Multi-stream programming mechanism can fully provide a variety of resource utilization methods such as pipelining and resource partitioning for heterogeneous many-core accelerators, but there is currently no effective guidance on how to choose effective resource utilization methods. Based on hStreams on heterogeneous manycore processor Intel MIC, we design a performance model for multi-stream program’s multihardware partitioning execution. Based on our performance model, we can identify the reasons for the performance difference of multi-stream programs under varied configurations, find out key factors that affect the performance, and provide a partitioning optimization strategy for multi-stream programs. In addition, it can also judge the effect of algorithm implementation. Our evaluation results show that the error between the estimated results of the performance model and the actual test results of multi-stream configuration is within 1%. Compared to the single-streamed version, our model also realizes a 5.83% performance improvement when guiding multi-stream programs of the dense matrix multiplication.