This research presents an efficient and accurate nonlinear collocation-type meshfree framework to address numerical simulation challenges in material and geometric nonlinearities. Traditional mesh-based methods often distort under large deformations, while the limitations of existing meshfree methods range from the high computational cost of Galerkin-type methods to the inadequate accuracy and stability of conventional collocation methods. The core of this work is a Stabilized Collocation Method using reproducing kernel approximation. Employing regularized integration subdomains, it significantly improves computational accuracy and efficiency for problems involving elastoplasticity [1] and geometric large deformation [2]. Building on this foundation, a Gradient Smoothing Stabilized Collocation Method is further developed [3]. This technique transforms domain integrals into boundary integrals, substantially boosting computational efficiency while maintaining solution accuracy. For tackling high-order nonlinear dynamic problems, the framework is extended to a Gradient Reproducing Kernel Stabilized Collocation Method. This advancement successfully simulates complex phenomena such as solitary wave propagation, demonstrating excellent numerical conservation properties. A series of numerical benchmarks verifies that the proposed framework exhibits superior effectiveness and robust stability in handling multi-physics nonlinear problems. It thus provides a reliable, high-performance numerical tool for advanced analysis in complex nonlinear mechanics.