Over the last several years, Oscillator Ising Machines (OIMs) have been shown to heuristically solve NP-hard combinatorial optimization (CO) problems, most notably MAX-CUT. In this paper, we show that OIMs are capable of solving Multi-User Multiple-Input-Multiple-Output (MU-MIMO) detection, an important real-world problem in telecommunications, achieving near-optimal Symbol Error Rates (SERs). Our results are obtained using CPU- and GPU-based simulation; the latter features a parallelizable event-based algorithm for the generalized Kuramoto equations that reduces OIM simulation times by about 6× without losing accuracy. We also find that good SER results are obtained if 6 or more bits are used to quantize the Ising problem's coupling weights. We provide runtime, throughput and energy consumption comparisons of different implementations and algorithms for MU-MIMO detection, including an OIM emulator chip we had reported earlier. Our results provide useful guidance for designing analog OIM ICs tailored for MU-MIMO detection.