- Hybrid Sliding Window Attention (Hybrid SWA) reduces KVCache storage and computation to about 1/7 of Full Attention, enhancing efficiency for long-context tasks.
- Sparse MoE activation maintains model capacity while reducing per-token compute, and multimodal encoders enable cross-modal understanding across vision, audio, and video.
- Optimizations include a dual KVCache pool for Full Attention and SWA layers, SWA-aware prefix cache trees for correct reuse, and a tiered caching system (GCache) for high performance and low cost.
- Scheduling strategies like KVCache affinity and priority for high-hit-rate requests improve throughput and reduce latency, especially in agentic scenarios.