 upscales per month at 2K resolution, watermarked. Creator: $9/month for 50 images and 20 videos up to 8K. Pro: $19/month for 100 images and 30 videos. Studio: $39/month for 250 upscales and 90 videos. Business: $49/month for 500 upscales and 150 videos with API access. Annual plans save 20%.
Free for personal and research use; prohibits closed-source proprietary monetization
Key features
14 specialized AI models for different upscaling jobs
Upscale images and videos up to 8K resolution
Resumable uploads supporting files up to 2GB
REST API for programmatic upscaling
Most jobs complete in under 30 seconds
Watermark-free results on Pro and Business plans
Commercial license included on paid plans
Native 1536x1536 high-resolution generation without upscaling
Hybrid Prompting System combining natural English and Danbooru tags
Stable text encoder fine-tuning for superior concept understanding
Trained on comprehensive Danbooru2023 dataset
Full compatibility with ComfyUI, Automatic1111, Forge, and Draw Things
Superior anatomy rendering with flawless hands and character details
V-Prediction architecture for enhanced dynamic range and contrast
Highly flexible base canvas for LoRA training and custom checkpoints
What makes it different
14 transparent models, each labeled whether it invents detail or only recovers existing information
Unified cloud platform handling both images and video without separate tools
Batch processing and API access for production workflows
No file training: original media is never used for model improvement
Free tier available with no credit card required
Only open-source SDXL model natively trained at 1536x1536 resolution
Stylistically neutral untuned base canvas unlike Pony Diffusion
Continuous rapid iterations from v0.1 to v3.5 with aggressive optimization
Thousands of compatible community-trained LoRAs and derivatives