We present a versatile quaternion-based inertial orientation estimation filter (VQF). Inclination drift from gyroscope strapdown integration is corrected from specific force measurements that are low-pass filtered in an almost-inertial frame to effectively compensate for instantaneous accelerations and decelerations. Heading drift is corrected via a scalar heading offset. The resulting decoupled state representation enables simultaneous 6D and 9D orientation estimation. We systematically evaluated the method on a rich orientation estimation benchmark dataset and show that the proposed method clearly outperforms three of the currently most commonly adopted and accurate inertial orientation estimation filters. The filter is available as open-source software, and its parameters are tuned to work well for a wide range of movements and application scenarios. The fundamentally different filtering approach with a decoupled state representation and novel inclination correction resulted in an unprecedented level of accuracy, with 41% lower orientation estimation errors and a twice-as-high inclination accuracy compared to existing state-of-the-art methods. This facilitates new and exciting high-precision applications in the field of inertial motion tracking.