Shrinking process technologies and growing chip sizes have profound effects on process variation. This leads to ChipMultiprocessors (CMPs) where not all cores operate at maximum frequency. Instead of simply disabling the slower cores or using guard banding (running all at the frequency of the slowest logic block), we investigate keeping them active, and examine performance and power efficiency of using frequency-heterogeneous CMPs on multithreaded workloads. With uniform workload partitioning, one might intuitively expect slower cores to degrade performance. However, with non-uniform workload partitioning, we find that using both low and high frequency cores improves performance and reduces energy consumption over just running faster cores. Thread scheduling and workload partitioning naturally play significant roles in these improvements. We find that using under-performing cores improves performance by 16% on average and saves CPU energy by up to 16% across the NAS and SPEC-OMP benchmarks on a quad-core AMD platform. Workload balancing via dynamic partitioning yields results within 5% of the overall ideal value. Finally, we show feasible methods to determine at run time whether using a heterogeneous configuration is beneficial. We validate our work through evaluation on a real CMP.