November 2025 monthly summary for kvcache-ai/sglang focusing on the Dynamic padding and Piecewise CUDA Graph enhancements. Delivered a key feature: Piecewise CUDA graph execution support for Qwen3-next, enhancing performance for large-scale tensor operations. Fixed a critical bug: missing dp_max_padding argument in set_dp_buffer_len to ensure correct padding mode handling within PiecewiseCudaGraphRunner. This combination improved runtime performance, reliability, and flexibility for model execution while aligning with repository standards and performance goals. Overall impact: Improved throughput and stability for CUDA-graph based workflows, enabling more scalable inference for Qwen3-next and similar models. Demonstrated strong collaboration with the codebase through clear commit messages and maintainable changes.