Traditional cellular network structure can no longer meet the growing demand for computing tasks. Using device to device (D2D) communication to offload tasks to nearby users can greatly reduce the energy consumption of task computation. However, existing methods overlook the limited resources of D2D idle devices. Therefore, to incentivize idle devices to participate in collaborative offloading, we suggest a mechanism that takes into account both price and computational resource allocation strategies, and present a price resource equilibrium scheme based on Stackelberg game theory. Besides, to optimize task publishers’ computational profit, we formulate a collaborative task allocation problem and introduce a bipartite matching-based optimal approach. According to simulation results, the proposed method outperforms the benchmark scheme in terms of efficient use of computer resources and can provide larger computational benefits.