Sol Video Inference Engine: Agent-Native Full-Stack Acceleration Framework for Efficient Video Generation

The Sol Video Inference Engine is a new framework designed for optimizing video diffusion models through a training-free, agent-native approach. It integrates five techniques—cache, sparse attention, token pruning, quantization, and kernel fusion—into a customizable acceleration stack, achieving over 2x end-to-end acceleration while preserving near-lossless quality across models of varying sizes, including 64B Cosmos3-Super, 22B LTX-2.3, and 2B SANA-Video. This framework addresses the challenges of instance-specific optimization in video generation, making it a valuable tool for practitioners aiming to enhance performance in diverse hardware and model configurations.