Worked on stabilizing NPU-backed inference for the yhyang201/sglang repository by addressing a critical bug in the Qwen3 model’s precision path. Focused on aligning weight loading mechanisms with NPU-specific utilities to ensure compatibility with Qwen3-next w8a8 precision settings, this effort reduced the risk of precision errors in production environments. Utilized Python programming and deep learning techniques to validate and reinforce the NPU optimization process. The work involved careful debugging and integration of machine learning workflows, resulting in a more reliable deployment pipeline for NPU-supported models. This contribution emphasized robust engineering practices and attention to hardware-specific inference challenges.