Within the Sovereign AI Foundation Model Project, Nota optimized large-scale LLMs to run on fewer GPUs through model compression, while using Backend.AI and FastTrack to streamline experimentation and resource management. This enabled serving a 250B-scale model with significantly reduced GPU requirements while maintaining quality, and extending on-device techniques to data center scale.