The requirements on numerical simulation methods for multistage axial compressors are rising together with those on the machines they are helping to design. Industry demands compressors that are lighter, more compact, and higher-performing. Numerical simulations are used to achieve these goals and to meet stringent safety standards while reducing the necessity of costly tests to ensure both performance at design conditions and off-design operability. These challenges drive the need for more sophisticated numerical approaches, particularly in accurately capturing unsteady flow phenomena and moving beyond the limitations of the mixing-plane assumption used in conventional steady state simulations. The limitations of state-of-the art solution approaches to the steady Reynolds-averaged Navier-Stokes (RANS) equations if compared to extensive unsteady RANS (uRANS) assessments have been discussed in literature recently [1, 2]. For instance, [1] highlights noticeable deviations with regard to predictions of the overall compressor efficiency, the resulting massflow and the occurrence of surge within an axial multistage compressor. Furthermore, the general capability of non-linear frequency domain methods to predict the unsteady compressor performance at substantially lower computational hardware requirements and run times is demonstrated [1]. Extending the findings of [1, 2], this research focuses on the numerical prediction of a compressor’s throttling curve by means of hybrid RANS/uRANS simulations. Compared to [1], a minimal subset of unsteady interactions within the compressor main gas path is resolved by relying on a model order reduction approach formulated in the frequency domain - the harmonic balance method that is. This comprises the inevitably unsteady interaction between casing treatments and main gas path as well as transonic multistage interactions within the compressor. The results are compared to predictions generated by an established mixing-plane RANS method and are used to assess the potential, but also future challenges when applying hybrid RANS/uRANS methods to enhance computational predictions of modern axial multistage compressor flows.