Open-source video generation models and world simulators
High-fidelity photorealistic AI image generation with natural prompting
Stage
Not given
Not given
Founded
Not given
Not given
Based in
US
Not given
Pricing model
Freemium
Open source
Pricing
Free plan: $0/month with 250 lifetime credits. Lite plan: 1,200 credits per month. Standard plan: 5,000 credits per month. Mochi video generation costs 100 credits; replay video costs 50 credits.
Free and open source
Key features
Text-to-video generation from written descriptions
Local execution and customization via open-source repository
ComfyUI integration for tailored experience
Interactive playground for testing capabilities
Commercial usage rights on paid plans
MP4 video format with H.264 encoding
Videos up to 5.4 seconds at 30fps
Video download for 30 days after generation
Watermark removal on paid plans
High queue priority for paid users
High-fidelity skin and eye rendering with fine pores and light reflections
Robust composition coherence for multi-subject scenes and action shots
Baked-in VAE with optimized color tuning
Simple natural language prompting without complex templates
Compatible with ComfyUI, Automatic1111, and Forge
Works with popular SDXL ControlNets and IP-Adapters
Thousands of compatible LoRAs available
Optimized CFG sensitivity for high quality at lower scales
Natural light scattering and structural accuracy
Experimental Catalyst branch for continuous model evolution
What makes it different
Apache 2.0 licensed open-source model for individual and commercial use
World simulator technology for embodied AI breakthroughs
Team with 55,000+ citations across foundational AI research
Run locally without vendor lock-in
State-of-the-art open text-to-video model
Minimal prompting complexity with natural language descriptions instead of complex embeddings
Eliminates artificial AI textures and generic rendering artifacts
Open-source with commercial use permissions
Seamless integration into existing AI image generation workflows
Continuously refined through community feedback and experimental development
CyberRealistic XL