Integrated GPUs have become an indispensable component of mobile processors due to the increasing popularity of graphics applications. The GPU frequency is a key factor both in application throughput and mobile processor power consumption under graphics workloads. Therefore, dynamic power management algorithms have to assess the performance sensitivity to the GPU frequency accurately. Since the impact of the GPU frequency on performance varies rapidly over time, there is a need for online performance models that can adapt to varying workloads. This paper presents a light-weight adaptive runtime performance model that predicts the frame processing time. We use this model to estimate the frame time sensitivity to the GPU frequency. Our experiments on a mobile platform running common GPU benchmarks show that the mean absolute percentage error in frame time and frame time sensitivity prediction are 3.8% and 3.9%, respectively.