During February 2026, clmngu developed a performance-optimized DeformableConv2D operator for the RVV backend in the Tencent/ncnn repository. Focusing on hardware-aware optimization and performance engineering, clmngu implemented a new RVV kernel in C++ that accelerated deformable convolution workloads on RVV-enabled devices. The operator achieved speedups between 12.94x and 20.16x over the previous scalar implementation, directly improving model inference efficiency. This work leveraged deep learning and machine learning expertise to address the computational demands of deformable convolutions, delivering a robust feature enhancement. No bugs were fixed during this period, with primary contributions centered on feature delivery and measurable performance gains.