To address the problems of multipath interference, high complexity and unstable performance of traditional detection algorithms in multiple-input multiple-output-orthogonal time-frequency space (MIMO-OTFS) systems under high-speed mobile scenarios, a detection algorithm (CG-MMSE-ADK-Best) for MIMO-OTFS systems based on the joint optimization of low-complexity minimum mean square error （MMSE） and K-Best is proposed.First, the conjugate gradient (CG) algorithm is introduced to iteratively solve the MMSE matrix equation, avoiding direct matrix inversion to reduce computational overhead.Second, CG-MMSE is combined and optimized with K-Best detection. The fixed path number strategy of the traditional K-Best algorithm is improved, and a dynamic K-value algorithm is proposed to further optimize complexity.Finally, the algorithm performance is verified through simulation experiments. The simulation results show that with 4-QAM modulation, path number K=8 and signal-to-noise ratio (SNR) of 20 dB, the proposed algorithm improves the bit error rate (BER) performance by 45.9% compared with the traditional K-Best algorithm. After integrating the dynamic path number algorithm, the BER curve is basically consistent with that of the fixed path number algorithm, but the computational complexity is significantly reduced due to the decrease in path number.The proposed algorithm can improve BER performance under the same path number and reduce computational complexity under the same BER, effectively solving the problems of high complexity and unstable performance of traditional algorithms. It provides technical support for the application of large-scale MIMO-OTFS systems in high-speed mobile scenarios.