To address the limited energy supply and insufficient transmission performance of heterogeneous bit and semantic communication networks （HBSCNs）， this paper investigates a movable antenna enabled wireless powered HBSCN （WP-HBSCN）. In the considered network， a hybrid access point （HAP） equipped with multiple movable antennas （MAs） first broadcasts radio-frequency energy signals to bit users and semantic users. Then， the users transmit bit and semantic information to the HAP by time-division multiple access using the harvested energy. By dynamically adjusting the positions of the MAs， additional spatial degrees of freedom are exploited to construct favorable channels for both downlink wireless energy transfer and uplink information transmission. To enhance the bit transmission performance while guaranteeing the quality-of-service requirements of semantic users， the total number of bit data maximization problem is formulated by jointly optimizing the energy beamforming vector， user transmit power， time-slot allocation， and MA positions. The formulated problem is challenging to solve directly because of the coupled optimization variables， nonlinear energy harvesting model， and non-convex antenna position constraints. To address this difficulty， an alternating optimization algorithm is developed based on the block coordinate descent framework. Specifically， the energy beamforming and power allocation subproblem is handled by successive convex approximation， the time-slot allocation subproblem is solved through convex optimization， and the MA position optimization subproblem is addressed using particle swarm optimization. Simulation results verify the convergence of the proposed algorithm and show that the MA-enabled scheme achieves a higher total number of bit data than the benchmark schemes， including the sparrow search-based scheme， equal time-slot allocation scheme， random beamforming scheme， and fixed-position antenna scheme. These results demonstrate the effectiveness of introducing MAs into the WP-HBSCN.