This study demonstrates the effective manipulation of antiferromagnetic order in the Weyl semimetal Mn₃Sn using orbital torques (OTs) generated by either metal Mn or oxide CuOₓ. The research shows that inserting a heavy metal layer, such as Pt, can significantly reduce the critical switching current density by one order of magnitude. The memristor-like switching behavior of Mn₃Sn can mimic the potentiation and depression processes of a synapse with high linearity, which is beneficial for constructing accurate artificial neural networks. The study highlights the potential of Mn₃Sn as a material for high-performance antiferromagnetic functional devices. The research also shows that OTs can be used to manipulate the magnetic order in topological antiferromagnets, offering an alternative to traditional spin current-based methods. The results indicate that the OT-driven switching in Mn₃Sn is highly efficient, with a critical switching current density as low as -1×10¹⁰ A/m². The study further demonstrates that Mn₃Sn can be used in neuromorphic computing due to its ability to mimic synaptic functions with high linearity. The findings suggest that Mn₃Sn-based devices could be used in future spintronic applications, including neuromorphic computing. The research also shows that the performance of Mn₃Sn-based devices can be optimized by adjusting the thickness of Pt and Mn layers. The study provides a new approach for manipulating the topological antiferromagnetic order, which could lead to more efficient spintronic devices.This study demonstrates the effective manipulation of antiferromagnetic order in the Weyl semimetal Mn₃Sn using orbital torques (OTs) generated by either metal Mn or oxide CuOₓ. The research shows that inserting a heavy metal layer, such as Pt, can significantly reduce the critical switching current density by one order of magnitude. The memristor-like switching behavior of Mn₃Sn can mimic the potentiation and depression processes of a synapse with high linearity, which is beneficial for constructing accurate artificial neural networks. The study highlights the potential of Mn₃Sn as a material for high-performance antiferromagnetic functional devices. The research also shows that OTs can be used to manipulate the magnetic order in topological antiferromagnets, offering an alternative to traditional spin current-based methods. The results indicate that the OT-driven switching in Mn₃Sn is highly efficient, with a critical switching current density as low as -1×10¹⁰ A/m². The study further demonstrates that Mn₃Sn can be used in neuromorphic computing due to its ability to mimic synaptic functions with high linearity. The findings suggest that Mn₃Sn-based devices could be used in future spintronic applications, including neuromorphic computing. The research also shows that the performance of Mn₃Sn-based devices can be optimized by adjusting the thickness of Pt and Mn layers. The study provides a new approach for manipulating the topological antiferromagnetic order, which could lead to more efficient spintronic devices.