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Abstract: State-of-the-art quantum circuit simulators have mostly focused on scaling the number of qubits. However, we argue that studying current noisy quantum computers and variational quantum algorithms benefits from high-throughput simulation of intermediate-scale quantum circuits. We present the first implementation and evaluation of a batched quantum simulator on the NEC Vector Engine (VE), a vector processor with massive memory bandwidth that is ideal for memory-intensive state vector simulation. To take advantage of the long-vector architecture of VE, we design a parallelization strategy and memory layout suited for batched state vector simulation. Our evaluation shows that the latest-generation VE Type 30A achieves equal performance as the NVIDIA A100 80 GB model for single-qubit gates, but slightly underperforms A100 for two-qubit gates. Furthermore, our vector-friendly noise gate implementation offers a large speedup compared to that of cuStateVec. When simulating a noisy 16-qubit random circuit with our simulator, VE30 is up to 1.95 × faster than A100.